Court filing

13A — In re Bank of America California Unemployment Benefits Litigation (Dkt. 591-22, S.D. Cal. No. 3:21-md-02992)

Filed October 17, 2025 in In re Bank of America California Unemployment Benefits Litigation; one of 1415 filings from this case.

Record facts

Court	U.S. District Court for the Southern District of California
Filed	2025-10-17

U.S. District Court for the Southern District of California · No. 3:21-md-02992-GPC-MSB · Doc. 591-22 · 2025-10-17 · Docket on CourtListener

Full text

DX 13.A
REDACTED VERSION OF
DOCUMENT SOUGHT TO
BE SEALED PURSUANT TO
STIPULATED
PROTECTIVE ORDER
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UNITED STATES DISTRICT COURT
SOUTHERN DISTRICT OF CALIFORNIA
IN RE BANK OF AMERICA CALIFORNIA
UNEMPLOYMENT BENEFITS LITIGATION
Case No. 3:21-md-02992-GPC-MSB
EXPERT REBUTTAL REPORT OF STEVE HINDLE
APRIL 4, 2025
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i
TABLE OF CONTENTS

I.
QUALIFICATIONS ...............................................................................................................1
II.
INTRODUCTION ..................................................................................................................2
A.
Case Background ...........................................................................................................2
B.
Summary of Mr. Minnucci’s March 4, 2025 Report .....................................................5
C.
Summary of Mr. Regan’s March 4, 2025 Report ..........................................................5
D.
Assignment ....................................................................................................................6
III. SUMMARY OF OPINIONS ..................................................................................................7
IV. MR. MINNUCCI’S CALCULATION OF BOFA’S “AVOIDED” COST IS
UNRELIABLE .....................................................................................................................11
A.
Mr. Minnucci’s Assumption that BofA Could Have and Should Have
Accurately Forecasted Actual Call Volumes and Average Handle Times
Sufficiently in Advance of the Proposed Class Period Is Speculative and
Unsupported .................................................................................................................13
1. Mr. Minnucci’s Assumption that BofA Could Have and Should Have
Accurately Forecasted Actual Call Volumes is Speculative and
Unsupported Given the Unprecedented Increase in Call Volumes
During the Proposed Class Period ........................................................................ 14
2. Mr. Minnucci’s Assumption that BofA Could Have and Should Have
Accurately Forecasted the Average Call Handle Time is Speculative
and Unsupported ................................................................................................... 19
3. Mr. Minnucci’s Claim that BofA Had a “Highly Reliable” Forecasting
Method of Call Volume Is Misleading and Incorrect ........................................... 21
B.
Mr. Minnucci’s Calculation of “Distinct Caller Demand” Is Speculative ...................23
C.
Mr. Minnucci’s Calculation of BofA’s Avoided Costs of Idle Hours Is
Unreliable ....................................................................................................................27
D.
Mr. Minnucci’s Calculation Ignores That BofA Did Not Avoid the Entirety of
Additional CSR Costs ..................................................................................................29
V.
MR. MINNUCCI HAS NOT SHOWN THAT HIS “INDUSTRY”
BENCHMARK OF ASA IS APPROPRIATE, RENDERING MR. REGAN’S
CALCULATION OF DAMAGES SUFFERED BY THE PROPOSED
CUSTOMER SERVICE CLASS DUE TO “EXCESS WAIT TIMES”
UNRELIABLE .....................................................................................................................29
A.
Contrary to Mr. Minnucci’s Claims, There Is No Universal “Industry
Standard” for Call Center Wait Times.........................................................................30
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ii
B.
Mr. Minnucci Fails to Consider that BofA Was Exempt from SLAs Related to
Wait Times During the Proposed Class Period ...........................................................33
VI. MR. MINNUCCI FAILS TO CONSIDER THAT BOFA TOOK REASONABLE
STEPS TO INCREASING STAFFING DURING AND AFTER THE
PROPOSED CLASS PERIOD .............................................................................................36
A.
After Experiencing Unanticipated Increase in Call Volume, BofA Quickly
Adjusted to New Information in Real Time ................................................................37
B.
BofA’s Real-Time Staffing Approach to Real Time Call Demand is
Consistent with Industry Practice ................................................................................41
VII. MR. MINNUCCI’S CLAIM ON BOFA’S BROADER SYSTEMIC FAILURE
TO REASONABLY OPERATE ITS PREPAID CALL CENTERS IS
UNSUPPORTED ..................................................................................................................44
A.
Mr. Minnucci’s Criticisms Regarding BofA’s Failure for Disaster Planning
Are at Odds with Reality .............................................................................................44
B.
Mr. Minnucci’s Criticism Regarding BofA’s Failure to Adopt Virtual Queuing
and Estimated Wait Time Notifications Is Unfounded ................................................47
C.
Mr. Minnucci’s Claims Regarding BofA’s “Lax Security Protocols in the
Transition to Work-from-Home” Are False ................................................................50
1. It Was Reasonable for BofA to Delegate Specific Compliance
Requirements to Call Center Vendors Employing and Managing CSRs ............. 50
2. It Was Not Unreasonable for BofA to Temporarily Suspend State and
Local Background Checks During COVID-19 ..................................................... 52
3. The Bank’s WFH Requirements Were Consistent With Industry
Practice .................................................................................................................. 54

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I.
QUALIFICATIONS
1.
I have worked in the contact center industry for 30 years. Over the course of my career, I
have held roles in direct service, operations management, and senior leadership in the contact
center industry for several global multi-billion dollar public and private Business Process
Outsource (BPO) organizations.
2.
I began my career at Royal Bank of Scotland’s support center in 1994. In 1996, I joined
McQueen Ltd., a pioneer of offshore global Business Process Outsource (BPO) in the contact
center industry. At McQueen Ltd., I served as an integral operations and technology leader,
overseeing the architecture and infrastructure planning for the first global BPO organization
in the Philippines. This initiative laid the foundation for the outsourced contact center and
offshore customer service industry now utilized by Fortune 500 through Fortune 50
companies. I became a Regional Manager in 2016, after McQueen Ltd. was acquired by
Sykes Enterprises Inc., a market leader in serving financial sector clients, predominantly
global and geographically regional banks. From 1998 to 2016 at Sykes Enterprises Inc., my
responsibilities increased to Senior Director of Global Security Operations. In 2016, I joined
Sitel Group and became Global Vice President.
3.
In 1998, I developed a specialized Training and Consultancy Solutions division at McQueen
Ltd. that provided highly specialized training services; the two largest revenue clients for this
contact center business unit were global banking institutions. As Senior Director of Sykes
Enterprises Inc. in 2012, I developed and led the governance programs that ensured
regulatory and industry compliance for, among others, global banking institutions, and their
geographies. In 2016, I developed a client-metrics compliance program for a customer
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service, multi-million dollar line of business at Sykes Enterprises Inc. This program was
considered an industry differentiator, and pioneered operational metrics compliance
programs and adoption across the contact center industry, in monitoring call center metrics,
reducing fraud volumes, and ensuring the highest levels of customer satisfaction.
4.
Throughout my contact center career, I have led technology teams to implement the strict
requirements of financial institutions when engaging with BPOs to serve their customers,
particularly around telephony and IT infrastructure that handles call volumes and facilitates
omni-channel customer interactions through voice, email, and chat support. As Global Vice
President at Sitel Group, a leading BPO serving the financial sector, I was accountable for $8
million P&L and managing technology for client programs that generated $4 billion in
revenue. During the pandemic, I oversaw 160,000 contact center employees (60% of which
were impacted and worked remotely) in over 40 countries, processing over 8 million
customer interactions every day.
II.
INTRODUCTION
A. Case Background
5.
Plaintiffs in this matter brought a proposed class action against Defendant Bank of America,
N.A. (“Bank of America” or “Bank”) for its alleged failures with regards to its contract with
the California Employment Development Department (EDD) to issue and service prepaid
debit cards to California residents who EDD determines are eligible for EDD benefits
including, for example, benefit payments for unemployment insurance and disability
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insurance.1 Among other things, Plaintiffs allege that Bank of America implemented a
Claims Fraud Filter on September 28, 20202 that deprived them of access to the benefits they
allege they were legally entitled to.3 Plaintiffs further claim that the Bank failed to provide
adequate customer service and issued prepaid debit cards without proper security features,
making the accounts vulnerable to fraud.4
6.
Plaintiffs seek certification of five classes, including a proposed “Customer Service Class”
that is comprised of those who telephoned Bank of America’s customer service telephone
number for its EDD prepaid debit cardholders at any time between September 13, 2020
through November 21, 2020, and whose telephone call was routed to the Bank’s Claims Call
Center.5
7.
On August 29, 2024, Mr. Jay Minnucci submitted an expert report.6 Among other things, he
opined that the average speed to answer (“ASA”) of 75 seconds (1.25 minutes) is an
appropriate industry benchmark to assess the wait times experienced by members of the

1
Third Amended Master Consolidated Complaint, In re: Bank of America California Unemployment Benefits
Litigation, No. 3:21-md-02992-GPC-MSB, United States District Court for the Southern District of California,
January 24, 2025 (“TAMCC”), ¶¶ 38-41.
2
Memorandum of Points and Authorities in Support of Motion for Class Certification, In re: Bank of America
California Unemployment Benefits Litigation, No. 3:21-md-02992-GPC-MSB, United States District Court for
the Southern District of California, August 29, 2024 (“Motion for Class Certification”), p. 2.
3
TAMCC, ¶¶ 93-96.
4
TAMCC, ¶¶ 55-69, 97-105.
5
The other four proposed classes are “Claim Denial Class,” “Credit Rescission Class,” “Account Freeze Class,”
and “EMV Chip Class.” Memorandum of Points and Authorities in Support of Motion for Class Certification,
Exhibit 4, Expert Class Certification Report of Greg J. Regan, CPA/CFF, CFE, August 29, 2024 (“Regan Class
Certification Report”), ¶ 4; Memorandum of Points and Authorities in Support of Motion for Class
Certification, Exhibit 3, Expert Report of Jay Minnucci, August 29, 2024 (“Minnucci Class Certification
Report”), ¶ 2.
6
Minnucci Class Certification Report.
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proposed Customer Service Class.7 Additionally, Mr. Greg Regan submitted an expert report
on August 29, 2024, opining, among other things, that actual damages for members of the
proposed Customer Service Class can be calculated on a class wide basis.8 He opined that
such damages can be measured by the value of class members’ lost time spent on hold with
the Claims Call Center that exceeded the industry benchmark ASA of 75 seconds proposed
by Mr. Minnucci.9
8.
On October 24, 2024, I submitted a declaration in response to certain opinions offered by Mr.
Minnucci and Mr. Regan in their expert reports dated August 29, 2024. In that declaration,
my opinions included that the actual damages for individual members of the proposed
Customer Service Class cannot reliably be calculated on a class wide basis using the
methodology proposed by Mr. Regan. I also opined that Mr. Minnucci had not shown that his
proposed industry benchmark for ASA is appropriate, which further rendered Mr. Regan’s
proposed damages calculation on an aggregate level speculative and unreliable.10
9.
On November 21, 2024, Mr. Minnucci submitted a rebuttal report in response to my prior
declaration, in which he challenged my qualifications and made several arguments that he
repeated in his latest report served on March 4, 2025 as I discuss below.11

7
Minnucci Class Certification Report, ¶¶ 12, 46.
8
Regan Class Certification Report, ¶ 113.
9
See Regan Class Certification Report.
10 Declaration of Laura Brys in Support of Defendant’s Memorandum in Opposition to Plaintiffs’ Motion for
Class Certification, Ex. (“DX”) 5, Expert Declaration of Stephen Hindle, October 24, 2024 (“Hindle Class
Certification Declaration”).
11 See Declaration of Connie K. Chan in Support of Plaintiff’s Motion for Class Certification, Ex. (“PX”) 161,
Expert Rebuttal Report of Jay Minnucci, November 21, 2024 (“Minnucci Class Certification Rebuttal Report”).
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B. Summary of Mr. Minnucci’s March 4, 2025 Report
10.
On March 4, 2025, Mr. Minnucci served an expert report in which he opined that:12
x “The Bank subjected EDD debit cardholders seeking assistance with unauthorized-
transaction claims to long wait times that were unprecedented and fell far below industry
performance standards;”
x “The Bank’s practice of understaffing its Claims call center in the face of foreseeable call
volume surges was inconsistent with industry standard practices;”
x “The substandard performance levels in the Bank’s Claims call center from September
13, 2020 through November 21, 2020 reflected the Bank’s broader systemic failure to
operate its prepaid call centers consistent with industry standards.”
11.
In addition, Mr. Minnucci provided an estimate of call center representative (“CSR”) costs
that the Bank “avoided” by allowing the staffing level in the Claims Call Center to drop
below what was required. Mr. Minnucci’s calculation includes two types of CSR costs: (1)
cost associated with workload hours (i.e., time CSRs spend processing calls) and (2) cost
associated with idle time (i.e., time CSRs are waiting for the next call to arrive). For each
type of CSR cost, Mr. Minnucci calculated the “avoided” cost as the difference between his
estimate of required workload/idle hours and the actual workload/idle hours, multiplied by
the CSR’s hourly rate.13
C. Summary of Mr. Regan’s March 4, 2025 Report
12.
On March 4, 2025, Mr. Regan served an expert report in which he provides a methodology to
calculate class-wide damages available to each of the five classes of Plaintiffs, including the
Customer Service Class.14 Mr. Regan opines that actual damages for members of the
proposed Customer Service Class can be calculated on a class-wide basis, as the product of

12 Expert Report of Jay Minnucci, March 4, 2025 (“Minnucci Report”), section VII.A, B, C.
13 Minnucci Report, ¶¶ 109-113, Table 9, Table 10, Table 11, Appendix H, and Appendix I.
14 Expert Report of Greg J. Regan, CPA/CFF, CFE, March 4, 2025 (“Regan Report”).
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(1) the number of times each class member called and was transferred to the Bank’s Claims
Call Center, (2) the amount the ASA of the Bank’s Claims Call Center was allegedly in
excess of an industry benchmark offered by Mr. Minnucci (“approximately
per
call”), and (3) the California minimum wage.15
D. Assignment
13.
I have been retained by counsel for Defendant Bank of America, N.A. (“Bank of America” or
“BofA”) to respond to opinions Mr. Minnucci provided in his report filed on March 4,
2025.16 I have also been asked to respond to Mr. Regan’s calculations of Customer Service
Class damages provided in his report filed on March 4, 2025.17
14.
This report contains my current opinions in this matter. I reserve the right to supplement my
opinions if additional relevant information becomes available.
15.
The materials that I have personally reviewed and relied on in preparing this report are listed
in Appendix A of this declaration. A copy of my CV is attached hereto as Appendix B. I
have not provided any expert testimony in the past four years.
16.
Eleven Canterbury, an expert search firm, charges $925 per hour for my time spent on this
matter, from which I receive $695 per hour for my time on this matter. Employees of
Analysis Group, Inc. (“Analysis Group” or “AG”) working under my direction have assisted
me in this assignment. My fees, Eleven Canterbury’s fees, and Analysis Group’s fees do not
depend upon the opinions I form or upon the outcome of this litigation.

15 Regan Report, ¶¶ 91-93.
16 See Minnucci Report.
17 See Regan Report, Section V.B.
-
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III.
SUMMARY OF OPINIONS
17.
Below is a summary of the opinions I have reached, which I elaborate on in the body of my
report.
18.
Mr. Minnucci’s calculation of BofA’s “avoided cost” is unreliable
a. Mr. Minnucci’s calculation of BofA’s avoided cost relies on speculative and unsupported
assumptions, including that anyone could have accurately forecasted actual call volumes
and average handle times during the Proposed Class Period sufficiently far in advance to
staff up to levels sufficient to deal with the surge in volume.
i. Mr. Minnucci’s estimates of required hours are based on a speculative and
unsupported assumption that anyone could have accurately projected the call
volumes and average handle time with sufficient lead time for it to ramp up
the staffing accordingly. In my experience, forecasting the significantly
increased call volume and handle times that BofA experienced during the
Proposed Class Period would have been extremely challenging and virtually
impossible.
ii. Mr. Minnucci’s claim that BofA had a “highly reliable” Workforce
Management (“WFM”) model that can be used to forecast future call volume
but “chose” not to use it is misleading and incorrect. This WFM model is not a
forecasting model. Rather, it simply describes the contemporaneous
correlation between the Main Call Center’s call volume and the UI payment.
It was not developed for the Claims Call Center at issue. Nor can it be directly
used to forecast call volume five to seven weeks in advance. In fact, had BofA
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used this WFM model in the way Mr. Minnucci suggested, it would have
predicted a decline in the Claims Call Center’s volume.
iii. In estimating the number of distinct callers that would have called back, Mr.
Minnucci relies on (1) an “industry average abandonment rate” in 2020 based
on a survey of call centers not directly comparable to the Claims Call Center
and (2) an estimate of distinct call demand that he calculates based on call
record data supplied by consulting clients of his firm, Service Agility. Mr.
Minnucci has done nothing to show that these inputs are reasonable. Further,
he has not provided the underlying data from his clients for me to assess
whether the data he uses can be used to reliably infer the recall rates of the
Claims Call Center.
iv. In estimating the number of idle hours, Mr. Minnucci relies on (1) an
“industry average” ASA in 2020 based on a survey of call centers not directly
comparable to the Claims Call Center and (2) the Erlang-C formula which
uses over simplified assumptions that are not suitable for the Claims Call
Center.
b. Mr. Minnucci’s calculation of BofA’s avoided cost is conceptually flawed as it fails to
consider that BofA likely did not entirely avoid the workload and idle time costs Mr.
Minnucci estimated. To the extent that a portion of the CSR costs BofA incurred after the
Proposed Class Period was for addressing backlog of claims, and Mr. Minnucci has
provided no evidence to the contrary, these costs have been simply delayed, not
“avoided” as Mr. Minnucci claims.
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19.
Mr. Minnucci’s calculation of “excess wait times” experienced by members of the
Customer Service Class is unreliable.
a. Mr. Minnucci has not shown that his “industry” benchmark of ASA is appropriate and
thus his calculation of “excess wait times” experienced by the proposed Customer
Service Class is unreliable.
i. His industry standard ASA, obtained from a ContactBabel survey of 214 call
centers, does not account for differences between industries, nor does it reflect
conditions comparable to BofA’s Claims Call Center during the Proposed
Class Period.
ii. Mr. Minnucci fails to consider that CA EDD had explicitly waived SLA
penalties for wait times in the Claims Call Center during the Proposed Class
Period.
b. For these reasons, Mr. Regan’s calculation of damages suffered by the proposed
Customer Service Class due to “excess wait times” is also unreliable.
20.
Mr. Minnucci fails to consider that BofA took reasonable steps to increase staffing.
a. BofA

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b. Despite challenges caused by COVID-19, BofA

c. BofA’s approach was reasonable given the specific circumstances and consistent with
industry practice, in my experience.
21.
Mr. Minnucci’s claims that BofA failed to meet industry standards for disaster
planning, adoption of Virtual Queuing and Estimated Wait Time Notifications
technologies, background checks, and WFH security protocol are false.
a. In my experience, while the call center industry had general pandemic contingency plans,
fully preparing for all the outcomes COVID brought was not feasible. In my opinion,
BofA acted reasonably and commendably in responding to COVID-related challenges in
early 2020.
b. Mr. Minnucci fails to consider that deploying the Virtual Queuing and Estimated Wait
Time Notifications technologies in a uniform manner requires not only technology
upgrade and integration with existing telephony systems, but also extensive testing,
configuration, and coordination across all vendors. Thus, it would not have been feasible
to implement these technologies in a short time period to quickly and effectively address
unprecedented surges in call volume.
c. In my experience, it was reasonable for BofA to

.
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d. In my experience, it was not unreasonable for BofA to

e. Contrary to Mr. Minnucci’s claims, BofA

IV.
MR. MINNUCCI’S CALCULATION OF BOFA’S “AVOIDED” COST IS
UNRELIABLE
22.
Mr. Minnucci claims BofA’s “

.”18
Mr. Minnucci calculates two different types of BofA’s

.19
23.
To calculate “workload charges avoided,” Mr. Minnucci estimates the additional salary costs
BofA would have been required to pay to answer calls at the Claims Call Center assuming
only 6.1 percent of calls were abandoned, equal to the average abandonment rate based on a
survey from ContactBabel.20 To estimate the costs necessary to answer calls assuming an
only 6.1 percent abandonment rate, he performs the following calculations:

18 Minnucci Report, ¶ 108.
19 Minnucci Report, ¶¶ 106-108, Table 10, and Table 11.
20 Minnucci Report, ¶ 111, Table 10.
-
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a. Estimates “distinct caller demand”, which equals to the calls answered plus his estimate
of distinct abandoned callers.21
b. Estimates “expected calls answered” assuming 93.9 percent of calls are answered, which
equals to his estimate of one minus the 6.1 percent abandonment rate multiplied by his
estimate of “distinct caller demand.”22
c. Estimates the workload time to handle “expected calls answered” as “expected calls
answered” multiplied by the actual average handle time of calls answered.23
d. Estimates the cost of the workload time by multiplying the workload time to handle
“expected calls answered” by an hourly rate of $32.46.24
24.
From this estimate, Mr. Minnucci subtracts his estimate of the actual costs BofA incurred to
answer calls during the Proposed Class Period, equal to calls answered multiplied by average
handle times multiplied by an hourly rate of $32.46.25
25.
To calculate the “idle time charges avoided” Mr. Minnucci performs the following
calculations:
a. Distributes his estimate of “Distinct Caller Demand” (discussed above) into 30-minute
intervals based on “[t]ypical half-hourly distribution for Service Agility clients;”26
b. Estimates the number of CSRs required to meet the estimated “Distinct Caller Demand”
and “industry standard” ASA of 75 seconds” using the Erlang-C formula.27
c. Estimates the number of CSR idle hours by subtracting the CSR “staffed minutes” from
the “workload minutes” (calculated using the distinct caller demand), divided by 60.28

21 Minnucci Report, ¶ 110.
22 Minnucci Report, ¶ 111, Table 10.
23 Minnucci Report, ¶ 111, Table 9, Table 10.
24 Minnucci Report, ¶ 111, Table 10.
25 Minnucci Report, ¶ 111, Table 10.
26 Minnucci Report, ¶ 113, Appendix I.
27 Minnucci Report, ¶ 113, Appendix I.
28 Minnucci Report, ¶ 113, Appendix I.
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26.
Mr. Minnucci then multiples this estimated CSR idle hours29 by an hourly rate of $32.46 to
arrive at the “idle time charges avoided.”30
27.
As I discuss in this section, Mr. Minnucci’s calculation is unreliable because:
x Both his calculations of “workload charges avoided” and “idle time charges avoided”
rely on a speculative and unsupported assumption that BofA could have and should
have accurately forecasted actual call volumes and average handle times sufficiently
in advance of the Proposed Class Period to ramp up the staffing in the Claims Call
Center;
x His estimate of “workload charges avoided” suffers from additional flaws;
x His estimate of “idle time charges avoided” suffers from additional flaws;
x To the extent customers who abandoned calls during the Proposed Class Period called
back after the Proposed Class Period when BofA had significantly increased its FTEs,
he fails to consider that a portion of his additional costs are not avoided, just delayed.
A. Mr. Minnucci’s Assumption that BofA Could Have and Should Have Accurately
Forecasted Actual Call Volumes and Average Handle Times Sufficiently in Advance
of the Proposed Class Period Is Speculative and Unsupported
28.
Mr. Minnucci claims that “[i]f a planned company decision or policy change is expected to
drive an increase in call volume, it is industry-standard practice to increase staffing levels as
needed to maintain satisfactory call center performance levels, and to implement those
staffing changes before implementing the company decision that is anticipated to drive up
call volume.” 31 Thus, he appears to recognize that planning for call center staffing requires
forecasts of call volume. However, his estimate of avoided costs relies on actual data during
the Proposed Class Period, including calls answered, calls abandoned, and average handle
times. Further, as Mr. Minnucci acknowledges,

29 Mr. Minnucci assumes that “
Minnucci Report, Table 11.
30 Minnucci Report, ¶ 113, Table 11, Appendix I.
31 Minnucci Report, ¶ 45.
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32 Thus, for BofA to meet Mr. Minnucci’s expected
staffing level for the Claims Call Center, it not only had to accurately predict the future call
volumes and AHT but also had to predict the volumes and AHT
before
the start of the Proposed Class Period (i.e., by July 26, 2020 - August 9, 2020).33
1. Mr. Minnucci’s Assumption that BofA Could Have and Should Have Accurately
Forecasted Actual Call Volumes is Speculative and Unsupported Given the
Unprecedented Increase in Call Volumes During the Proposed Class Period
29.
The Claims Call Center experienced an unprecedented increase in call volume and average
handle time during the Proposed Class Period. As shown in Figure 3 of the Minnucci Report

34
Based on my experience, such a massive increase in call volume is rare in the industry and is
virtually impossible to be anticipated.

32 Minnucci Report, ¶ 61. This ramp up period (which includes the time spent to hire, train, and nest new CSRs) is
consistent with industry standards in my experience. Nesting “refers to the period immediately following formal
training, where new agents are given the opportunity to apply their learned skills in a live environment but with
enhanced support” (“What Is Nesting?” Call Centre Helper, available at
https://www.callcentrehelper.com/what-is-nesting-219108.htm). A CSR is not considered a fully trained
employee that handle calls independently until they have successfully passed through the nesting phase.
33 In my opinion, it would be unreasonable to assume that BofA could have hired, trained, and nested the amount
of CSRs suggested by Mr. Minnucci in less than five weeks in 2020, particularly considering the availability of
suitable talent pool at the time.
34 DX 116, BANA_EDD_MDL-00719115, tab “

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30.
Given that Mr. Minnucci's calculation of avoided costs relies on actual call volumes during
the Proposed Class Period, he implicitly assumes that BofA could have and should have
accurately forecasted the significant increase in Claims Call Center volume -
-
in advance to allow sufficient time to hire, train, and nest new CSRs. As shown in
Figure 2 below, with a
, Mr. Minnucci has effectively assumed that
BofA could have and should have anticipated increases of call volume
Mr. Minnucci has not shown such an assumption is reasonable.
35
DX 116, BANA_EDD_MDL-00719115, ta
15
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31.
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below and also testimony of Mr. William Golden, who was in charge of BofA's
EDD prepaid debit card operations between August 2020 and November 2021. 37
36
DX 116, BANA_EDD_MDL-00719115, tab'
16
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32.
33.
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38
------
Another expert, Ms. Teresa A. Pesce, finds that: 39
"During the COVID-19 pandemic, the number of unemployment benefits recipients
increased dramatically as the federal government broadened eligibility and EDD
abandoned many of its pre-pandemic controls. As the number of benefits recipients
increased and controls were relaxed the number of unauthorized transaction claims
-
,, As explained by another expert, Mr. Russell Cronan:40
38
BANA_EDD _MDL-00886356-358; BANA_EDD _MDL-00886359, tab
BANA_EDD_MDL-00104784-788, at 785; Golden Deposition, at pp. 296:24-297:3.
39
Expe1t Repo1t of Teresa A. Pesce, March 4, 2025 ("Pesce Repo1t"), ,r 43.
40
Expe1t Repo1t of Russell Cronan, March 4, 2025 ("Cronan Repo1t"), ,r 43.
17
"· '
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34.
Thus, Mr. Minnucci's assumption that BofA could have and should have accurately predicted
the increase in call volumes necessarily requires BofA to have been able to
. Mr. Minnucci has not shown how such a prediction could have been
reasonably done.
35.
fudeed, in my experience, historical call volume is a necessa1y input for developing any
forecast. However, during the several months immediately preceding the Proposed Class
Period (July and August 2020)
-
· 43 This made it paiiicularly difficult to forecast future volume at the time, as the most
41
Deposition of Paiz Alunad, January 29, 2025, at pp. 209: 17-210:8 and Exhibit 322.
42
Pesce Report, Exhibit 2, ,r 44 ("While historically the Bank received approximatelyllllunauthorized
transaction or e1rnr claims er month in its unem lo ment re aid card program, that number increased I
").
18
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recent historical call volume did not represent normal operating conditions, where the
expected population of callers is based on the scope of the program or service
provided. Instead, in the several months leading up to the Proposed Class Period, the call
metrics of the Claims Call Center were likely distorted by fraudulent activities. Unless there
is a reliable methodology to predict future fraudulent activity and its impact on call metrics
—and Mr. Minnucci has not presented one—this historical data cannot be used as a reliable
basis for forecasting.
36.
For all the reasons discussed above, I conclude that Mr. Minnucci’s assumption that BofA
could have and should have accurately predicted the unprecedented, massive increase in call
volumes sufficiently in advance of the Proposed Class Period is speculative and unsupported.
To the extent that Mr. Minnucci has overstated

44), he would have overstated
his estimate of “workload charges avoided.”
2. Mr. Minnucci’s Assumption that BofA Could Have and Should Have Accurately
Forecasted the Average Call Handle Time is Speculative and Unsupported
37.
In calculating the number of workload hours that BofA should have planned for, Mr.
Minnucci also assumes, without any support, that BofA could have and should have
accurately forecasted the actual AHT during the Proposed Class Period. As shown in Figure
4 below,
, Mr. Minnucci has effectively assumed that BofA

44 Deposition of Faiz Ahmad, January 29, 2025, at pp. 209:17-210:8 and Exhibit 322.
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-
Mr. Minnucci has not shown that such an assumption is reasonable. He has not
considered
45 -
46 -
47
-
38.
Further, such a substantial increase in AHT would compound the impact of the ah-eady large
spike in call volume, on staffing during the Proposed Class Period because Mr. Minnucci
45
Pesce Report, ,r,r 19, 21.
46
Pesce Report, ,r 46.
47
Deposition of Paiz Alunad, January 29, 2025, at pp. 209: 17-210:8 and Exhibit 322.
48
DX 116, BANA_EDD_MDL-00719115, tab'
20
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multiplies the estimated number of distinct caller demand by the AHT to aITive at the
expected CSR workload hours. 49 Based on my review of internal documents,
39.
Mr. Minnucci's implicit assumption that BofA could have and should have accurately
predicted the increase in AHT sufficiently in advance of the Proposed Class Period is
speculative and unsupported. To the extent that Mr. Minnucci has overstated the increase in
the Claims Call Center's AHT that BofA could have and should have reasonably anticipated
prior to the start of the Proposed Class Period, he would have overstated
his estimate of "workload charges avoided."
3. Mr. Minnucci 's Claim that Bo/A Had a "High~y Reliable" Forecasting Method of
Call Volume Is Misleading and Incorrect
40.
Mr. Minnucci claims that BofA's
49
Minnucci Report, Table 10.
cannot be used as a reliable basis for forecasting.
50
BANA_EDD_MDL-00886356-358, at 357.
21
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.51 Mr. Minnucci’s claim is misleading and incorrect in several ways.
41.
First, the BofA

. Minnucci argues that

,52
however, Mr. Minnucci has not done any analysis to validate this derivative relationship
using historical data (e.g., showing the “percentage” would have remained stable and
predictable), without which his statements are pure speculation.53
42.
Second, Mr. Minnucci mischaracterizes the BofA WFM Model as a forecasting model. In
fact, this model simply describes the contemporaneous correlation between the Main Call
Center’s call volume and the UI payment volume, and cannot be used directly to forecast call
volume in
based on the UI payment today.54 Furthermore, Mr. Minnucci
incorrectly states that the BofA

55 R2 only measures how well one data series explains the
variance in another. It does not measure the model’s predictive power or accuracy, i.e., it
does not indicate how well the BofA WFM Model can forecast call volume in say September
2020 using UI payment data available in July 2020.

51 Minnucci Report, ¶¶ 63-65.
52 Minnucci Report, ¶ 65.
53 Nor has he examined whether and how such a “derivative” relationship may change under different
circumstances, e.g., during times of significant increase in Claims Call Center volume, or after the
implementation of the Claims Fraud Filter.
54 One could use the BofA WFM Model to estimate future call volume based on future UI Payment volume.
However, Mr. Minnucci has not shown how BofA could have reliably forecasted the future UI payment amount
either.
55 Minnucci Report, ¶ 65.
I
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43.
Lastly, Mr. Minnucci has not considered whether this con-elation described in the BofA
The only input
to the BofA
56
57 Following Mr. Minnucci's logic, had BofA relied on this "highly reliable"
forecasting model, it would have predicted a decline in call volume to the Main Call Center,
and consequently, a decline in the Claims Call Center's call volume as well (which according
to Mr. Minnucci would simply be a
B. Mr. Minnucci's Calculation of "Distinct Caller Demand" Is Speculative
44.
Mr. Minnucci estimates the number of workload hours that BofA should have planned for
during the Proposed Class Period based on his estimate of "Distinct Caller Demand," which
equals the sum of actual calls answered and an estimated number of "Distinct Abandoned
Callers" (i.e., the number of abandoned calls BofA should have answered in the Claims Call
Center, after removing duplicate callers). 59
45.
To estimate the number of "Distinct Abandoned Callers," Mr. Minnucci multiplies the actual
number of calls abandoned by an "Estimated Percent of Abandons That Did Not Recall,"
which he derived using call record data from consulting clients of his own fom, Service
57
Minnucci Report, Appendix F.
58
Minnucci Report, ,r 65.
59
Minnucci Report, Table 9.
23
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Agility. Mr. Minnucci has done nothing to show that such record data are reasonable inputs.
Further, Mr. Minnucci has not produced the underlying data or provided sufficient
explanation for me to assess whether they can be used to reliably infer the recall rates of the
Claims Call Center. Based on the limited information I have, I see two potential issues with
his approach.
46.
First, Mr. Minnucci does not explain why the proprietary customer data he used as a basis for
this analysis is appropriate, and applicable to the experience of the at-issue Claims Call
Center. Given the nature of the calls to the Claims Call Center (e.g., EDD cardholder calling
to seek reconsideration of a claim that the Bank had automatically denied), I would expect a
higher recall rate, all else equal, than a call center that handles general inquiries like hotel
reservations which can be resolved using alternative means. Under Mr. Minnucci’s approach,
a higher recall rate would result in a lower distinct demand, which in turn yields a lower
estimate of “workload charges avoided.”
47.
Second, according to Appendix H of the Minnucci Report,

.60 In

Mr. Minnucci has not provided any support whether the relationship he examined
based on a limited sample would still hold during times with exceptionally high

60 Minnucci Report, Appendix H.
-
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abandonment rates. It is speculative for Mr. Minnucci to extrapolate the relationship outside
the range of the data points he observed. 61
48.
Third, although he provides no explanation, it appears that Mr. Minnucci aggregated his
individual client data into six data points based on predefined abandonment rate ranges. 63
Specifically, when analyzing the relationship between recall percentage and abandonment
rate, Mr. Minnucci appears to have used (1) the midpoint of each abandonment rate range
and (2) a single recall percentage for each abandonment rate range. 64 This aggregation
61
See, e.g., McClave, James T., and Terry Sincich, Statistics, 13th Edition, Pearson, 2018, at p. 779 ("One of the
problems was that many of the regression models were used to extrapolate (i.e., predict y for values of the
independent variables that were outside the region in which the model was developed). [ ... ] [T]he model may
be highly accurate in predicting y when x is in the range of experimentation, but the use of the model outside
that range is a dangerous practice."); Han-ell, Frank E. Jr., Regression Modeling Strategies, Second Edition,
Springer, 2015, pp. 7-8 ("Many things can go wrong in statistical modeling, including the following . ... The
user of the model relies on predictions obtained by extrapolating to combinations of predictor values well
outside the range of the dataset used to develop the model.")
62
63
64
DX 116, BANA_EDD_MDL-00719115, tab
See table in Appendix H of the Minnucci Report.
Minnucci Report, Appendix H. Mr. Minnucci provides no explanation of how he derived this single recall
percentage for each abandonment rate range, i.e., whether the recall percentage represents the simple average
( or some other statistical measure) of the underlying individual client data.
25
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process masks the underlying variability in the data. For example,

Assuming that Mr. Minnucci has calculated the recall percentage
for this range by taking a simple average of the underlying proprietary customer data,

In such a scenario,
the substantial variation in the underlying data would call into question the reliability of the
relationship between recall percentage and abandonment rate that Mr. Minnucci has derived
and presented. Without the underlying data comprising each of the six abandonment rate
ranges, it is not possible for me to assess the accuracy or reliability of Mr. Minnucci’s
estimates.
49.
In addition to his unsupported estimation of distinct abandoned callers, Mr. Minnucci has not
shown that it is appropriate to assume that the Claims Call Center should have answered 93.9
percent of the calls during the Proposed Class Period, which Mr. Minnucci calculates as 1
minus an “industry average” abandonment rate of 6.1 percent to calculate.66 As I discuss
further in Section V, Mr. Minnucci fails to show that the multi-industry benchmark he has
selected is appropriate to use, given, as noted above, the Claims Call Center was faced with
unprecedented challenges during the Proposed Class Period. I note that Appendix H of the
Minnucci Report shows

67 To the extent that Mr. Minnucci has understated the abandonment rate (or
overstated the call answer rate) that the Claims Call Center could have and should have

65 Minnucci Report, Appendix H.
66 Minnucci Report, Table 10, note 3.
67 Minnucci Report, Appendix H.
■
-
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reasonably achieved during the Proposed Class Period given the specific circumstances, he
would have overstated his estimate of “workload charges avoided.”
C. Mr. Minnucci’s Calculation of BofA’s Avoided Costs of Idle Hours Is Unreliable
50.
Mr. Minnucci’s use of the Erlang-C formula is inappropriate as it relies upon oversimplified
assumptions that are not applicable to the at-issue Claims Call Center.
51.
First, the Erlang-C formula is based on over simplified assumptions that deviate from reality,
namely that all customer contact will follow a “Poisson” call arrival process and are serviced
by a defined number of statistically identical CSRs.68 Due to its limitations, in my
experience, the Erlang-C formula is typically adopted by smaller contact centers with limited
WFM resources because an Erlang-C calculator is freely available online, as Mr. Minnucci
did here.69 In my experience, call centers with more WFM resources typically build a staffing
model taking into account the customer statistics, CSR performance (such as average handle
time), and historical call center performance to better predict future staffing need.70 Such a
staffing model may be used for call centers operating under “normal” day-to-day business
environment, but not in “[…] high traffic environments, a situation where the Erlang-C
model is not applicable.”71

68 Robbins, Thomas R., “Evaluating the Fit of the Erlang A Model in High Traffic Call Centers,” IEEE, 2016,
available at https://ieeexplore.ieee.org/document/7822226, at p. 1791.
69 I understand Mr. Minnucci’s calculations were done with the cc-Modeler Lite calculator cited in his report and
available at https://www.kooltoolz.com/lite.htm. Also, see, e.g., “Erlang Calculator,” CCmath B.V., available at
https://appsource.microsoft.com/en-gb/product/office/wa200002158?tab=overview; “Erlang Calculator - for
Call Centre Staffing (Online Version 5.0),” Callcentretools, available at
https://www.callcentretools.com/tools/erlang-calculator/.
70 “How business intelligence can revolutionize contact center performance,” CX Network, December 20, 2024,
available at https://www.cxnetwork.com/contact-center/articles/business-intelligence-contact-center.
71 Robbins, Thomas R., “Evaluating the Fit of the Erlang A Model in High Traffic Call Centers,” IEEE, 2016,
available at https://ieeexplore.ieee.org/document/7822226, at p. 1790.
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52.
Second, academic research has found that Erlang-C based WFM tends to overstaff the call
center, indicating that Mr. Minnucci’s use of the Erlang-C formula to estimate allegedly
avoided CSR hour costs would likely overstate damages.72
53.
Third, the Erlang-C formula assumes independent and random call arrivals,73 making it
unsuitable to use during unprecedented events or disaster scenarios where call volumes tend
to spike due to the common influencing factors.74

,75
Therefore, it is
inappropriate for Mr. Minnucci to apply the Erlang-C formula in calculating the CSR idle
hours for the Claims Call Center, rendering his calculation of avoided costs of idle hours
unreliable.
54.
In addition, one of the inputs that Mr. Minnucci uses for the Erlang-C formula is an “industry
average” ASA of 75 seconds. As I discuss further in Section V, Mr. Minnucci fails to show
that the multi-industry benchmark he has selected is appropriate to use as a benchmark
against the Claims Call Center. To the extent that Mr. Minnucci has understated the ASA that
the Claims Call Center could have and should have reasonably achieved during the Proposed

72 See, e.g., Robbins, Thomas R., “Evaluating the Performance of the Erlang Models for Call Centers,”
International Journal of Applied Sciences and Technology (2019), available at
https://myweb.ecu.edu/ROBBINST/PDFs/S-12130-TR.pdf.
73 Koole, Ger M., and Siqiao Li, “A Practice-Oriented Overview of Call Center Workforce Planning,” Stochastic
Systems 13, no. 4 (2023): 479-495, available at https://pubsonline.informs.org/doi/10.1287/stsy.2021.0008.
74 See “What Is Erlang, and Why Does It Matter?,” CX Today, November 25, 2022, available at
https://www.cxtoday.com/contact-center/what-is-erlang-and-why-does-it-matter/.
75 Pesce Report, ¶¶ 19, 21.
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Class Period given the specific circumstances, he would have overstated his estimate of “idle
time charges avoided.”
D. Mr. Minnucci’s Calculation Ignores That BofA Did Not Avoid the Entirety of
Additional CSR Costs
55.
Mr. Minnucci’s calculation of BofA’s allegedly avoided workload and idle hour costs fails to
consider that BofA likely did not avoid these costs entirely. As discussed further in Section
VI.A, BofA

. To the extent that a portion of the CSR costs BofA incurred after the Proposed
Class Period was for addressing backlog of claims and Mr. Minnucci has provided no
evidence to the contrary, these costs have been simply delayed, not “avoided” as Mr.
Minnucci claims.76 Mr. Minnucci fails to consider these delayed costs as an offset to his
calculation, which overstates his estimate of workload charges avoided.
V.
MR. MINNUCCI HAS NOT SHOWN THAT HIS “INDUSTRY” BENCHMARK OF
ASA IS APPROPRIATE, RENDERING MR. REGAN’S CALCULATION OF
DAMAGES SUFFERED BY THE PROPOSED CUSTOMER SERVICE CLASS DUE
TO “EXCESS WAIT TIMES” UNRELIABLE
56.
Mr. Minnucci claims that Bank of America subjected its EDD debit cardholders to wait times
“far longer than what is considered acceptable by industry standards.”77 To estimate the
“excess wait times” experienced by members of the proposed Customer Service Class, Mr.
Minnucci compares the Claims Call Center’s
during the

76 To put it differently, consider a but-for world where BofA ramped up the Claims Call Center during the
Proposed Class Period to meet the “industry standard” service level as Mr. Minnucci claimed, and resolved the
cardholders’ inquiries during the Proposed Class Period. In such case, there would be fewer customers recalling
the Claims Call Center after the Proposed Class Period, and the call volume after the Proposed Class Period
would have been lower than the actual. Thus, BofA would have ramped down the staffing after the Proposed
Class Period and incurred a lower CSR cost.
77 Minnucci Report, ¶ 49.
-
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Proposed Class Period with an “industry standard” ASA of 75 seconds (1.25 minutes), based
on a survey of 214 call centers conducted by ContactBabel.78 Mr. Minnucci has not shown
that the “industry standard” ASA he selected appropriately reflects the ASA experienced by
other call centers comparable to Bank of America’s Claims Call Center during the Proposed
Class Period. In addition, Mr. Minnucci fails to consider the fact that during the Proposed
Class Period,

, in light of COVID-19.
57.
Therefore, Mr. Minnucci has not shown that his industry standard ASA can be relied upon to
estimate the “excess wait times” experienced by members of the proposed Customer Service
Class. Consequently Mr. Regan’s calculation of damages for the Proposed Customer Service
Class, which relies on Mr. Minnucci’s calculation of “excess wait times,” is also unreliable.
A. Contrary to Mr. Minnucci’s Claims, There Is No Universal “Industry Standard” for
Call Center Wait Times
58.
Mr. Minnucci claims that “there are not substantial differences between the ASA or
abandonment rate targets set in different industries,” such that “multi-industry call center
performance data is the best source for identifying ASA and abandonment rate benchmarks
applicable to the [Bank of America]’s Claims call center.”79 I disagree.
59.
In my experience, ASA, which measures the average amount of time that a customer waits
before speaking with a CSR, is a common performance metric used to assess call center
performance across different industries. However, the expectations of target ASAs and

78 Minnucci Report, ¶ 52.
79 Minnucci Report, ¶¶ 41-43.
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realized ASAs vary significantly depending on the industry80 and the nature and complexity
of the requests handled.
60.
Generally speaking, banking and financial services call centers operate under stricter security
protocols and regulatory compliance requirements than many other industries. For example,
banks must adhere to stringent fraud detection and identity verification procedures,81 when
handling complex service requests such as transaction disputes and loan inquiries, all of
which would demand longer call handle times. Even Mr. Minnucci himself acknowledges
that the ASA in the financial industry in 2020 is higher than his industry standard.82 Yet,
without any explanation, Mr. Minnucci chooses to use an ASA benchmark derived from call
centers that serve a wide range of industries that are not comparable to BofA.
61.
Within the financial industry, the expectations of target ASAs and realized ASAs can also
vary depending on the nature and complexity of the requests handled. For example, in my
experience, wait times can be very different for banks’ call centers that handle general
inquiries about account balance and certain transactions and those that handle more complex
requests such as unauthorized transactions and account security.

80 For example, in my experience, call centers for a bank typically prioritize CSAT (Customer Satisfaction) over
call times, while call centers serving the hospitality industry prioritize minimizing call length to reduce wait
times.
81 For example, in 2016, the Bureau of Consumer Financial Protection (CFPB) issued its official guidance on
banks’ (and nonbanks’) reliance on third-party service providers, clarifying its expectation for “banks and
nonbanks to have an effective process for managing the risks of service provider relationships” and recognizing
that risk management may “vary depending upon the service being performed […] and the performance of the
service provider in carrying out its activities in compliance with Federal consumer financial laws and
regulations.” These expectations for banks include “[e]stablishing internal controls and on-going monitoring” to
ensure provider’s compliance, as well as “appropriate and enforceable consequences” for violation of
compliance. See “Compliance Bulletin and Policy Guidance; 2016-02, Service Providers,” Bureau of Consumer
Financial Protection, October 31, 2016, available at
https://files.consumerfinance.gov/f/documents/102016_cfpb_OfficialGuidanceServiceProviderBulletin.pdf.
82 Minnucci Report, ¶ 43. Mr. Minnucci notes that the average ASA across 29 Finance call centers from
ContactBabel was 145 seconds, longer than his “industry standard” of 75 seconds.
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62.
fumy view, there is no standard ASA applicable to all call centers. This is especially true in
2020 after the outbreak of the global COVID-19 pandemic, which had different effects on
call centers depending on the industry served and requests handled. For example, in my
experience, call volumes in the hospitality and tr·avel industry, which accounts for 11 of the
respondents in the ContactBabel survey, 83 plummeted as tr·avel came to a halt at the onset of
the pandemic.
63.
fu contr·ast, Bank of America
83
84
85
mged. 84 As discussed by
Ms. Pesce, the number of new EDD prepaid debit card accounts issued increased from
-
in Febma1y 2020, to-
in April 2020,
_85 fu
addition,
start of the Proposed Class Period and at the staii of the Proposed
Class Period. As discussed by Ms. Pesce,
DX 119, The 2021 US Contact Decision-Makers' Guide, 13th Edition, ContactBabel. In addition to hospitality
and travel, entertainment and home services were among industries experiencing a decline in call volumes. See,
e.g., "COVID-19's Impact on Customer Service Volumes, " HelpScout, September 10, 2024, available at
https://www.helpscout.com/blog/suppo1t-volumes-covid/.
DX 120, BANA_EDD_MDL-00884198. Aroun t s trme, news
out ets a o repo1te t at "t e c a enges for [bank] call centers have been magnified by increased call volume,
increased call complexity, high stress of both employees and customers and a huge shift to work at home
representatives." See "Bank call centers feeling pressure ofCOVID-19," ATM Marketplace, April 28, 2020,
available at https :/ /www.atmmarketplace.com/articles/bank-call-centers-feeling-pressure-of-covid-19/. In
addition to financial services, airlines and retailers were among industries also experiencing long wait times.
See, e.g., "Customer Calls to Companies Rise Amid Coronavims, but Operators Aren't Standing By," Wall
Street Journal, March 29, 2020, available at https://v.rww.wsj.com/articles/calls-to-companies-rise-amid-
coronavirus-but-operators-arent-standing-by-11585483200.
Pesce Report, ,r 37.
32
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87 Mr. Minnucci has
not considered these unique circumstances that BofA's Claims Call Center was faced with
during the Proposed Class Period. Mr. Minnucci provides no evidence, and I have no reason
to believe, that any of the call centers surveyed by ContactBabel experienced such a
significant and extended increase in call volume over such a sho1t period in time. As a result,
attempting to apply a universal "industiy standard" of wait times, as Mr. Minnucci has done
here, is inappropriate.
B. Mr. Minnucci Fails to Consider that BofA Was Exempt from SLAs Related to Wait
Times During the Proposed Class Period
64.
Further, in my experience, the expected service levels and perfonnance of a specific call
center are typically defined in its conti·actual agreements. These contracts typically outline
service level agreements ("SLAs"), including wait times and abandonment thresholds, that
are set based on the unique needs of the client, the nature of the services provided, and the
standards in that industiy in general. 88 Thus, when evaluating the perfo1mance of a call
center including its ASA, it is impo1tant to consider the relevant SLAs, as they appropriately
account for key factors such as complexity of inquiries, regulato1y requirements, and client
86
Pesce Report, ,r 43.
87
Cronan Repo1t , ,r 43.
88
See, e.g., Baron, Opher, and Joseph Milner, "Staffing to Maximize Profit for Call Centers with Altemate
Service-Level Agreements," Operations Research 57, no. 3 (2009): 685-700, at p. 685 ("Firms sign service-
level agreements (SLAs) with outsourced call centers to ensure quality in the handling of their customers'
calls.").
33
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priorities specific to the industry in which this particular call center operates and unique to
this call center.89
65.
In 2020, the impact of COVID-19 necessitated companies across industries to re-evaluate
and adjust operations due to rapidly changing customer demand and workforce disruption.90
These adjustments included revisions to SLAs, to “permit non-performance without incurring
a penalty” due to challenges brought about by the pandemic.91 Therefore, any assessment of
the Claims Call Center’s performance during the Proposed Class Period must take into
account the specific SLA targets, or the lack thereof, as set forth in its agreement with the CA
EDD at that time, which Mr. Minnucci fails to do.
66.
On August 24, 2020, Bank of America entered into an amendment with CA EDD to
temporarily modify the SLAs, obligations, and reporting requirements in light of the COVID-
19 pandemic.92 Pursuant to this amendment, Bank of America would be excused from any
failure to meet the above-mentioned SLAs for customer services (including the SLA that 70

89 Baron, Opher, and Joseph Milner, “Staffing to Maximize Profit for Call Centers with Alternate Service-Level
Agreements,” Operations Research 57, no. 3 (2009): 685-700, at p. 685 (“Within these agreements are terms
that describe services to be provided, such as the hours of operation and the types of facilities; and terms that
describe the service level, such as the average actual handling time (the service time), the acceptable
abandonment rate, and acceptable customer delay times. Although such SLAs are common in industry, their
terms and the extent of their specifications vary.”). Emphasis added.
90 See, e.g., “Hot Topic: Coronavirus Potential impacts on the accounting for arrangements with customers,”
KPMG, March 25, 2020, available at https://kpmg.com/kpmg-us/content/dam/kpmg/frv/pdf/2020/hot-topic-
coronavirus-revenue.pdf.
91 “Hot Topic: Coronavirus Potential impacts on the accounting for arrangements with customers,” KPMG, March
25, 2020, available at https://kpmg.com/kpmg-us/content/dam/kpmg/frv/pdf/2020/hot-topic-coronavirus-
revenue.pdf (“The current disruption to business and the workforce may cause companies to be unable to meet
the service levels they promised to their customers. […] Companies should consult legal counsel to determine
whether force majeure clauses in a customer or subcontractor contract would permit non-performance without
incurring a penalty based on the specific facts and circumstances.”).
92 BANA_EDD_MDL-00014091-095, at 091.
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percent of the calls must be answered within 30 seconds “30/70 SLA”93), “if such failure
occurs despite the Bank’s use of efforts that are commercially reasonable in the context of
the COVID-19 pandemic.”94 This amendment was effective from August 24, 2020 through
June 30, 2021,95 which included the entirety of the Proposed Class Period.
67.
In other words, during the Proposed Class Period, given the disruptions caused by COVID-
19, CA EDD acknowledged that it was unreasonable to require BofA to adhere to the 30/70
SLA they initially agreed upon, or any other fixed, alternative SLA requirement. The
amendment provided BofA discretion to use “commercially reasonable” efforts to manage
the Claims Call Center’s performance and flexibility to react dynamically to the
unpredictable ups and downs in call volume. In my experience, such amendments are rare
and would only be agreed to by a client in dire times. The fact that CA EDD—an agency
responsible for providing critical unemployment benefits—agreed to this amendment
underscores the unprecedented challenges and call volume spikes the Claims Call Center
faced during the Proposed Class Period. Under these extraordinary circumstances, it is
inappropriate for Mr. Minnucci to assess the Claims Call Center’s performance using a
“universal benchmark” that does not account for the specific challenges experienced by the
Claims Call Center as a result of the pandemic. In other words, even setting aside the
important differences in industry, nature of calls handled, and varying impact from COVID-
19 which Mr. Minnucci’s “industry average” fails to properly account for, in my opinion, the
mere fact that

93 BANA_EDD_MDL-00014091-095, at 091, 093.
94 BANA_EDD_MDL-00014091-095, at 091.
95 BANA_EDD_MDL-00014091-095, at 091.
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indicates that a “universal
benchmark” is not applicable to the Claims Call Center during the Proposed Class Period.
68.
For the reasons discussed above, the “excess wait times” that Mr. Minnucci calculates based
on an inappropriate industry standard ASA are unreliable. Because of the flaws in Mr.
Minnucci’s approach, Mr. Regan’s calculation of damages allegedly suffered by the
Proposed Customer Service Class due to these “excess wait times” is also unreliable.
69.
In addition, I note that Mr. Regan does not provide a methodology to calculate actual
damages, if any, to individual class members using their actual wait times. Rather, Mr. Regan
relies on Mr. Minnucci’s report and intends to use the average ASA of Bank of America’s
Claims Call Center over the entire Proposed Class Period and assumes that each individual
class member’s experience and alleged harm was the same.96 Based on my decades of
experience leading contact center metrics compliance programs and teams, it is inappropriate
because it does not represent each individual member’s personal experience.
VI.
MR. MINNUCCI FAILS TO CONSIDER THAT BOFA TOOK REASONABLE
STEPS TO INCREASING STAFFING DURING AND AFTER THE PROPOSED
CLASS PERIOD
70.
As discussed above, Mr. Minnucci has not shown that it is reasonable to assume that BofA
could have and should have accurately predicted the increase in call volumes or AHT during
the Proposed Class Period, yet he claims that BofA “deliberately” understaffed the Claims
Call Center, “causing its Claims call center and its Fraud call center to perform at levels far
below industry standards for sustained periods of time.”97 I understand assessing the

96 Regan Report, ¶¶ 91-93.
97 Minnucci Report, ¶¶ 82. See also Minnucci Report, ¶¶ 15 and 69.
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Defendants’ state of mind is not an appropriate area for expert analysis and opinion, and I am
not offering such an analysis or opinion. Rather, my analysis is intended to provide
information to assist the fact-finder in assessing whether BofA deliberately chose to
understaff. While BofA of course chose its target staffing levels, simply observing with the
benefit of hindsight that the Claims Call Center’s performance would have been better with
more staff does not mean BofA intentionally chose the staffing levels to impose long wait
times on customers. Indeed, as I explain in detail below, based on my experience and my
review of the evidence, BofA quickly adjusted its staffing in response to new information in
real time and its actions were consistent with industry standards to provide reasonable
customer service.
A. After Experiencing Unanticipated Increase in Call Volume, BofA Quickly Adjusted
to New Information in Real Time
71.
As I discuss in Section IV.A.1,

After observing the surge, BofA

72.
Consistent with Mr. Golden’s testimony,98

shown in Figure 6,

This is in line with the time that
BofA
, which Mr. Minnucci acknowledges, and

98 BofA was “
Golden Deposition, pp. 82:5-16 and 85:2-18.
-
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also consistent with my experience under n01mal circumstances. 99 This indicates that BofA
adjusted quickly to new info1mation in real time and sta1ted the hiring process at the sta1t of
the Proposed Class Period.
73.
One of the reasons that the Claims Call Center's FTEs fluctuated earlier during the Proposed
Class Period is that BofA
. 101 A late 2020 update outlined BofA's approach,
99
Golden Deposition, at p. 69:5-20.
100 Minnucci Report, Appendix F; DX 116, BANA_EDD _MDL-00719115, tab'
101 For example,
See
Minnucci Report, Appendix G.
38
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noting that the bank was

.”102

103
74.
BofA’s

is reasonable and aligns with standard industry practices. Based on my experience,
newer CSRs typically remain in frontline roles where they directly interact with customers
and handle more straight forward inquiries, while more experienced CSRs transition to roles
in higher-tier escalation call centers or back-office functions, such as the Claims Processing
Center, to handle more complex inquiries or claim resolutions. Thus, it is reasonable, from a
strategic perspective, for BofA

.
75.
Further, around this time period, BofA

104

102 BANA_EDD_MDL-00494863-865, at 863. See also, BANA_EDD_MDL-00886305-309, at 306-307.
103 BANA_EDD_MDL-00494863-865, at 863. See also, BANA_EDD_MDL-00886305-309.
104 BANA_EDD_MDL-00060129-143, at 132.
-
-
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105
_
_ 106
76.
Despite these challenges, BofA
77.
•
•
112
105 BANA_EDD_MDL-00886356-358, at 357.
106 BANA_EDD_MDL-00498505-512, at 505 ('
107
108 Paul Simpson (who was brought in to run the call centers for BofA's unemployment benefits programs in 2020)
and William Golden led this initiative, which sought to "[ c ]onsolidate Call Service Center, Fraud Tier 1 and
Claims Servicing under GBAM Ops to holistically manage the three functions." Deposition of Paul Simpson,
February 21, 2025 ("Simpson Deposition"), at p. 9:12-20; BANA_EDD_MDL-00153928-930;
BANA_EDD_MDL-00153872-874; BANA_EDD_MDL-00389951-956, at 955.
109 BANA_EDD_MDL-00103857-865; BANA_EDD_MDL-00105042-046; BANA_EDD_MDL-00389951-956.
110 DX 116, BANA_EDD_MDL-00719115, tab "Weekly Sllllllllary".
111 DX 116, BANA_EDD_MDL-00719115, tab "Weekly SUlllllla1y".
112 91,786 calls abandoned / 115,168 calls offered = 79.7% in the week of October 25; 6,068 calls abandoned/
78,164 calls offered = 7.8% in the week of December 13. DX 116, BANA_EDD_MDL-00719115, tab "Weekly
Sllllllllary".
40
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B. BofA's Real-Time Staffing Approach to Real Time Call Demand is Consistent with
Industry Practice
78.
Mr. Minnucci criticizes BofA for following
113 I disagree. My review of the documents
indicate that BofA and its vendo
114
. 115 After obse1ving this unprecedented increase in the Claims Call
Center's call volume, BofA's decision to adopt a real-time response approach aligns with
industry nonns in my experience. 116
79.
Further, Mr. Minnucci asserts, with the benefit of hindsight, that the'
_ 111 As
a preliminaiy matter, Mr. Minnucci ignores that the
113 Minnucci Report, ,r 60.
114
115
116 Insurance contact centers, for example, "find it challenging to predict the onslaught of needs dw-ing these times.
Even when [we] know a disaster is coming, preparing for a surge can still be difficult." "How to Handle Contact
Center Staffing During a Natural Disaster," ShyftOff, November 8, 2024, available at
https://www.shyftoff.com/blog/contact-center-staffing-during-a-natural-disaster; "Optimising Call Centre
Staffing Levels to Manage Call Spikes," Answer4U, December 11, 2024, available at https://wv.rw.answer-
4u.com/blog/manage-call-spikes ("[e]ven with accurate forecasting, unforeseen events can cause sudden surges
in call volume"),
118 Deposition of Paiz Arnuad, January 29, 2025, at pp. 209: 17-210:8 and Exhibit 322.
41
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118
. 119 Fmt her, in my experience, it is extremely difficult
to accurately predict the change in call volume with any degree of ce1tainty, paiticularly in
the absence of prior precedent on which BofA could rely. For example, if most of the
-
. Mr. Minnucci has not shown how BofA could have
Even if one were to assume that an initial
increase in the Claims Call Center's call volume could be anticipated, it is extremely difficult
to predict the duration and magnitude of such an increase. Based on my experience, it was
reasonable for BofA not to make any drastic staffing changes immediately, and instead,
choose to closely monitor the situation and make real-time adjustments based on actual call
patterns.
118 Deposition of Paiz Alunad, January 29, 2025, at pp. 209: 17-210:8 and Exhibit 322.
119 In addition, I understand that Mr. Cronan and Ms. Pesce both opine that not acting quickly to mitigate the fraud
could have exposed the BofA to significant risks. Cronan Report, ,r 49 ("based on the rapidly unfolding
circumstances and the emerging scale of the unprecedented fraud, not acting to 1nitigate the fraud could have
resulted in OCC action under safe and soundness re uirements as discussed elsewhere in this re ort" ; Pesce
56
42
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_120A~
I
I
Mr. Minnucci claimed BofA should
have added dming the first seven weeks of the Proposed Class Period.
120 That is, I calculate the additional FTEs BofA would have forecasted for the first seven weeks of the Proposed
Class Period (from the week of September 13, 2020 through the week of October 25, 2020) seven weeks ahead
of time (from the week of July 26, 2020 through the week of September 6, 2020, which is the week prior to the
start of the Proposed Class Period).
121 For the pwpose of this analysis, I assume that BofA would have planned for the Claims Call Center's staffing
level seven weeks in advance based on (1) the number of calls offered it observed at the time of planning,
multiplied by 93.9 percent (1 minus Mr. Minnucci's "industry standard" abandonment rate of 6.1 percent) and
(2) the AHT it observed at the time of planning. I did not use Mr. Minnucci' s estimation of distinct calls to
reduce the number of calls expected to answer, which is conservative.
My calculation here is intended solely to illustrate magnitude of the call volume spike in the Claims Call Center
and the resulting staffing challenges. It should not be constmed as an opinion on the appropriate approach to
staffing planning or an opinion that this is what BofA should have done when planning for staffing.
In addition, as I discuss in ,r 35 above, the Claims
•
. .
'
.
e
·audulent activity and its impact on AHT- and Mr. Mmnucc1 has not presente on~the histoncal data ·om
seven weeks prior cannot be used as a reliable basis for any forecast.
43
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VII.
MR. MINNUCCl'S CLAIM ON BOFA'S BROADER SYSTEMIC FAILURE TO
REASONABLY OPERATE ITS PREPAID CALL CENTERS IS UNSUPPORTED
A. Mr. Minnucci's Criticisms Regarding BofA's Failure for Disaster Planning Are at
Odds with Reality
82.
Mr. Minnucci claims that BofA "failed to engage in reasonable planning for its Prepaid call
centers for potential staffing-intensive events like the pandemic." 122 To support his claim,
Mr. Minnucci
123 Mr.
Minnucci claims that it
124 Mr. Minnucci further opines that that "[t]his lack of preparation from
a major U.S. bank providing a service of immense impo1iance to its cardholders is
substantially out of step with industiy noims." 125 However, as I discuss below, Mr.
Minnucci's claims are at odds with the industiy -wide operational challenges the call centers
experienced due to COVID-19. 126 In addition, Mr. Minnucci fails to acknowledge that BofA
122 Minnucci Report, ,r 83.
123 Minnucci Report, ,r,r 83-88.
124 Minnucci Report, ,r,r 88-90. Further, Mr. Minnucci asserts that the "disconnected" calls were in violation of
BofA's contractual promise that '"no call' would be 'transferred to voicemail or automatically disconnected
from the ueue."' Minnucci Re ort, 89. I note that accordin to an email dated A ril 16, 2020, •-
See PX 140,
BANA_EDD_MDL-00021102-136, at 102.
125 Minnucci Report, ,r 90.
126 "5 Insights of Covid-19 in the Contact Center," Pindrop, April 30, 2020 (updated on Januaiy 17, 2025),
available at https://wv.rw.pindrop.comhuticle/insights-covid-nineteen-in-the-contact-center ("As a critical
customer interface, contact centers have felt the effects directly, regardless of geography and industry. The
global pandemic hit this critical function, and many were left scrambling to keep their operations mnning,
customer service levels up, and their customer data safe").
44
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quickly responded to the outbreak of COVID-19, adding CSRs to its call centers and
providing the necessary technology for its employees to work effectively in a remote
environment.
83.
After the outbreak of the COVID-19 pandemic, call centers’ operations faced severe
disruptions due to a sudden surge in call volumes, and workforce shortages. Social distancing
mandates forced approximately 90% of global CSRs to work remotely.127 This mass
transition to remote work complicated workforce management and operational oversight.128
Many CSRs, working from home for the first time, lacked basic infrastructure such as stable
and low latency voice connections or peer support, making it more difficult to assist
customers efficiently.129 Meanwhile, the pandemic-induced shift to remote work also
exacerbated staffing shortages, with many call centers experiencing high levels of
absenteeism, attrition, and workforce shrinkage.130
84.
Unlike seasonal fluctuations, which customer service teams could anticipate and prepare for,
the COVID-19 pandemic brought rapid, large-scale changes with little to no warning.131 In
addition, before the COVID-19 pandemic, while call center had previously prepared

127 “Impact of Covid-19 on Contact Centers and Measures Taken,” GEP, October 29, 2020, available at
https://www.gep.com/blog/mind/impact-of-covid-19-on-contact-centers-and-measures-taken.
128 “5 Insights of Covid-19 in the Contact Center,” Pindrop, April 30, 2020 (updated on January 17, 2025),
available at https://www.pindrop.com/article/insights-covid-nineteen-in-the-contact-center.
129 “Supporting Customer Service Through the Coronavirus Crisis,” Harvard Business Review, April 8, 2020,
available at https://hbr.org/2020/04/supporting-customer-service-through-the-coronavirus-crisis; “How Remote
Work Has Changed The Call Center,” Forbes, May 22, 2023, available at
https://www.forbes.com/councils/forbestechcouncil/2023/05/22/how-remote-work-has-changed-the-call-center/.
130 A study from November 2021 found that “[o]ne in three contact center leaders (33%) say high agent turnover is
one of their biggest pain points.” “Why Do Call Centers Have High Turnover (and What Can We Do About
It),” Medallia, February 15, 2022, available at https://www.medallia.com/why-do-call-centers-have-high-
turnover-and-what-can-we-do-about-it/.
131 “COVID-19’s Impact on Customer Service Volumes,” Help Scout, September 10, 2024, available at
https://www.helpscout.com/blog/support-volumes-covid.
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pandemic response plans as part of their overall business continuity programs,132 the focus of
call center disaster planning typically centered around events such as natural disasters (e.g.,
Hurricane Katrina), power or system outages, and labor strikes, which are all localized and
short term. When such disastrous events occur, assistance can be sought from unaffected
regions (e.g., call centers located in a different region). COVID-19, on the contrary, created a
global crisis in which virtually every region and business was affected, which significantly
limited the availability of external assistance that organizations can typically rely on during
localized disruptions.133 As a result, in my experience, most of the call centers—even the
ones with the most sophisticated and comprehensive disaster planning ahead of time—were
disrupted in 2020 after the outbreak of the COVID-19 pandemic. Mr. Minnucci’s ideal world
in which “reasonable planning” could have prevented these challenges is detached from
reality.
85.
Further, my review of the internal documents indicate that BofA acted reasonably and
commendably in responding to COVID-related challenges in early 2020, increasing the
number of vendor CSRs supporting the three call centers for prepaid cards (Main, Claims,
and Fraud Call Centers) from

132 Following the outbreak of H1N1 in 2009–2010, contact centers were often contractually required to prepare,
maintain, test, and present their pandemic response plans on at least an annual basis.
133 As the COVID-19 pandemic unfolded, it became clear that both businesses and even well-resourced
governments found their localized, business-unit-focused pandemic plans—originally designed around H1N1
scenarios—were not fit for purpose. For example, the Council on Foreign Relations published a task force
report titled “Improving Pandemic Preparedness: Lessons From COVID-19,” which noted that the U.S. was
unprepared for COVID-19, “having failed to integrate and implement the lessons of earlier epidemics and
multiple training exercises, to designate a strong focal point for interagency coordination, to allocate resources
commensurate with the magnitude of the threat […].” See “Improving Pandemic Preparedness: Lessons From
COVID-19,” Council on Foreign Relations (2020), available at https://www.cfr.org/task-force-
report/improving-pandemic-preparedness/findings.
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-
134
•
. 135 BofA.
136 BofA.'s actions are consistent
with best practices of COVID-19 response in call centers supporting financial institutions in
my expenence.
B. Mr. Minnucci's Criticism Regarding BofA's Failure to Adopt Virtual Queuing and
Estimated Wait Time Notifications Is Unfounded
86.
Mr. Minnucci criticizes BofA. for failing to adopt alternative technology such as Virtual
Queuing (which allows callers to hold their place in line and receive a callback instead of
waiting on hold indefinitely) and Estimated Wait Time Notifications (which provides callers
with an estimated time until their call is answered). 137 In my experience, any technology
deployed to facilitate the customer experience is typically agreed upon by the pa1ties in
advance. Mr. Minnucci has not shown-nor have I seen any evidence-that the use of either
134 BANA EDD MDL-00494863-865.
-
-
135 BANA_EDD_MDL-00265136-143, at 137, 138.
136
137 Minnucci Report, ,r,r 79-81.
47
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Virtual Queuing or Estimated Wait Time Notifications was mandated by CA EDD or

.138 In addition, Mr. Minnucci fails to consider that for BofA to adopt such
technologies uniformly across all of its vendors’ call centers, it would require significant
time, coordination, and infrastructure changes, such that it would not be an effective solution
to quickly address the call volume surge caused by factors such as the COVID-19 pandemic
or fraudsters implementing “double dipping” schemes.
87.
In my experience, the decision to use certain technology or not at a specific call center is
typically based upon a number of factors, including the nature and type of calls handled,
whether consistently high volumes and/or wait times are anticipated, and most importantly
the desired customer experience. In my experience, for organizations that rely on multiple
outsourced contact center vendors—as is the case with BofA—providing a uniform customer
experience is often the most important factor when making technology decisions.
Specifically, in my experience, BofA requires all of the contact center vendors to deliver a
consistent experience across all customer interactions, from the initial greeting and caller
verification, through the call flow, questions asked, tools used, and data collected, to the
conclusion of the call, including any post-call surveys.139
88.
In my experience, to maintain a uniform customer experience, the implementation of Virtual
Queuing and Estimated Wait Time Notifications technologies would take considerable
coordination, planning, and infrastructure changes. Adopting these technologies would
require not only a technology upgrade (e.g., to allow for outbound callbacks to customers)

138 PX 115, BANA_EDD_MDL-00002286-851.
139 This is to ensure that callers must never perceive that they are speaking with anyone other than BofA.
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and integration with existing telephony systems across all call centers at multiple vendors,
but also extensive testing and alignment in revising telephony configuration and operational
workflows across all vendors. Thus, to ensure that the technologies are implemented in a
uniform manner and cause minimal disruption to customer experience, the deployment would
not be a trivial undertaking. Given these complexities, it would not have been feasible to
implement such technologies in a reasonably short timeframe—such as a month or two—
especially during periods of heightened demands.140 As such, contrary to Mr. Minnucci’s
claims, adopting the Virtual Queuing and Estimated Wait Time Notifications technologies
would not be an effective solution to quickly address the call volume surge caused by factors
such as the COVID-19 pandemic or fraudsters implementing “double dipping” schemes.

.141 Further, as I discussed above, it is extremely difficult to
accurately predict the change in call volume resulting from the Claims Fraud Filter or spikes
in call volume attributed to attempted fraud or criminal activity with any degree of certainty,
in the absence of prior precedent on which BofA could rely. Therefore, it was reasonable for
BofA not to devote significant resources to implement such technologies ahead of time.

140 In my experience, implementing technologies like Virtual Queuing or Estimated Wait Time Notifications would
require weeks of planning, followed by additional weeks of implementation and testing at each individual call
center, to ensure that they are seamlessly integrated with the existing systems and work uniformly and
effectively across all vendors.
141 Deposition of Faiz Ahmad, January 29, 2025, at pp. 209:17-210:8 and Exhibit 322.
I
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C. Mr. Minnucci’s Claims Regarding BofA’s “Lax Security Protocols in the Transition
to Work-from-Home” Are False
1. It Was Reasonable for BofA to

89.
Mr. Minnucci claims that BofA failed to comply with Payment Card Industry Data Security
Standard (PCI DSS) because it

.142 Mr. Minnucci’s claims are misleading and incorrect.
90.
Mr. Minnucci has conflated the responsibilities of different entities in the banking and
payment processing ecosystem, such as banks and card brands (Visa/Mastercard, acting as
issuers/acquirers) versus contact center vendors (service providers/processors) and merchants
(handling payment transactions). The PCI DSS is an industry standard enforced by Visa and
Mastercard through their contracts with banks, which serve as the issuers.143 PCI DSS
requires employee screening such as previous employment history, criminal record, credit
history, and reference checks.144 However, banks have a separate, regulated obligation to
comply with the Gramm-Leach-Bliley Act (GLBA).145 In 2021, the FTC significantly
strengthened the GLBA’s information security requirements under the Safeguards Rule,

142 Minnucci Report, ¶ 100.
143 “PCI DSS explained: Requirements, fines, and steps to compliance,” CSO, April 3, 2024, available at
https://www.csoonline.com/article/569591/pci-dss-explained-requirements-fines-and-steps-to-compliance.html.
144 “Requirements and Security Assessment Procedures,” Payment Card Industry (PCI) Data Security Standard,
Version 3.2.1., May 2018, at p. 110, available at
https://www.pcisecuritystandards.org/document_library/?category=pcidss.
145 “Gramm-Leach-Bliley Act,” Federal Trade Commission, available at https://www.ftc.gov/business-
guidance/privacy-security/gramm-leach-bliley-act.
-
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which banks are legally required to meet.146 Consequently, banks adhere to both regulatory
mandates and industry standards, demonstrating compliance as required by the respective
governing bodies—such as the card brands in this instance.147
91.
In the call center industry, compliance with PCI DSS is contractual rather than regulatory.148
Third-party call centers are often under contractual obligations to provide evidence to their
client banks that they maintain PCI compliance through a structured information security and
governance program.149 This compliance is typically attested to by a responsible executive
within the contact center.150 In the case of BofA and the call center vendors (i.e., TTEC and
ACT), the specific security requirements were outlined in their contracts, including
151
Vendors are audited annually to ensure adherence to these requirements across all relevant

146 “FTC Strengthens Security Safeguards for Consumer Financial Information Following Widespread Data
Breaches,” Federal Trade Commission, October 27, 2021, available at https://www.ftc.gov/news-
events/news/press-releases/2021/10/ftc-strengthens-security-safeguards-consumer-financial-information-
following-widespread-data.
147 See, e.g., “Visa Issuer and Acquirer Payment Card Industry Data Security Standard Compliance,” Visa,
February 10, 2009, available at https://usa.visa.com/dam/VCOM/global/support-legal/documents/bulletin-
issuer-acquirer-pci-dss.pdf.
148 “What Are the PCI DSS Third-Party Service Provider Management Requirements,” PCI DSS Guide, July 13,
2021, available at https://pcidssguide.com/what-are-the-pci-dss-third-party-service-provider-management-
requirements/ (“The service provider’s acknowledgment of liability for card data will be a form of liability
acceptance offered to you by the third party. It should be noted that PCI DSS [Attestation of Compliance] is not
a legal contract between you and a third party and has nothing to do with the acceptance of liability.”).
149 See, e.g., “What Are the PCI DSS Third-Party Service Provider Management Requirements,” PCI DSS Guide,
July 13, 2021, available at https://pcidssguide.com/what-are-the-pci-dss-third-party-service-provider-
management-requirements/.
150 “What Are the PCI DSS Third-Party Service Provider Management Requirements,” PCI DSS Guide, July 13,
2021, available at https://pcidssguide.com/what-are-the-pci-dss-third-party-service-provider-management-
requirements/ (“A PCI DSS compliant third-party service provider that has passed its PCI DSS assessment will
have its Attestation of Compliance (AoC).”).
151 “What Are the PCI DSS Third-Party Service Provider Management Requirements,” PCI DSS Guide, July 13,
2021, available at https://pcidssguide.com/what-are-the-pci-dss-third-party-service-provider-management-
requirements/. See also DX 117, BANA_EDD_MDL-00012816-874, at 834; DX 118, BANA_EDD_MDL-
00013111-163, at 128.
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service areas. 152
. 153 It was reasonable for BofA to
2. It Was Not Unreasonable for Bo/A to
92.
Compliance gaps that arise due to operational or technological changes are expected to be
remediated within 90 days of discove1y to maintain compliance.154 In my experience,
93.
tempora1y relaxations, such as a
, are often adopted as an adaptive response to an unprecedented event and were
intended to be corrected moving fo1ward.
156
152 "What Are the PCI DSS Third-Party Service Provider Management Requirements," PCI DSS Guide, July 13,
2021, available at https ://pcidssguide .com/what-are-the-pci-dss-third-party-service-provider-management-
requirements/. See also DX 117, BANA_EDD _MDL-00012816-874, at 840; DX 118, BANA_EDD _MDL-
00013111-163, at 135.
153 DX 117, BANA_EDD_MDL-00012816-874, at 837, 866; DX 118, BANA_EDD_MDL-00013111-163, at 132,
161.
154 Further, in my experience, since PCI DSS compliance assessments are conducted annually as "point-in-time"
audits, PCI Qualified Security Assessors (QSA) examine suppo1ting evidence that is not older than 90 days
prior to the audit to confinn compliance.
155 BANA EDD MDL-00515252-254.
-
-
156
52
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158 Based on my experience, it was not unreasonable
for Bo
given the circumstances at the
time. 159
160
157
158
289:17-20.
159
improved the call center service. In fact,
would have slowed down the ramping up process
160
53
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3. The Bank's WFH Requirements Were Consistent With Industry Practice
94.
Mr. Minnucci asse1ts that BofA
Minnucci fmi her asse1ts that '
95.
First, Mr. Minnucci's statement that
161
Internal documentation confums
BANA EDD MDL-00103022-0 3, a
047.
162 Minnucci Report, ,r 105.
163
164 Minnucci Report, ,r 105.
162 Specifically, Mr. Minnucci criticizes BofA
163 Mr.
164
. 165 Mr. Golden testified that the
165 DX 117, BANA_EDD_MDL-00012816-874, at 834, 837, 840, 866; DX 118, BANA EDD MDL-00013111-
163, at 128, 132, 135, 161.
. See BANA EDD MDL-00370698-
-
-
700, at 699; BANA_EDD _MDL-00476903-905, at 904; BANA_EDD _MDL-00476906-908;
BANA EDD MDL-00697112-113;BANA EDD MDL-00697114-118.
54
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167
96.
168
168
55
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The PCI Security
Avaya is a VOiP and VTI solution "to enhance and simplify communications and collaboration." See "Avaya
OneCloud™ Collllllunications and Collaboration Solutions for Advanced Call Center Technologies (ACT), an
Outsourcing Provider, Improve Experiences while Significantly Reducing Costs," Avaya, April 11, 2022,
available at https://www.avaya.com/en/about-avaya/newsroom/pr-us-22041 l/; "Professional Services Case
Study in Focus: Avaya and ACT," UC Today, August 12, 2022, available at https://www.uctoday.com/unified-
collllllunications/professional-services-case-study-in-focus-avaya-and-act/.
Visa DPS is a platfo1m suppo1ting "payment processing needs, from speed to authorization and fraud
rotection." See "Visa DPS," Visa, available at h
s://usa.visa.com/sites/visa-d s.html
56
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Standards Council also recognized the unprecedented impact of the COVID-19 pandemic on
remote work controls and issued guidance accordingly.171
97.

.172

.173

175
176
.177

171 See, e.g., “Guidance On Working Remotely,” PCI SSC, available at
https://www.pcisecuritystandards.org/covid19/guidance-on-working-remotely/; “Protecting Payments While
Working Remotely,” PCI SSC, available at https://blog.pcisecuritystandards.org/protecting-payments-while-
working-remotely.
172 BANA_EDD_MDL-00287970-973.
173 BANA_EDD_MDL-00871377-400.
174 BANA_EDD_MDL-00370698-700.
175 BANA_EDD_MDL-00268474-489, at 480 (noting that “Global Information Security has reviewed at enterprise
level to address any incremental risks [associated with USB adapters] and also to ensure the technology will
work.”).
176 BANA_EDD_MDL-00268474-489, at 482 (noting that privacy and data protection compliance process during
WFH “was reviewed and approved by Privacy.”).
177 Furthermore, BofA noted that appropriate partners with expertise “have been engaged” to “help identify risks
and mitigation plans” such that “all concerns [have] been addressed.” BANA_EDD_MDL-00268474-489, at
485.
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98.
Highly Confidential - Attorneys' Eyes Only
. 178 At the same
time, compliance with legal employee privacy protections remained essential. Employers
were still required to respect personal rights, meaning they could not monitor home office
environments through cameras or similar means without employee awareness and consent. 179
. 180 In my opinion, BofA's remote work
WFH airnngements for CSRs ai·e consistent with industry best practices.
Executed on this 4th day of April, 2025.
/44
-
By:
Stephen Hindle
179 See, e.g., "Workplace Monitoring: What's Allowed, What's Off Limits?" ADP, February 5, 2024, available at
https://sbshrs.adpinfo.com/blog/workplace-monitoring-whats-allowed-whats-off-limits (The Electronic
Communications Privacy Act (ECP A) "generally restricts the interception and monitoring of oral, wire and
electronic communications, unless certain conditions, such as a legitimate business pwpose and an employee's
consent to monitor, are met.").
180 See, e.g., BANA_EDD_MDL-00376191-201, at 197.
58
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Appendix A
Documents Considered
Legal Documents
1. Bank of America’s Responses and Objections to Plaintiff Yick’s Fifth Set of Interrogatories, In re: Bank of America
California Unemployment Benefits Litigation, No. 3:21-md-02992-LAB-MSB, United States District Court for the
Southern District of California, February 2, 2024.
2. Declaration of Kelly Lorenzen, In re: Bank of America California Unemployment Benefits Litigation , No. 21-md-02992-
LAB-MSB, United States District Court for the Southern District of California - San Diego Division, January 17, 2025.
3. Declaration of William Golden, In re: Bank of America California Unemployment Benefits Litigation , No. 21-md-02992-
LAB-MSB, United States District Court for the Southern District of California - San Diego Division, October 21, 2021.
4. Declaration of William Golden, Jennifer Yick, et al., v. Bank of America, N.A , No. 3:21-cv-00376-VC, United States
District Court for the Northern District of California San Francisco Division, April 20, 2021.
5. Memorandum of Points and Authorities in Support of Motion for Class Certification, In re: Bank of America California
Unemployment Benefits Litigation, No. 3:21-md-02992-GPC-MSB, United States District Court for the Southern
District of California, August 29, 2024.
6. Second Amended Master Consolidated Complaint, In re: Bank of America California Unemployment Benefits
Litigation, No. 3:21-md-02992-GPC-MSB, United States District Court for the Southern District of California, July 16,
2024.
7. Third Amended Master Consolidated Complaint, In re: Bank of America California Unemployment Benefits Litigation,
No. 3:21-md-02992-GPC-MSB, United States District Court for the Southern District of California, January 24, 2025.
Expert Reports
1. Expert Class Certification Report of Greg J. Regan, CPA/CFF, CFE, August 29, 2024.
2. Expert Declaration of Stephen Hindle, October 24, 2024.
3. Expert Rebuttal Report of Jay Minnucci, November 21, 2024.
4. Expert Report of David I. Levine, March 4, 2025.
5. Expert Report of Greg J. Regan, CPA/CFF, CFE, March 4, 2025.
6. Expert Report of Jay Minnucci, August 29, 2024.
7. Expert Report of Jay Minnucci, March 4, 2025.
8. Expert Report of Russell Cronan, March 4, 2025.
9. Expert Report of Teresa A. Pesce, March 4, 2025.
Depositions
1. 30(b)(6) Deposition of William Golden, February 22, 2024, and All Associated Exhibits.
2. Deposition of Faiz A. Ahmad, January 29, 2025, and All Associated Exhibits.
3. Deposition of Jennifer Ehresman, February 19, 2025, and All Associated Exhibits.
4. Deposition of Paul Simpson, February 21, 2025, and All Associated Exhibits.
5. Deposition of Robert A. Chestnut, February 8, 2024, and All Associated Exhibits.
Data Files
1. Exhibit 11 to BANA's Response to Plaintiff's Interrogatories, February 2, 2024.
2. Exhibit 12 to BANA's Response to Plaintiff's Interrogatories, February 2, 2024.
3. Servicing and Fraud Call Metrics 2020-2021.xlsx.
Bates Stamped Documents
1. BANA_EDD_MDL-00001365.
2. BANA_EDD_MDL-00001367.
3. BANA_EDD_MDL-00002286.
4. BANA_EDD_MDL-00008349.
5. BANA_EDD_MDL-00009974.
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Appendix A
Documents Considered
6. BANA_EDD_MDL-00010691.
7. BANA_EDD_MDL-00010783.
8. BANA_EDD_MDL-00012191.
9. BANA_EDD_MDL-00012653.
10. BANA_EDD_MDL-00012671.
11. BANA_EDD_MDL-00012793.
12. BANA_EDD_MDL-00012816.
13. BANA_EDD_MDL-00013074.
14. BANA_EDD_MDL-00013096.
15. BANA_EDD_MDL-00013107.
16. BANA_EDD_MDL-00013111.
17. BANA_EDD_MDL-00014091.
18. BANA_EDD_MDL-00015507.
19. BANA_EDD_MDL-00021174.
20. BANA_EDD_MDL-00052780.
21. BANA_EDD_MDL-00053041.
22. BANA_EDD_MDL-00054100.
23. BANA_EDD_MDL-00054439.
24. BANA_EDD_MDL-00054478.
25. BANA_EDD_MDL-00054515.
26. BANA_EDD_MDL-00060126.
27. BANA_EDD_MDL-00060128.
28. BANA_EDD_MDL-00060129.
29. BANA_EDD_MDL-00060144.
30. BANA_EDD_MDL-00060339.
31. BANA_EDD_MDL-00060395.
32. BANA_EDD_MDL-00060396.
33. BANA_EDD_MDL-00060470.
34. BANA_EDD_MDL-00060669.
35. BANA_EDD_MDL-00060670.
36. BANA_EDD_MDL-00060772.
37. BANA_EDD_MDL-00060774.
38. BANA_EDD_MDL-00060783.
39. BANA_EDD_MDL-00060854.
40. BANA_EDD_MDL-00060855.
41. BANA_EDD_MDL-00060864.
42. BANA_EDD_MDL-00060866.
43. BANA_EDD_MDL-00060881.
44. BANA_EDD_MDL-00060918.
45. BANA_EDD_MDL-00080512.
46. BANA_EDD_MDL_00090040.
47. BANA_EDD_MDL-00090066.
48. BANA_EDD_MDL-00098267.
49. BANA_EDD_MDL-00099615.
50. BANA_EDD_MDL-00099617.
51. BANA_EDD_MDL-00099620.
52. BANA_EDD_MDL-00102458.
53. BANA_EDD_MDL-00103022.
54. BANA_EDD_MDL-00103857.
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Appendix A
Documents Considered
55. BANA_EDD_MDL-00104400.
56. BANA_EDD_MDL-00104402.
57. BANA_EDD_MDL-00104403.
58. BANA_EDD_MDL-00104412.
59. BANA_EDD_MDL-00104414.
60. BANA_EDD_MDL-00104449.
61. BANA_EDD_MDL-00104450.
62. BANA_EDD_MDL-00104468.
63. BANA_EDD_MDL-00104553.
64. BANA_EDD_MDL-00104554.
65. BANA_EDD_MDL-00104685.
66. BANA_EDD_MDL-00104708.
67. BANA_EDD_MDL-00104709.
68. BANA_EDD_MDL-00104784.
69. BANA_EDD_MDL-00104906.
70. BANA_EDD_MDL-00105042.
71. BANA_EDD_MDL-00106044.
72. BANA_EDD_MDL-00106159.
73. BANA_EDD_MDL-00118438.
74. BANA_EDD_MDL-00118444.
75. BANA_EDD_MDL-00140232.
76. BANA_EDD_MDL-00141022.
77. BANA_EDD_MDL-00141407.
78. BANA_EDD_MDL-00141585.
79. BANA_EDD_MDL-00142093.
80. BANA_EDD_MDL-00142331.
81. BANA_EDD_MDL-00142333.
82. BANA_EDD_MDL-00142497.
83. BANA_EDD_MDL-00142764.
84. BANA_EDD_MDL-00142949.
85. BANA_EDD_MDL-00142950.
86. BANA_EDD_MDL-00153666.
87. BANA_EDD_MDL-00153667.
88. BANA_EDD_MDL-00153872.
89. BANA_EDD_MDL-00153928.
90. BANA_EDD_MDL-00154045.
91. BANA_EDD_MDL-00173061.
92. BANA_EDD_MDL-00186897.
93. BANA_EDD_MDL-00201310.
94. BANA_EDD_MDL-00202603.
95. BANA_EDD_MDL-00205638.
96. BANA_EDD_MDL-00224936.
97. BANA_EDD_MDL-00226642.
98. BANA_EDD_MDL-00233640.
99. BANA_EDD_MDL-00233643.
100. BANA_EDD_MDL-00233647.
101. BANA_EDD_MDL-00233648.
102. BANA_EDD_MDL-00233649.
103. BANA_EDD_MDL-00233653.
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Appendix A
Documents Considered
104. BANA_EDD_MDL-00265136.
105. BANA_EDD_MDL-00268474.
106. BANA_EDD_MDL-00287970.
107. BANA_EDD_MDL-00354508.
108. BANA_EDD_MDL-00354749.
109. BANA_EDD_MDL-00356316.
110. BANA_EDD_MDL-00370698.
111. BANA_EDD_MDL-00371301.
112. BANA_EDD_MDL-00371324.
113. BANA_EDD_MDL-00371326.
114. BANA_EDD_MDL-00371328.
115. BANA_EDD_MDL-00371330.
116. BANA_EDD_MDL-00371468.
117. BANA_EDD_MDL-00371469.
118. BANA_EDD_MDL-00371572.
119. BANA_EDD_MDL-00371574.
120. BANA_EDD_MDL-00371576.
121. BANA_EDD_MDL-00371578.
122. BANA_EDD_MDL-00371580.
123. BANA_EDD_MDL-00371788.
124. BANA_EDD_MDL-00371790.
125. BANA_EDD_MDL-00372684.
126. BANA_EDD_MDL-00372686.
127. BANA_EDD_MDL-00372688.
128. BANA_EDD_MDL-00372690.
129. BANA_EDD_MDL-00372692.
130. BANA_EDD_MDL-00372694.
131. BANA_EDD_MDL-00373634.
132. BANA_EDD_MDL-00373654.
133. BANA_EDD_MDL-00373656.
134. BANA_EDD_MDL-00373658.
135. BANA_EDD_MDL-00374118.
136. BANA_EDD_MDL-00374120.
137. BANA_EDD_MDL-00374122.
138. BANA_EDD_MDL-00374124.
139. BANA_EDD_MDL-00376191.
140. BANA_EDD_MDL-00377043.
141. BANA_EDD_MDL-00388873.
142. BANA_EDD_MDL-00389950.
143. BANA_EDD_MDL-00389951.
144. BANA_EDD_MDL-00392014.
145. BANA_EDD_MDL-00407466.
146. BANA_EDD_MDL-00424455.
147. BANA_EDD_MDL-00424457.
148. BANA_EDD_MDL-00424461.
149. BANA_EDD_MDL-00424465.
150. BANA_EDD_MDL-00425815.
151. BANA_EDD_MDL-00425817.
152. BANA_EDD_MDL-00425822.
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Appendix A
Documents Considered
153. BANA_EDD_MDL-00425827.
154. BANA_EDD_MDL-00455953.
155. BANA_EDD_MDL-00468924.
156. BANA_EDD_MDL-00468927.
157. BANA_EDD_MDL-00468933.
158. BANA_EDD_MDL-00476903.
159. BANA_EDD_MDL-00476906.
160. BANA_EDD_MDL-00476998.
161. BANA_EDD_MDL-00489021.
162. BANA_EDD_MDL-00489025.
163. BANA_EDD_MDL-00489026.
164. BANA_EDD_MDL-00489027.
165. BANA_EDD_MDL-00489030.
166. BANA_EDD_MDL-00489031.
167. BANA_EDD_MDL-00489032.
168. BANA_EDD_MDL-00489035.
169. BANA_EDD_MDL-00489036.
170. BANA_EDD_MDL-00489037.
171. BANA_EDD_MDL-00489041.
172. BANA_EDD_MDL-00493780.
173. BANA_EDD_MDL-00494310.
174. BANA_EDD_MDL-00494862.
175. BANA_EDD_MDL-00494863.
176. BANA_EDD_MDL-00494866.
177. BANA_EDD_MDL-00494874.
178. BANA_EDD_MDL-00495466.
179. BANA_EDD_MDL-00495468.
180. BANA_EDD_MDL-00496759.
181. BANA_EDD_MDL-00496761.
182. BANA_EDD_MDL-00496774.
183. BANA_EDD_MDL-00496860.
184. BANA_EDD_MDL-00498505.
185. BANA_EDD_MDL-00502609.
186. BANA_EDD_MDL-00515252.
187. BANA_EDD_MDL-00532675.
188. BANA_EDD_MDL-00552698.
189. BANA_EDD_MDL-00573033.
190. BANA_EDD_MDL-00586163.
191. BANA_EDD_MDL-00586455.
192. BANA_EDD_MDL-00586456.
193. BANA_EDD_MDL-00586695.
194. BANA_EDD_MDL-00587330.
195. BANA_EDD_MDL-00587331.
196. BANA_EDD_MDL-00587537.
197. BANA_EDD_MDL-00587538.
198. BANA_EDD_MDL-00619219.
199. BANA_EDD_MDL-00619347.
200. BANA_EDD_MDL-00641652.
201. BANA_EDD_MDL-00643995.
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Appendix A
Documents Considered
202. BANA_EDD_MDL-00683155.
203. BANA_EDD_MDL-00683158.
204. BANA_EDD_MDL-00683159.
205. BANA_EDD_MDL-00684195.
206. BANA_EDD_MDL-00684196.
207. BANA_EDD_MDL-00684454.
208. BANA_EDD_MDL-00684455.
209. BANA_EDD_MDL-00697112.
210. BANA_EDD_MDL-00697114.
211. BANA_EDD_MDL-00697906.
212. BANA_EDD_MDL-00701634.
213. BANA_EDD_MDL-00701637.
214. BANA_EDD_MDL-00705999.
215. BANA_EDD_MDL-00706002.
216. BANA_EDD_MDL-00706007.
217. BANA_EDD_MDL-00706012.
218. BANA_EDD_MDL-00706588.
219. BANA_EDD_MDL-00706589.
220. BANA_EDD_MDL-00711015.
221. BANA_EDD_MDL-00711016.
222. BANA_EDD_MDL-00714960.
223. BANA_EDD_MDL-00714961.
224. BANA_EDD_MDL-00714968.
225. BANA_EDD_MDL-00716446.
226. BANA_EDD_MDL-00716448.
227. BANA_EDD_MDL-00716450.
228. BANA_EDD_MDL-00719114.
229. BANA_EDD_MDL-00719115.
230. BANA_EDD_MDL-00719116.
231. BANA_EDD_MDL-00719209.
232. BANA_EDD_MDL-00845255.
233. BANA_EDD_MDL-00845810.
234. BANA_EDD_MDL-00845812.
235. BANA_EDD_MDL-00845820.
236. BANA_EDD_MDL-00845821.
237. BANA_EDD_MDL-00845868.
238. BANA_EDD_MDL-00845870.
239. BANA_EDD_MDL-00846141.
240. BANA_EDD_MDL-00846145.
241. BANA_EDD_MDL-00846147.
242. BANA_EDD_MDL-00856027.
243. BANA_EDD_MDL-00862684.
244. BANA_EDD_MDL-00862685.
245. BANA_EDD_MDL-00869975.
246. BANA_EDD_MDL-00869978.
247. BANA_EDD_MDL-00870072.
248. BANA_EDD_MDL-00871377.
249. BANA_EDD_MDL-00884198.
250. BANA_EDD_MDL-00886271.
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Highly Confidential – Attorneys’ Eyes Only
Appendix A
Documents Considered
251. BANA_EDD_MDL-00886273.
252. BANA_EDD_MDL-00886275.
253. BANA_EDD_MDL-00886280.
254. BANA_EDD_MDL-00886286.
255. BANA_EDD_MDL-00886293.
256. BANA_EDD_MDL-00886305.
257. BANA_EDD_MDL-00886320.
258. BANA_EDD_MDL-00886322.
259. BANA_EDD_MDL-00886324.
260. BANA_EDD_MDL-00886327.
261. BANA_EDD_MDL-00886330.
262. BANA_EDD_MDL-00886339.
263. BANA_EDD_MDL-00886346.
264. BANA_EDD_MDL-00886347.
265. BANA_EDD_MDL-00886352.
266. BANA_EDD_MDL-00886356.
267. BANA_EDD_MDL-00886359.
268. BANA_EDD_MDL-00886360.
269. BANA_EDD_MDL-00886387.
270. BANA_EDD_MDL-00886404.
Publicly Available Documents
1. “5 Insights of Covid-19 in the Contact Center,” Pindrop , April 30, 2020 (updated on January 17, 2025), available at
https://www.pindrop.com/article/insights-covid-nineteen-in-the-contact-center.
2. “Avaya OneCloud™ Communications and Collaboration Solutions for Advanced Call Center Technologies (ACT), an
Outsourcing Provider, Improve Experiences while Significantly Reducing Costs,” Avaya , April 11, 2022, available at
https://www.avaya.com/en/about-avaya/newsroom/pr-us-220411/.
3. “Bank call centers feeling pressure of COVID-19,” ATM Marketplace , April 28, 2020, available at
https://www.atmmarketplace.com/articles/bank-call-centers-feeling-pressure-of-covid-19/.
4. “Compliance Bulletin and Policy Guidance; 2016-02, Service Providers,” Bureau of Consumer Financial Protection ,
October 31, 2016, available at
https://files.consumerfinance.gov/f/documents/102016_cfpb_OfficialGuidanceServiceProviderBulletin.pdf.
5. “COVID-19’s Impact on Customer Service Volumes,” Help Scout , September 11, 2024, available at
https://www.helpscout.com/blog/support-volumes-covid.
6. “Customer Calls to Companies Rise Amid Coronavirus, but Operators Aren’t Standing By,” Wall Street Journal , March
29, 2020, available at https://www.wsj.com/articles/calls-to-companies-rise-amid-coronavirus-but-operators-arent-
standing-by-11585483200.
7. “Erlang Calculator - for Call Centre Staffing (Online Version 5.0),” Callcentertools , available at
https://www.callcentretools.com/tools/erlang-calculator/.
8. “Erlang Calculator,” CCmath B.V. , available at https://appsource.microsoft.com/en-
gb/product/office/wa200002158?tab=overview.
9. “FTC Strengthens Security Safeguards for Consumer Financial Information Following Widespread Data Breaches,”
Federal Trade Commission , October 27, 2021, available at https://www.ftc.gov/news-events/news/press-
releases/2021/10/ftc-strengthens-security-safeguards-consumer-financial-information-following-widespread-data.
10. “Gramm-Leach-Bliley Act,” Federal Trade Commission , available at https://www.ftc.gov/business-guidance/privacy-
security/gramm-leach-bliley-act.
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Highly Confidential – Attorneys’ Eyes Only
Appendix A
Documents Considered
11. “Guidance On Working Remotely,” PCI SSC , available at https://www.pcisecuritystandards.org/covid19/guidance-on-
working-remotely/.
12. “Hot Topic: Coronavirus Potential impacts on the accounting for arrangements with customers.” KPMG , March 25,
2020, available at https://kpmg.com/kpmg-us/content/dam/kpmg/frv/pdf/2020/hot-topic-coronavirus-revenue.pdf.
13. “How business intelligence can revolutionize contact center performance,” CX Network , December 20, 2024, available
at https://www.cxnetwork.com/contact-center/articles/business-intelligence-contact-center.
14. “How Remote Work Has Changed The Call Center,” Forbes , May 22, 2023, available at
https://www.forbes.com/councils/forbestechcouncil/2023/05/22/how-remote-work-has-changed-the-call-center/.
15. “How to Handle Contact Center Staffing During a Natural Disaster,” ShyftOff , November 8, 2024, available at
https://www.shyftoff.com/blog/contact-center-staffing-during-a-natural-disaster.
16. “Impact of Covid-19 on Contact Centers and Measures Taken,” GEP , October 29, 2020, available at
https://www.gep.com/blog/mind/impact-of-covid-19-on-contact-centers-and-measures-taken.
17. “Improving Pandemic Preparedness: Lessons From COVID-19,” Council on Foreign Relations (2020), available at
https://www.cfr.org/task-force-report/improving-pandemic-preparedness/findings.
18. “Optimising Call Centre Staffing Levels to Manage Call Spikes,” Answer4U , December 11, 2024, available at
https://www.answer-4u.com/blog/manage-call-spikes.
19. “PCI DSS explained: Requirements, fines, and steps to compliance,” CSO , April 3, 2024, available at
https://www.csoonline.com/article/569591/pci-dss-explained-requirements-fines-and-steps-to-compliance.html.
20. “Professional Services Case Study in Focus: Avaya and ACT,” UC Today , August 12, 2022, available at
https://www.uctoday.com/unified-communications/professional-services-case-study-in-focus-avaya-and-act/.
21. “Protecting Payments While Working Remotely,” PCI SSC , available at https://blog.pcisecuritystandards.org/protecting-
payments-while-working-remotely.
22. “Requirements and Security Assessment Procedures,” Payment Card Industry (PCI) Data Security Standard , Version
3.2.1., May 2018, available at https://www.pcisecuritystandards.org/document_library/?category=pcidss.
23. “Supporting Customer Service Through the Coronavirus Crisis,” Harvard Business Review , April 8, 2020, available at
https://hbr.org/2020/04/supporting-customer-service-through-the-coronavirus-crisis.
24. “Visa DPS,” Visa , available at https://usa.visa.com/sites/visa-dps.html.
25. “Visa Issuer and Acquirer Payment Card Industry Data Security Standard Compliance,” Visa , February 10, 2009,
available at https://usa.visa.com/dam/VCOM/global/support-legal/documents/bulletin-issuer-acquirer-pci-dss.pdf.
26. “What Are the PCI DSS Third-Party Service Provider Management Requirements,” PCI DSS Guide , July 13, 2021,
available at https://pcidssguide.com/what-are-the-pci-dss-third-party-service-provider-management-requirements/.
27. “What Is Erlang, and Why Does It Matter?,” CX Today , November 25, 2022, available at
https://www.cxtoday.com/contact-center/what-is-erlang-and-why-does-it-matter/.
28. “What Is Nesting?” Call Centre Helper , available at https://www.callcentrehelper.com/what-is-nesting-219108.htm.
29. “Why Do Call Centers Have High Turnover (and What Can We Do About It),” Medallia , February 15, 2022, available
at https://www.medallia.com/why-do-call-centers-have-high-turnover-and-what-can-we-do-about-it/.
30. “Workplace Monitoring: What’s Allowed, What’s Off Limits?” ADP , February 5, 2024, available at
https://sbshrs.adpinfo.com/blog/workplace-monitoring-whats-allowed-whats-off-limits.
31. Baron, Opher, Joseph Milner, “Staffing to Maximize Profit for Call Centers with Alternate Service-Level Agreements,”
Operations Research 57, no. 3 (2009): 685-700.
32. Harrell, Frank E. Jr., Regression Modeling Strategies , Second Edition, Springer, 2015.
33. Koole, Ger M., and Siqiao Li, “A Practice-Oriented Overview of Call Center Workforce Planning,” Stochastic Systems
13, no. 4 (2023): 479-495, available at https://pubsonline.informs.org/doi/10.1287/stsy.2021.0008.
34. McClave, James T., and Terry Sincich, Statistics , 13th Edition, Pearson, 2018.
35. Robbins, Thomas R., “Evaluating the Fit of the Erlang A Model in High Traffic Call Centers,” IEEE , 2016, available at
https://ieeexplore.ieee.org/document/7822226.
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Highly Confidential – Attorneys’ Eyes Only
Appendix A
Documents Considered
36. Robbins, Thomas R., “Evaluating the Performance of the Erlang Models for Call Centers,” International Journal of
Applied Sciences and Technology (2019), available at https://myweb.ecu.edu/ROBBINST/PDFs/S-12130-TR.pdf.
37. The 2021 US Contact Decision-Makers’ Guide, 13th Edition, ContactBabel.
Note:
I also considered the materials listed in Appendix D of the Expert Report of Jay Minnucci, August 29, 2024, Appendix B of
the Expert Class Certification Report of Greg J. Regan, CPA/CFF, CFE, August 29, 2024, Appendix A of the Expert Rebuttal
Report of Jay Minnucci, November 21, 2024, Appendix D of the Expert Report of Jay Minnucci, March 4, 2025, and
Appendix B of the Expert Report of Greg J. Regan, CPA/CFF, CFE, March 4, 2025.
Page 9 of 9
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Eleven Canterbury, LLC x P.O. Box 111001, Naples, FL 34108 x +1 888-330-6850 x www.elevencanterbury.com
STEPHEN HINDLE
FLORIDA
EXPERIENCE
ACHILLES SHIELD LLC
2007 – Present
Founder, Board Advisor, and Vice President, Tampa, FL
x
Founder of consulting practice advising cybersecurity startups and VC Boards in partnership with the
Israeli Economic and Trade Mission, Washington DC. VP and Operating Officer of consultancy
business across four continents; APAC, EMEA, NAMER, LATAM.
x
Board member of “The American Dog Society”, a 501(c)(3) organization aiming to prevent and reduce
dog abandonment.
x
Board appointed fractional Chief IT & Security Officer for FinTech payments startup, “Orquid
Finance” providing financial services to the immigrant labor industry.
x
Board appointed fractional Chief IT & Security Officer for Television Station subsidiary of Berkshire
Hathaway - ensuring compliance with SEC mandates for cybersecurity.
x
Strategic cybersecurity advisory for disruptive data analytics startup, “Šóta Signal Analytics”
identifying Public Co. accounting fraud. The organization was awarded Entrepreneur of the Year 2023,
by Pasco Economic Development Council
x
Board member and CISO in Residence for two global 501c3 cybersecurity community organizations.
x
“The CISO Society” (>1,500 member CISOs), and “Infosec.Live” (>12,000 member cyber
talent development).
x
Principal Security Advisor in cybersecurity incident response and resilience planning for “Abira
Security.”
x
Principal Chief Security Advisor for sensitive data discovery and loss prevention organization,
“Spirion” providing SME advisory services to their prospective customers.
x
Cybersecurity Board Advisor for Venture Capital group investing in Israeli cybersecurity startups.
MAD MOBILE INC.
2022 – 2023
Disruptive global FinTech payments application development organization.
Global Chief Information Security Officer (CISO) & CIO, Tampa, FL
x
Created and delivered a combined greenfield Cybersecurity and IT strategic plan, which transformed
the organization’s maturity to defined industry standards and defensible Board metrics reporting on
cyber, legal, and risk landscape.
x
Negotiated Cybersecurity and Tech E&O insurance with 75% increase to coverage limits and removal
of 50% ransomware co-insurance obligation. Assessments by global insurance Carriers considered
program and controls to be “Best in Class.”
x
Delivered protective controls, preventing inbound threats including 78 attempts to deploy ransomware.
x
Restored client confidence and increased trust in CI/CD pipelines through automated application/code
scanning platform.
x
Ground-up creation of Governance, Risk Management, & Compliance program, delivering
consolidation of multiple external audits for Anti Money Laundering (AML) and obtaining compliance
certifications for PCI DSS, PCI P2PE, and SOC2.
x
Undertook ownership of IT strategy development with oversight of IT Technical Operations group, as
acting CIO.
x
Established strategic partnership with leading IT solution providers, resulting in >50% reduction in
renewal/replacement costs and improved efficiency by reducing deployment timeframes from >3
months to <4 days.
x
Developed a strategy to perform Cloud consolidation, reduce complexity and overall cost-reduction of
25%.
Highly Confidential – Attorneys' Eyes Only
APPENDIX B
ELEVENCANTERBURY
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x
Curated an Operational Risk Management framework with Board of Directors, providing quarterly
reporting on risk and quantifiable FinOps technology metrics illustrating reduced Total Cost of
Ownership and Return on Investment (ROI).
SITEL GROUP
2016 – 2021
One of the world’s leading business processing outsourcing (BPO) in the Call/Contact Center industry.
Vice President, Head of Global Security, Miami, FL
x
Held accountability for $8MM P&L budget and managing client programs that generated $4B revenue
across 40 countries and supporting 160K employees, 60% of which work remotely. Developed and
managed diverse cyber talent in a team of 60 top performers with strategic oversight of enterprise-level
risk management strategy.
x
Championed data security for complex, internationally recognized clients in highly regulated verticals
including banking and healthcare. Constantly driving innovation, effectiveness, and resilience in the
evolving battle against cyberattacks and data breaches.
x
Developed and maintained ownership and accountability of client relationships, designing, and
promoting service offerings to grow revenue streams, building protection around vital infrastructure,
business operating models, and security frameworks.
x
Resolved cyber risk issues for clients with improved deterrence and protection of legacy systems,
adapting to cloud-native architecture and tactics with upgraded internal controls and policies based
upon NIST Cybersecurity Framework.
x
Orchestrated crisis management for 70 global business continuity events since 2018, including
cybersecurity, civil unrest, extreme weather, power outages, bomb threats, tsunamis, earthquakes,
hurricanes, and Typhoons.
x
Led incident response of three global cybersecurity incidents in 2020, including ransomware and
DDOS. Increased client trust through collaboration and partnership with leading cybersecurity
organizations, strengthening client relationships through transparency and trust, with no loss of business
or revenue.
SYKES ENTERPRISES INC.
1998 – 2016
$2BN public company in the BPO Call/Contact Center industry.
Senior Director, Global Security Operations, Tampa, FL (2008 – 2016)
x
Formulated high level, strategic plans for multi-national Fortune 100-500 clients, prioritizing roadmaps
for data security, business continuity, disaster recovery, physical safety, and compliance to cover 100
locations in 26 countries with over 33K associates. Supplied strategic leadership to seven managers and
directors with a total team of 24 personnel.
x
Brought to life a global compliance assurance program which encompassed contractual requirements
alongside industry and regulatory compliance—served as an industry differentiator and created
alignment among people, processes, and technologies to drive 20% revenue growth in the
telecommunications vertical.
x
Defined best practices based on emerging trends and aligning cyber solutions to business needs and
appetite for risk, which included anti-fraud and social-threat programs as well as protection services in
areas of political and civil unrest.
x
Commended by U.S. military 3-star general for supplying critical intelligence crucial to success of ex-
patriot evacuation during the 2011 “Arab Spring” civilian uprising in Egypt.
Director, Global Security (2003 – 2008)
x
Formed and later Recognized for leading one of SC Magazine’s Top Five “Best Security Teams”
(2008)
x
Championed new business development and global service delivery, offering strategic guidance on IT,
security, & compliance programs.
Highly Confidential – Attorneys' Eyes Only
APPENDIX B
ELEVENCANTERBURY
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x
Formation of the Corporate Security & Risk Management (CSRM) organization and Global Security
Operations Center.
x
Developed payment card industry (PCI) compliance program, servicing 43 clients, and yielding
$850MM annual revenue.
x
Established a robust incident response plan and managed cyber crises in coordination with government
agencies, law enforcement and external counsel, to ensure solutions met with diverse and complex
regulations.
Technical Lead, Regional Enterprise Engineering (2000 – 2003)
x
Expert Witness in criminal trials in the UK and South Africa
x
IT Architect & lead engineer for the EMEA region
x
IT Architect & lead engineer for the EMEA region.
x
Established 24/7/365 resilient, multi-regional data centers with supporting policies, standards, and
processes to provide end-to-end service solutions related to intrusion detection, penetration testing, risk
assessment and audit.
x
Accountable for software licensing and IT standards compliance.
x
Primary point of contact for security concerns and incident response prior to formal structure.

Manager, Training & Consultancy Solutions (1998 – 2000)
x
Developed the first channel reseller training program for Citrix new ‘Multi-user NT’ platform
x
Launched specialized IT consultancy division and developed bespoke training program for partner
alliances, gaining highest-tier partner certification from Microsoft and Citrix to expand business
opportunities.
x
Led engineering of multi-user, thin-client, enterprise architecture for multinational banking, stock-
market, and government customers.
x
Developed bespoke technical training programs and through formation of a 5-person team, delivered to
banking, oil, and defense industry clients globally in 3 languages.
MCQUEEN LTD.
1996 – 1998
Pioneer of offshore global BPO in the Call/Contact Center industry and distribution centers in Europe, Asia and
the USA.
Manager, Customer Engineering, Edinburgh, UK
x
Led the provision of highly technical contact center teams
x
Built and managed outsourced European Response Centre for Insignia Solutions, a cross-platform
Operating System emulation and terminal services provider.
x
Delivered architecture and infrastructure planning for the first multinational contact center in The
Philippines in 1997.
x
Developed IT infrastructure for manufacturing, printing, and fulfilment operations in Galashiels
Scotland, Shannon Ireland, and Nashville Tennessee USA, for McQueen Ltd.
x
Print and production services for NATO threat assessment targets and patented self-healing ballistic
rubber; Rand McNally maps within the USA.
ROYAL BANK OF SCOTLAND
1996
Analyst
x
Online Banking platform development and support.
x
Ensured all associates were appropriately trained for the call/contact center.
x
Transition from mainframe/command-line to Windows.
Highly Confidential – Attorneys' Eyes Only
APPENDIX B
ELEVENCANTERBURY
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Eleven Canterbury, LLC x P.O. Box 111001, Naples, FL 34108 x +1 888-330-6850 x www.elevencanterbury.com

LAND REGISTRY OF SCOTLAND
1995
Technician, Edinburgh, UK
x
Geographical digitization and land dispute resolution of contested boundaries.
x
Technology administration.
SCOTTISH NATURAL HERITAGE
1994
Engineer, Edinburgh, UK
x
Scottish Government conservation and oil-company partnerships.
x
Documentation and technology management.
HM CUSTOM & EXCISE AND INLAND REVENUE
1993
Secretary, London, UK
x
Treasury and collection from debtors for the British government.
x
HM Collector of Taxes and Inspector of Taxes. Documentation and initial contact triage.

EDUCATION
MBA, The PowerMBA, Harvard Business School
Harvard ‘ManageMentor’ Certificates, Harvard Business School, Corporate Learning
Executive & Cloud Financial Taxonomies, Technology Business Management (TBM Council)
Bachelor of Arts (BA), Criminal Justice: Homeland Security, Saint Leo University (with highest honors)
CISSP – Certified Information Systems Security Professional, (ISC)2 since 2007
Building Leadership Impact, Eckerd College
Accelerate Leadership Development, Spencer Stuart
Community-Led Action in Response to Violent Extremism, University of Maryland
Advanced OSINT Tradecraft 1-4, InfraGard National Members Alliance
Network Cyber Threat Hunting, Active Countermeasures
Active Shooter, FEMA
CORE Impact Certified Professional (CICP), Core Security
Advanced Interview & Interrogation, John Reid Institute
Internal Auditor – ISO27001, British Standards Institution (BSI)
Fighting COVID-19 with Epidemiology, Johns Hopkins Bloomberg School
Chinese for HSK Prep 1 – 3.1, Peking University
Microsoft Certified Systems Engineer (MCSE), Microsoft, 1999 – 2002
PUBLICATIONS
Everything Starts with a Why: How to Promote Meaningfulness at Work, AuditBoard
Journey of a CISO, Cisco Secure
Achieving Cyber Resilience in Today’s Threat Landscape, Cyberclan
Cybersecurity Strategies & Challenges of a Hybrid World, Cisco
Success Stories, Sykes Enterprises Inc
The State of Continuous Controls Monitoring, The CISO Society & Regscale
The 2024 State of Data Security Report, The CISO Society & BigID
Generative AI: LLM-Ready Data, Spirion
SolarWinds Ruling: Why CISOs Need to be Aware of Fraud, Bank Info Security
Debunking the Myths About Cyber Risk Quantification, AuditBoard
Empowering the Hybrid Workforce, Securely, Cisco
Highly Confidential – Attorneys' Eyes Only
APPENDIX B
ELEVENCANTERBURY
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Highly Confidential - Attorneys ' Eyes Only
Exhibit 1
----------------
---------------
- • ..
- • ..
Sources:
[1] DX 116, BANA_EDD _MDL-00719115, tab '
[2] Minnucci Report, Table 9 and Table 10.
-
-
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