Court filing

Exhibit 3 — In re Bank of America California Unemployment Benefits Litigation (Dkt. 386-3, S.D. Cal. No. 3:21-md-02992)

Filed December 2, 2024 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	2024-12-02

U.S. District Court for the Southern District of California · No. 3:21-md-02992-GPC-MSB · Doc. 386-3 · 2024-12-02 · Docket on CourtListener

Full text

Exhibit 3
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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 REPORT OF JAY MINNUCCI
August 29, 2024
REDACTED PUBLIC VERSION
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i
TABLE OF CONTENTS
I.
ASSIGNMENT .................................................................................................................1
II.
SUMMARY OF EXPERT QUALIFICATIONS .............................................................2
III.
SUMMARY OF OPINIONS ............................................................................................5
IV.
FACTS AND DATA CONSIDERED ..............................................................................8
V.
HOURLY RATE ..............................................................................................................8
VI.
BACKGROUND ..............................................................................................................8
A.
Bank of America’s Prepaid Call Center Operations ............................................8
B.
Call Center Industry Performance Standards ......................................................13
C.
Call Center Industry Operational Standards .......................................................15
VII.
STATEMENT OF OPINIONS AND BASIS FOR OPINIONS ....................................17
A.
Bank Subjected EDD Debit Cardholders Seeking Assistance with
Unauthorized-Transaction Claims to Unprecedentedly Long Wait
Times that Fell Far Below Industry Performance Standards .............................17
B.
The Bank’s Practice of Understaffing Its Claims Call Center in the
Face of Foreseeable Call Volume Surges Was Inconsistent with
Industry Standard Practice ..................................................................................23
C.
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 ..................................34
D.
The Bank’s Deliberate Understaffing Choice Harmed Cardholders
While Saving the Bank Money ...........................................................................46
VIII.
CONCLUSION ..............................................................................................................50
Appendix A: Curriculum Vitae ...................................................................................................51
Appendix B: Prior Publications (March 2014 to Present) .........................................................53
Appendix C: Prior Testimony (January 2020 to Present) ..........................................................55
Appendix D: Materials List .......................................................................................................56
Appendix E: Survey Results, The 2021 US Contact Center Decision Makers’ Guide .............60
Appendix F: Claims Call Center Data 2020-2021 .....................................................................61
Appendix G: Fraud Tier 2 Call Center Data 2020-2021 ............................................................63
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I.
ASSIGNMENT
1.
I have been retained as an expert witness in this matter by Cotchett, Pitre &
McCarthy LLP, and Altshuler Berzon LLP (“Counsel”), co-lead counsel for the Class Plaintiffs.
2.
I understand from Counsel that Class Plaintiffs are seeking certification of five
classes, three of which are relevant to this report: (1) a “Claim Denial” class, defined as all Bank
of America EDD debit cardholders who notified the Bank that an unauthorized transaction had
occurred on their Bank of America EDD debit card account (“Claim”) at an automated teller
machine (“ATM”), and whose Claim the Bank denied or closed at any time from September 28,
2020, through June 8, 2021, based solely on Indicator 1 of the Bank’s Claim Fraud Filter
(“CFF”); (2) a “Credit Rescission” class, defined as all Bank of America EDD debit cardholders
who received permanent credit from the Bank in connection with their Claim, which credit the
Bank rescinded at any time from September 28, 2020 through June 8, 2021, based solely on
Indicator 1 of the Bank’s CFF; and (3) a “Customer Service” class, defined as all members of the
Claim Denial Class and/or Credit Rescission Class who telephoned the Bank’s customer service
telephone number for its EDD 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. Counsel have asked me to review and analyze certain documents and data produced by
the Bank and testimony provided by the Bank’s Rule 30(b)(6) designees on matters related to the
Customer Service Class’s claims. Specifically, Counsel have asked me to determine the
following:
a.
The Bank’s Claims call center performance metrics during 2020 and 2021,
as measured using industry standard metrics;
b.
Whether the Bank’s Claims call center performance metrics fell below
industry standards, and if so, to what extent and during what period;
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c.
Whether the operational processes and technology the Bank utilized in its
Claims call center in 2020 and 2021 fell below industry standards, norms,
and best practices;
d.
Whether there were reasonable alternative actions the Bank could have
taken consistent with industry standard practices to avoid or mitigate the
adverse impact on EDD debit cardholders who telephoned the Bank’s
customer service telephone number for its EDD 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; and
e.
The effects on EDD debit cardholders of the Bank’s performance failures
in its Claims call center between September 13, 2020 through November
21, 2020.
II.
SUMMARY OF EXPERT QUALIFICATIONS
3.
I am the founder and owner of Service Agility, Inc. (“Service Agility”), an S-Corp
domiciled in Pennsylvania. Service Agility was founded in 2008 and provides consulting,
training, and related services to the call center industry.
4.
I received a Bachelor of Business Administration from Temple University in
1984, graduating magna cum laude.
5.
My entire professional career—more than four decades—has been in the call
center industry, working for and advising in-house departments and third-party vendors that
handle inbound and outbound customer service calls, and the corporate managers that oversee
those departments and vendors. I spent 17 years in various leadership positions in a call center
and have served as a consultant, author, speaker, and trainer for more than the last two decades.
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6.
In October 1983, I began working in the 800-seat call center serving the AARP
Group Health Insurance Program, where I held a variety of supervisory and management roles,
in both the call center and related back-office departments.
7.
In 1995, I was promoted to Director and Senior Director roles at that call center,
where I established policies and practices to maximize call center performance while minimizing
staffing expenses. Some of my core responsibilities over the next five years in those positions
included:
a.
Forecasting and budgeting oversight, including developing staffing
expense estimates and monitoring actual spend vs. projections.
b.
Meeting our key performance metric of service level, which is a
measurement of the percentage of calls answered within a certain number
of seconds (e.g., 70% of calls answered within 30 seconds), while
minimizing staffing expenses.
c.
Designing and developing the organization’s first Workforce Management
Team. In a call center, the Workforce Management (“WFM”) team is
responsible for forecasting incoming call volumes and associated average
handling times (the amount of time required to complete a call from the
time it is answered), and using those projections to calculate the number of
staff needed to meet the organization’s targeted service level objectives.
d.
Overseeing proper maintenance and support for key applications and
systems, including overseeing telephone IT support positions (which
perform technology related functions that are essential to satisfying call
center performance metrics, such as designing and maintaining phone
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systems, Interactive Voice Response (IVR) systems, outbound calling, and
call monitoring).
8.
Following my 17 years of work in a call center, I began work as a call center
consultant, first as Vice President of Consulting from 2000 to 2008 at the International Customer
Management Institute (“ICMI”), where I provided call center consulting services to the Federal
Reserve Bank, Discovery Financial, Charles Schwab, Wells Fargo, and dozens of other clients.
During that time, I grew the firm’s consulting revenue from $0 to over $3 million per year. In
2008, I founded my own company, Service Agility, which has provided consulting services to
over 100 clients operating call center services, including MetLife, Nationwide Insurance,
Guardian Life, LGE Community Credit Union, Thrift Savings Plan, United Healthcare, Allstate,
and UBS Group. Through my work at both ICMI and Service Agility, I have, among other
things: advised clients on best practices in selecting and managing an outsourcing provider;
overseen the drafting, negotiation, and revision of General Service Agreements (GSAs) and
Statements of Work (SOWs) involving dozens of call centers; provided guidance on determining
proper staffing levels, including for call center agent positions, as well as other support positions;
created forecasts and scheduling tools to help determine staffing needs; built quality assurance
programs to help clients optimize call handling processes and results; educated clients on
recruitment, training and employee retention strategies; and counseled executive teams on setting
objectives and monitoring performance in call centers.
9.
In addition to my consulting work, I speak at industry events and I have published
several articles in leading trade publications, focusing on best practices for the management of
call centers. More detail on my background is provided in my Curriculum Vitae in Appendix A.
Details of my published works in the past ten years are included in Appendix B.
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10.
I have designed and delivered training courses for call center managers around the
globe. Through those courses, I estimate that I have trained well over one thousand call center
managers.
11.
I have also worked as an expert witness in several cases involving call center
operations, technology, service contracts, and related performance standards. A list of the cases
in which I provided testimony under oath in the past four years appears in Appendix C.
III.
SUMMARY OF OPINIONS
12.
The Bank’s data shows

seen in the call center industry. For example, the
average speed to answer (“ASA”) is an industry-standard metric that reflects the average amount
of time a customer is kept waiting on hold before their call is initially answered, a metric that is
typically measured in seconds. The average ASA reported in 2020 across 214 call centers
surveyed by ContactBabel was 75 seconds (1.25 minutes), which is consistent with (but on the
higher end) of my understanding of the industry standard ASA generally.1 By contrast, between
September 13, 2020 and November 21, 2020,

industry average. The performance of the Bank’s Claims call center

1 The U.S. Contact Center Decision-Makers’ Guide is a report published by ContactBabel
annually studying the “performance, operations, technology and HR aspects of US contact center
operations;” the 2020 survey included data from 214 U.S.-based call centers, including 29 from
the Finance industry and 28 from the Outsourcing/Telemarketing industry. Ex. 112 (The 2021
US Contact Decision-Makers’ Guide, 13th Edition, ContactBabel) at 13, 46. In this report, “Ex.”
refers to exhibits attached to the Declaration of Connie K. Chan in Support of Plaintiffs’ Motion
for Class Certification (“Chan Decl.”), which are also listed in Plaintiffs’ concurrently filed
Index of Exhibits.
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during this ten-week period in the Fall of 2020

in my 41 years in the industry.2
13.
Virtually all EDD debit cardholders who telephoned the Bank between September
13, 2020 and November 21, 2020 and had their calls routed to the Bank’s Claims call center
(which I understand includes all EDD debit cardholders who informed the Main call center that
they were calling either (a) to submit an unauthorized transaction claim, (b) to inquire about or
seek reconsideration of a claim that the Bank had automatically denied based on the results of its
Claim Fraud Filter, or (c) to inquire about or seek reconsideration of the Bank’s rescission of
previously issued permanent credit based on the retroactive application of its Claim Fraud Filter)
thus
In their effort to
get the Bank’s Claims call center to answer their calls,

.
14.
The very long wait times to which EDD debit cardholders were subjected

The average abandonment rate in 2020 across
call centers surveyed by ContactBabel was 6.1%.3 By contrast,

.
Because wait time before abandonment is not included in the ASA data, ASA understates the

2 To date, the only call center I have seen provide similarly inadequate service over two+ months
is

3 See Ex. 112 (2021 Decision-Maker’s Guide) at 46.
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actual amount of time spent on the phone by the many EDD debit cardholders who had to call
and wait multiple times before connecting with a CSR.
15.

16.
Although the Customer Service class as defined by plaintiffs includes only those
EDD debit cardholders who called the Bank and were routed to the Claims call center between
September 13, 2020 and November 21, 2020,

17.
The Bank’s consistent conduct in understaffing its Claims call center and not
using standard technology

while causing significant harm to EDD debit cardholders.
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IV.
FACTS AND DATA CONSIDERED
18.
In preparing this report, I have relied on my general knowledge, training,
experience, and other expertise accumulated during my 41 years as an executive and consultant
in the call center industry. In addition, during the course of my analysis, I have relied upon
documents and information produced in discovery in this case as well as publicly available
documents and information. I have relied upon the materials cited in this report and those
materials cited in Appendix D.
19.
My work on this matter is ongoing, and I may review additional materials or
conduct further analysis. I reserve the right to update, refine, or revise my opinions as
appropriate, including should additional information become available to me.
V.
HOURLY RATE
20.
I am being compensated for my work on this matter at a rate of $375 per hour.
The compensation for my work in this matter is not contingent upon the nature of my findings or
on the outcome of this litigation.
VI.
BACKGROUND
A.
Bank of America’s Prepaid Call Center Operations
21.
In the 2020-2021 timeframe covered by this report, the Prepaid call centers at
Bank of America served

4 Ex. 113 at -643387-88.
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22.
From April 2020 to June 2021, the Bank’s customer service operations for its
prepaid debit cardholders

.5
23.
.6

.7 The IVR system prompted callers to provide basic
authentication information (such as name and card number) and gave cardholders several self-
service options (e.g. card balance inquiries, recent transaction activity).8

.10

.11
24.

.12

5 Ex. 114 (BANA’s Responses & Objections to Plaintiffs’ Fifth Set of Interrogatories (“5th
Rogs”), No. 34).
6 Ex. 18 (Rule 30(b)(6) Depo. of William Golden (“Golden Tr.”)) 100:2-9.
7 Ex. 18 (Golden Tr.) 100:16-21.
8 See Ex. 115 at -2453.
9 Ex. 114 (5th Rogs, No. 34), 14:26-15:4.
10 See Ex. 116 at -153673-74.
11 Ex. 18 (Golden Tr.) 32:5-21.
12 Ex. 114 (5th Rogs, No. 34), 15:5-14.
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25.

.13

.14
26.

.15

.16
27.

.17

13 Ex. 114 (5th Rogs, No. 34), 15:11-22.
14 See id.; Ex. 116 at -153673-74; Ex. 14 (Rule 30(b)(6) Depo. of Shane Daniels (“Daniels Tr.”))
84:23-86:24.
15 See Ex. 18 (Golden Tr.) 32:5-21, 100:2-21, 168:5-17.
16 See ibid.
17 Ex. 114 (5th Rogs, No. 34), 15:23-16:12.
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.18
28.

.19

29.
I understand that the Bank

.20

, it is reasonable
to estimate that the percentage of total Claims calls attributable to EDD debit cardholders would
be approximately 56% in 2020.

18 Id.
19
. Compare
Ex. 117

).
20 Ex. 18 (Golden Tr.) 57:19-25.
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30.
At all relevant time periods, the Bank

.21

.22

.23

.24

.25

.26

,27

.28
31.
The Bank’s telephone system

.
Some of the calls

21 Ex. 18 (Golden Tr.) 58:13-60:5.
22 Ex. 18 (Golden Tr.) 47:16-22.
23 See Ex. 118 at -172242; Ex. 119 at -60237; Ex. 18 (Golden Tr.) 47:4-15.
24 See Ex. 18 (Golden Tr.) 48:2-9; Ex. 119 at -60237.
25 See Ex. 126 at -90040.
26 Compare, e.g., Ex. 120 (246363) at May – English tab, Cell B8 (showing 57,424 EDD Main
calls offered to TTEC on May 4, 2020), with Ex. 121 at -356316

27 See Ex. 122 at -171905.
28 Ex. 18 (Golden Tr.) 59:13-60:13.
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.29 The Bank had

.
B.
Call Center Industry Performance Standards
32.
Call centers operate in what is referred to in the industry as a “real-time”
environment, meaning that phone calls must be answered shortly after being queued for an agent.
It is well known in the industry that failure to answer incoming calls shortly after they are
queued results in high rates of call abandonment (i.e., where the caller hangs up before the call is
answered), resulting in high levels of customer dissatisfaction.
33.
Call centers are heavily reliant on data to manage operational performance. Since
the emergence of call centers in the 1970s, phone equipment has been developed to track and log
nearly every event that occurs during a call center call (e.g., the specific welcome message
played, the selection made by the caller on the main menu, the time the call was queued to an
agent, etc.). By logging these events, a phone system can generate massive amounts of data
related to both group and individual CSR performance, which is reviewed by managers.
34.
There are standard call center performance metrics that nearly every call center
measures. These include the incoming volume of calls (also referred to as offered calls), the
number of calls handled (also referred to as answered calls), the number and percentage of
abandoned calls, and the speed with which calls are answered. The Bank collected and tracked
this data for its Prepaid call centers.30

29 See Ex. 123 at -13135, section 21.2.
30 See, e.g., Ex. 124 at -719115); Ex. 125 at -719116.
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35.
Two of the most common metrics for evaluating call center performance are
average speed of answer (ASA) and abandonment rate.31 The ASA is the arithmetic mean of the
number of seconds each answered call remained on hold before the caller was connected to a live
CSR, while the abandonment rate is the percentage of callers who hang up or are otherwise
disconnected after their call enters the hold queue but before their call is answered.32 These are
standard measurements that call center vendors regularly report to their clients, often multiple
times per day. The Bank

.33
36.
Table 2 below shows the average ASA and abandonment rate over a nine-year
period for 214 call centers that completed an annual survey conducted by ContactBabel
(complete results regarding performance metrics of these centers are provided in Appendix E).34
Table 2: Average ASA and Abandonment Rates for US Call Centers, 2012-2022

37.
As shown in Table 2, the average ASA across these 214 call centers in 2020 was
75 seconds (1.25 minutes). The average abandonment rate in 2020 was 6.1%. Although this
survey reported ASA and abandonment rates as an annual average, the most common interval for
reporting ASA and abandonment rate performance is a month. Based on my experience and

31 See Susan Hash, Metrics Roundup, CONTACT CENTER PIPELINE (Oct. 2019),
https://www.contactcenterpipeline.com/Article/contact-center-metrics-roundup (identifying
abandonment rate and response time as among the most-used call center performance metrics).
32 Id.; see also Ex. 18 (Golden Tr.) 32:22-33:11.
33 See, e.g., Ex. 124 at -719115; Ex. 125 at -719116; Ex. 18 (Golden Tr.) 60:24-61:14.
34 See Ex. 112 (2021 Decision-Makers’ Guide) at 46.
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familiarity with performance standards in the industry, an ASA of 1.25 minutes and an
abandonment rate of 6.1% is consistent with industry standards for acceptable average
performance levels across a single month, although it is on the higher end of what is considered
acceptable.
38.
The vast majority of call center vendors operate under contracts that specify
performance targets for both ASA and abandonment rate.

,35 which is a common industry target for
abandonment.

.36 Because ASA and abandonment rate are among the
most frequently reported call answer metrics in the Prepaid call centers, those metrics are used
throughout this report to measure call answer performance.
C.
Call Center Industry Operational Standards
39.
Call center performance is affected by numerous variables that could drive surges
and declines in call volume. Call centers have a variety of standard industry practices available to
help forecast changes in call volume and to prepare for and respond to unanticipated events, and
to ensure they maintain satisfactory call center performance in the face of changing
circumstances.
40.
For example, call centers often employ skilled analysts that, with the assistance of
forecasting software, predict call volume and staffing requirements from the monthly level down

35 See e.g., Ex. 126 at -90046
; Ex. 127 at -13092

; Ex. 128 at -12882-83
and Ex. 130).
36 See ibid.
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to fifteen-minute time intervals.37 It is not uncommon for call volumes to surge dramatically in
response to external events or other changed circumstances.38 Whenever decisions are being
considered that could impact incoming call volumes and/or the average time it takes to process a
transaction, it is a standard practice to first consult these analysts to determine the likely impact
of such a decision on staffing requirements. This advance planning enables the client overseeing
the call center to make whatever staffing changes are necessary in advance of the implementation
of the decision so customer wait times are not negatively impacted.39 If 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.
41.
When call center operations are outsourced, it is standard industry practice for the
client and vendor to document the process for establishing staffing levels.

37 See Lori Bocklund, Support Technology without an Analyst Is Like a Car without a Driver,
CONTACT CENTER PIPELINE (May 2021), https://www.contactcenterpipeline.com/Article/support-
technology-without-an-analyst-is-like-a-car-without-a-driver (detailing the role of skilled, trained
analysts in using contact center technologies to optimize staffing).
38 Ex. 131 (The 2023 US Contact Decision-Makers’ Guide, 15th Edition, ContactBabel) at 31
(“Understanding how the business will change some months in advance – perhaps for seasonal
reasons, or with the launch of a new product – will certainly impact on resourcing, and close
communication and integration between resource planning and day-to-day WFM is desirable.”).
39 See Ex. 131 (2023 Decision-Makers’ Guide) at 30 (“The modern contact center not only
requires the basics (having enough people to answer interactions in a reasonable amount of
time), but also more sophisticated functionality such as the ability to forecast and schedule
agents in near-real time and handle virtual contact centers, mobile resources and home- working
resources.”).
40 See Ex. 126 at -90040, section 3.4; Ex. 127 at -13086, section 3.4; Ex. 132 at -13097, section
3.5.
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.
VII.
STATEMENT OF OPINIONS AND BASIS FOR OPINIONS
A.
The Bank Subjected EDD Debit Cardholders Seeking Assistance with
Unauthorized-Transaction Claims to Unprecedentedly Long Wait Times that
Fell Far Below Industry Performance Standards.
42.

.41

.42
43.
During 2020,

. As depicted in Appendix F,

. Later in the year,

41 See Ex. 118 at -172242.
42 The Bank’s designee testified

. See Ex. 18 (Golden Tr.) 99:11-100:1. See also workflow at Ex. 118 at -
172243.
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.
44.
While these numbers represent averages,

Combined with the Banks’ data

industry
standards.43
45.
Comparing performance in the

.
46.
The average ASA in 2020 among the 214 call centers surveyed by ContactBabel
was 75 seconds (1.25 minutes), which the data shows is on the high end of what is typically
considered an acceptable ASA and likely reflects the pandemic circumstances.

43 See Ex. 124 at -719115.
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.44 This means that cardholders who called the Bank

. The 2020 performance of the Bank’s Claims call center is by far the worst
I have seen across a full year in my 41 years in the industry,

.
Table 3: Average Speed to Answer Comparison, September 13 – November 21, 2020

44 The weighted average

, based on data from Ex. 124.
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Figure 1:

47.

. Abandonment rate is another
commonly reported metric reflecting call center performance.

,45 and in 2020 the average
abandonment rate among the 214 surveyed companies was 6.1%. In my experience these figures
are consistent with industry norms.

. In short,

than at companies participating in the 2020 ContactBabel survey. While this
is already far outside the industry norm,

45 See Ex. 126 at -90046.
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These are
extraordinarily high levels of abandonment that any competent call center operator would be
expected to undertake enormous efforts to avoid.
48.
Another common performance metric, related to abandonment rate, is average
abandon time (also known as “abandon delay”). This metric measures how long on average a
caller who ultimately abandons the call waited on hold before hanging up.

.46

.47
49.

. ASA data
only accounts for the time spent waiting on a call that ultimately connects and does not include
this time that callers wait before abandoned or disconnected calls. As such, ASA understates the
total wait time

46 Because call centers strive to keep abandonment rate as low as possible and generally under
5%, average abandon time is a less frequently reported metric because, in most call centers, it
reflects the experience of a very small number of callers. As such, the ContactBabel survey did
not include this metric.
47 Average abandon time weighted on abandoned calls as provided in Ex. 124.
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Table 4:

Figure 2:

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50.
To summarize, EDD debit cardholders who telephoned the Bank

at surveyed companies.
B.
The Bank’s Practice of Understaffing Its Claims Call Center in the Face of
Foreseeable Call Volume Surges Was Inconsistent with Industry Standard
Practices.
51.
Understaffing was the root cause of the poor service in the Claims call center
from April 26, 2020 to June 13, 2020 and again from September 13, 2020 to November 21, 2020,
and the Bank’s documents and testimony

. Long wait times and high abandonment rates are
entirely avoidable, even in the face of call volume surges, if a call center properly forecasts call
volume and staffs its call centers accordingly. The 2020 ContactBabel survey and my experience
with clients grappling with similar pandemic-related issues show that many call centers were
able to provide adequate services to their customers within weeks of the onset of the pandemic.
52.
Wait times are a function of call volume, average handle time, and call center
staffing. When call volume increases are projected, call center staffing needs to be
correspondingly increased in order to maintain adequate levels of service.

.48 Such a practice is well outside of industry-standard

48 See Ex. 18 (Golden Tr.) 66:8-68:6.
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24
operating procedures, certain to result in sub-standard performance, and not adopted by
competent call center operators.
53.

.49

.
54.
The Bank’s designated witnesses have testified that the Bank’s standard practice
was to

.50

.
55.
The Bank’s admitted practice of

is well outside of standard operating procedures, because

are known to be the cause of performance results that are widely viewed in the industry as

49 See Ex. 18 (Golden Tr.) 69:5-20.
50 Ex. 18 (Golden Tr.) 66:8-68:6.
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25
unacceptable. There is, in fact, an entire field of specialization within the call center industry
known as Workforce Management (WFM) dedicated to forecasting volumes and calculating
staffing needs in advance.51 WFM teams employ skilled analysts using forecasting and
scheduling software for the purpose of being appropriately staffed at all times.52 Documents
produced by the Bank in this litigation show

.
56.
As early as April 2020,

.53

.54

.
57.
The method used by the Bank’s

51 See Ex. 112 (2021 Decision-Makers’ Guide) at 47-49 (describing the importance of
forecasting to call center operations and the many inputs that can contribute to more accurate
staffing forecasts).
52 Of the call centers surveyed by ContactBabel, 90 percent of large call centers (more than 200
agents) and 67 percent of Finance call centers used specialized workforce management
forecasting and scheduling software. See Ex. 112 (2021 Decision-Makers’ Guide) at 54-55. As
virtually all call centers at this size engage in forecasting, other call centers are likely using Excel
or other in-house tools.
53 See, e.g., Ex. 133 at -60339, tab labeled “
,”

labeled “
.”
54 See, e.g., Ex. 133 at -60339, tab labeled “
,”
.
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26
. Most call centers depend on a multitude of factors (e.g.,
business growth rate, seasonality factors, event timing, etc.) to project future volume. This
process is not only complex, but it requires that all of these factors align with expectations to
produce a reliable forecast. Here, by contrast, the Bank was able

.55 The R squared value is a measure of how well one data set (

) explains variance in another (
).
The R squared value can be used to compare any two sets of data, with readings ranging from a
minimum of 0 (meaning no correlation) to a maximum of 1.0 (perfectly correlated). Over my
career, I have run these types of calculations for dozens of call centers, and I have never
encountered this high of a correlation from a single factor. For call center forecasting, an R2 of
.7 will deliver monthly forecasts with error rates typically below 10%, meeting the target
accuracy rate used most often in the industry.

55 See, e.g., Ex. 133 at -60339, tab labeled “
,”

.”
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27
58.

.56 To ignore a forecast
with proven reliability is completely outside of normal operating procedure for a call center.
59.
In the Fall of 2020, in addition to

, the Bank also

.57
60.
In other words, a key driver of the

56 See supra ¶¶53-55.
57 Ex. 18 (Golden Tr.) 75:14-76:2; 124:11-125:1.
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.”58 The Bank’s witness acknowledged

.59
61.
Deliberately subjecting customers to intentionally prolonged wait times is
unheard of in the call center industry. In my 41 years in the industry, I have never heard of a call
center deliberately taking such actions to increase wait times and impede the provision of
customer service. This is especially true where the affected customer population is seeking a
critical service, such as (in this case) public benefits recipients seeking customer service to help
them recover money that has been stolen from their account.
62.
I have consulted for approximately a dozen clients that answer calls that I would
consider to be of a similar level of importance to the calls directed to the Bank’s Claims call
center, ranging from suicide hotlines (at the highest level of importance) to other critical
customer service roles such as physical/mental health care advisors and utility companies. In my
experience, such companies and service providers recognize they have particularly vulnerable
customers and take care to balance their legitimate business concerns against the significant
harms that could result from inadequate customer service. In my experience, such companies and
service providers take their responsibilities to these vulnerable customers seriously, prioritizing
quick speeds of answer and high-quality customer service interactions above other legitimate call
center or corporate objectives. During my career, I have never heard—and cannot imagine
hearing—any supervisor or executive in one of those call centers suggesting that

58 See, e.g., Ex. 77 at -118438 (

”); Ex. 134 at -106093-94 (

.”).
59 Ex. 18 (Golden Tr.) 85:25-87:2.
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.
63.

.
64.
The Bank’s implementation of the

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.
Table 5:
:
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31
Figure 3:
:
65.
As Table 5 and Figure 3 demonstrate,

.
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32
66.
Not only did the Bank cause these

.
67.
For decades, telephone systems (

) have offered an Estimated Wait Time (EWT) application that
would provide callers in queue an estimate of how long before their call would be answered.
This application allows callers to make better decisions concerning whether to wait on hold, and
if they choose to wait, they might at least be able to get some tasks done before the time the call
should be answered. Despite the availability of EWT technology,

.
68.
In addition, for several decades, many phone systems have also offered virtual
queuing. This application provides each caller the EWT, and then offers to hold a caller’s place
in queue and to call back when it is the caller’s turn, thereby allowing the caller to attend to other
matters until the system initiates the scheduled callback.60 This feature is now native to many
phone systems, but even those systems without it can add it on from a third-party vendor, making

60 See Jason Barro, Rahul Sethi, Alison Leibovitz, and Blair Markell, “Please Don’t Hold”: A
Better Banking Call Center Experience, BAIN & CO.: INSIGHTS (Feb. 16, 2023),
https://www.bain.com/insights/please-dont-hold-better-banking-call-center-experience-snap-
chart/ (“[B]anks can boost satisfaction during disputes by giving customers the option to receive
a callback rather than holding. Customers who chose a call back gave a Net Promoter Score of
28 points, compared with a Net Promoter Score of –3 from those who didn’t have a choice.”).
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33
the feature available to any call center willing to purchase it.

.61
69.
It is difficult to overstate just how poor the Bank’s Claims call center performance
was in 2020 compared to typical call center performance, even after factoring in the pandemic.
With no other service channel available to address Claims calls, and no other option but to
remain on hold waiting for a CSR with no idea how long the remaining wait time would be,
callers seeking assistance with their unauthorized-transaction claims were forced to endure the
exceptionally long waits experienced in 2020. Despite speed-to-answer metrics being cited as
one of the three most important metrics by 36% of call centers,62 the Bank took the opposite
approach and imposed long wait times on its EDD debit cardholders,

63 The Bank’s documents reflect that a

.64 In my 41 years of experience in the industry, I have never seen a call center managed
with such total disregard for the customer’s experience and need for service.

61 See Ex. 18 (Golden Tr.) 97:5-98:19.
62 See Ex. 112 (2021 Decision-Makers’ Guide) at 45.
63 See Ex. 77 at -118438 (

”).
64 See Ex. 134 at -106094. To the extent that the Bank’s primary purpose in understaffing the
Claims call center was to deter fraudulent claims, it is not clear from the Bank’s documents or
testimony

.
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34
C.
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.
70.
Although the Customer Service Class is limited to EDD debit cardholders who
called the Bank and were routed through the Main call center to the Claims call center between
September 13, 2020 and November 21, 2020, the substandard performance level in the Claims
call center during this period was not an isolated occurrence for the Bank. Rather, it is
representative of systemic failures by the Bank to provide call-center customer service to its
EDD debit cardholders that was consistent with industry standards.

. In my
experience, the hold times to which the Bank subjected EDD debit cardholders are virtually
unprecedented in the call center industry. The Bank also engaged in a variety of other reckless
and irresponsible call center practices that are far outside the norms of industry standard
practices.
Failure to Plan for Disasters Leading to Excessive Disconnected Calls
71.
The Bank failed to engage in reasonable planning for its Prepaid call centers for
potential staffing-intensive events like the pandemic. As a result of those failures, during the
early months of the pandemic, callers to the Bank’s Prepaid call centers were more likely to be
disconnected or dropped than to actually get through to a CSR in the Main call center (which, as
previously discussed, was a necessary step before a caller could speak with a CSR in the Bank’s
Claims or Fraud call centers).
72.
The Bank was

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35
.65 That provisioning
involved determining how many phone lines are needed and then obtaining them from the phone
company. Calculating the correct number of these lines requires, among other factors, a forecast
of the busiest phone hour expected in the future.

. By mid-April,

.66 Another report from the Bank showed that

.67 It is not clear how long the Bank continued to generate

, but this significant gap

generated disastrously high levels of disconnects.
73.
In late March/early April 2020,

.68
, though, even
in non- pandemic circumstances, which may be why the

69 The Bank’s

65 See e.g., Ex. 135 at -382184, sections 5.5.1 to 5.5.4.
66 See Ex. 136 at -352986.
67 See Ex. 137 at -288640.
68 See Ex. 137 at -288641, item 3.
69 Ibid.
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.
74.
Facing a significant number of disconnects and an unknown timeframe to
provision additional phone lines,

.70

.71 A second issue was the

.72

.73 Eventually,

.74

70 Ibid at -288640, item 1.
71 See Ex. 151 at -103078. A “
”—

.
72 Ibid.
73 See Ex. 137 at -288637.
74 See Ex. 151.
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37
75.
In place of the

”75 which in the industry is more commonly referred to as call diverting or
call blocking, and which many callers perceive as being hung up on.
,76

.
76.
By mid-April 2020,

.
While no call center wants to invoke a disconnect message, prudent disaster recovery planning
measures include the potential use of such a message. Knowing this, AT&T has for decades
provided call center operators an option to set up such a message in advance, in the AT&T
network cloud, to be deployed immediately and with minimal effort through an online portal or a
call to AT&T. This capability is well known to industry professionals and is utilized by many
call center operators using the AT&T network. In fact,

.77

75 See ibid at -103076.
76 See Ex. 138 at -424944.
77 See, e.g., Ex. 139 at -718999.
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.78

.79
77.
despite the Bank’s contractual promise, made
when securing the EDD’s business, that “no call” would be “transferred to voicemail or
automatically disconnected from the queue.”80 A genuine commitment to an objective of “no
disconnects” would have required the Bank to analyze potential volume surge scenarios, to
invest in enough phone lines to handle the increased traffic projected in these scenarios, and to
have back-up plans ready to implement quickly if call volume were to expand beyond what was
projected.

.
78.
This lack of

78 See, e.g., Ex. 140 at -21114 and Ex. 139 at -718999.
79 See Ex. 138 at -424947.
80 See Ex. 22 at 185, requirement 203.
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81

.
Understaffing Leading to Excessive Wait Times in the Fraud Call Center
79.
Although the Customer Service Class is limited to EDD debit cardholders who
called the Bank and were routed to the Claims call center between September 13, 2020 and
November 21, 2020,

.
80.
The Bank’s

.
81.

.
82.

81 See Ex. 18 (Golden Tr.) 334:22-335:23.
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83.

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.
Figure 6:

84.
The principal cause of the

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:
85.
Just as in the Claims call center,

.
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43
86.

,82

83
.
87.
Comparing 2020 performance in the
call centers
to the performance of other call centers during this pandemic year helps quantify how truly poor
the Bank’s results were. Callers to

is by far the worst I have seen across a full year in my 41 years in the industry.
Lax Security Protocols in the Transition to Work-from-Home
88.
Call centers often have access to and utilize personal and confidential customer
information to complete transactions. Phone representatives see this information on screen and
hear it in discussions with callers. Call center systems use this information across various
applications, such as customer databases, IVR systems, and call recording equipment.
Maintaining security over this information is vitally important, and many industries have
documented standards to be followed by call centers to provide the appropriate level of security.
In the financial services industry, the Payment Card Industry Data Security Standard (PCI DSS)

82 See Appendix G,
.
83 See Appendix G,
.
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44
defines security controls to protect payment card data throughout the transaction lifecycle,84 and
the Bank was required by contract with the CA EDD to “be certified as PCI DSS compliant.”85
Version 3.2.1 of the PCI DSS, updated in May of 2018, was the version in place when the
pandemic began in March 2020.86 Section 12.7 of the standards requires the screening of
personnel, and lists examples of the types of screening, including employment history, credit
history and reference checks. Contrary to the PCI DSS,

.
89.
With the onset of the pandemic,

.87 Given
the increased risk of security breaches, it should have been all the more important for the Bank to
perform other checks that remained available, such as employment and credit checks. But the

.
90.

.88 The

84 See Information Supplement: Protecting Telephone Based Payment Card Data, Version 3.0,
Protecting Telephone Based Payments Special Interest Group of the PCI Security Standards
Council at 1,
https://listings.pcisecuritystandards.org/documents/Protecting_Telephone_Based_Payment_Card
_Data_v3-0_nov_2018.pdf.
85 See Ex. 22 at 250, requirement 394.
86 Available at www.pcisecuritystandards.org.
87 See Ex. 93 at -517115.
88 See id.
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Bank

,89

.
91.
At the same time the Bank

.
92.
Those call centers already using or testing WFH were able to identify concerns
with maintaining the confidentiality of information. As a result, most call centers utilizing WFH
instituted rules such as i) requiring that calls be handled from a hard walled office with a door
that could be closed for privacy, ii) restricting cameras from the WFH work space, and iii)
ensuring staff followed a “clean desk” work policy where no paper or writing instruments were
allowed in the work area. Policies such as these have become standard WFH requirements in the
call center industry and are routinely documented in vendor contracts.
93.
The Bank

89 See Ex. 18 (Golden Tr.) 289:10-290:7.
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46
.90 When asked,

.91 Keeping other

.92 Despite claims
that

.93 In my experience, based on reviewing well

. In my opinion,

.
D.
The Bank’s Deliberate Understaffing Choice Harmed Cardholders While
Saving the Bank Money.
94.
The Bank’s EDD debit cardholders

. The share of cardholders calling the Claims call center who are
members of Plaintiffs’ Customer Service class and assert an injury from the Bank’s conduct

90 See e.g., Ex. 123; Ex. 152; Ex. 126; Ex. 135.
91 See Ex. 18 (Golden Tr.) 286:19-287:19.
92 See Ex. 18 (Golden Tr.) 285:3-289:2.
93 See Ex. 18 (Golden Tr.) 285:3-289:9.
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47
).94 This data is

,95

.
95.
Given no

.
96.
The Bank’s

.96 Under this structure, the
largest block of payable time is workload (the time agents spend processing calls). The second
largest block of payable time, for call centers providing industry-standard service, is agent idle
time (time CSRs are available and waiting for the next call to arrive).

94 See, e.g., Ex. 144 at -205620 (

).
95 See, e.g., Ex. 152 at -12841-42, sections 21.2 and 21.7, and Ex. 123 at -13135-36, sections
21.2 and 21.7.
96 See e,g, Ex. 128 at -90043 and Ex. 138 at -13090 defining a Paid Production Hour as

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48
97.
First,

.97
98.
Multiplying true caller demand by average handle time provides the total
workload hours that would have been charged to service these callers with industry-standard
performance levels. Those hours could be multiplied by the hourly rate paid to CSRs to obtain a

.
99.
Second,

. This
can be calculated
on a classwide basis, using the industry standard measure of the Erlang-C formula. The Erlang-C
formula is used in a variety of circumstances where demand or traffic varies over time (for
example, restrooms in a stadium), but is most commonly employed by call centers to estimate
staffing needs. The necessary inputs for performing this calculation

97 See Ex. 112 (2021 Decision-Makers’ Guide) at 46.
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49
.98 The requirement to build in
(and ultimately pay for) agent idle time in order to achieve contracted-for and industry-standard
ASA is a mathematical fact in call centers. Nonetheless, performance in the

.99

.
100.
The amount of necessary idle time can be calculated by applying the industry-
standard Erlang-C formula to half-hourly distinct call volume and handle time distributions
(together, call intensity) for an average day for each week. Based on call intensity, the Erlang-C
formula can be used to calculate the number of staff required to deliver an industry-standard
ASA for the interval. The difference between the total staffed hours and the workload (again, the
time agents spend processing calls) is the agent idle time. Summing the interval agent idle times
for the day and multiplying the total daily idle time by the number of work days in the week will
provide a total amount of required wait hours for the week. Multiplying the wait hours by the
hourly rate will provide

98 See Rahul Awati, Erlang C, TechTarget (accessed Aug. 22, 2024),
https://www.techtarget.com/searchunifiedcommunications/definition/Erlang-C (“Erlang C is a
traffic modeling formula, primarily used in call center scheduling to calculate delays and to
predict waiting times for callers. . . . It is widely considered a standard calculation for managing
call centers.”).
99 See Ex. 124

.
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50
VIII. CONCLUSION
101.
The Bank’s

, was inconsistent with industry
standards and caused substandard performance in its Claims call center.

was so
substandard that it subjected cardholders to wait times rarely, if ever, seen in the call center
industry.

Executed on August 29, 2024, at Collegeville, Pennsylvania.

_______________________________

Jay Minnucci

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Appendix A: Curriculum Vitae
Jay Minnucci

President, Service Agility, jaym@serviceagility.com
(267) 733-8778

Summary

Jay Minnucci is the President and Founder of Service Agility, a consulting and training
company dedicated to improving customer service and contact center operations. In this role,
he provides strategic and tactical guidance across all industries for enterprises that seek to
optimize customer interactions. His client list ranges from small start-up operations to large
Fortune 500 corporations. He is well-known throughout the industry as an accomplished
consultant, trainer, speaker and author on all subjects relevant to contact center best practices.

Experience

April 2008 – Present: Owner of Service Agility, Inc.

March 2000 – April 2008: Vice President of Consulting, International Customer
Management Institute (ICMI). Built the consulting division from the ground up, leading a
staff of 12. Furthered the ICMI brand through various speaking, training and writing
engagements.

October 1983 – March 2000: Various management and executive positions in the contact
center supporting the AARP Group Health Insurance Program. This operation was run by
Prudential Insurance from 1983 to 1996, when The Hartford took over.

Education

BBA from Temple University, May 1984, graduated Magna Cum Laude

Consulting Experience

Jay leads up to 20 consulting/training assignments a year in the United States and abroad,
including past projects in China, Australia, England, Canada, The Czech Republic, Portugal,
Malaysia, Singapore and Dubai. Some of the clients that Jay has worked with include:

Federal Reserve Bank
Gartner Group
Duke Energy
Hyatt
Discover Financial
Kaiser Permanente
BMW
Charles Schwab
Canon
Michigan BCBS
Wells Fargo
American Diabetes Assoc
Government of Australia Allstate
UBS
Vodafone
Thrift Savings Plan
United Healthcare
Speaking Engagements

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52
Past speaking engagements include the following:

• Annual Call Center Exhibit (ACCE) 2003 – 2008
• China Call Center Conference 2007
• Middle East Contact Center Forum 2013
• Help Desk Institute 2007, 2009, and 2011
• Contact Center Association Conference 2011 – 2013
• Contact Centre Association of Singapore Symposium – 2013
• J.D. Power Customer Service Conference 2013 and 2015
• NM Credit Union Association 2015, 2018, 2019 and 2022
• Avail Technologies Customer-Centric Services Summit, 2024

Training

Jay has provided training in both public and private venues on topics that include the
following:

• Crafting a Contact Center Strategy
• Contact Center Management Principles
• Enhancing Efficiency
• Workforce Management Principles
• Metrics and Objectives
• Managing a Small Contact Center

Writing

Jay is a member of the editorial board for the industry journal Contact Center Pipeline.
From 2010 to 2018, he wrote a popular monthly column for the Pipeline. He has been
published in many other journals as well, including Call Center Magazine, Customer
Management Insight, Foresight, Contact center Management Review, Business
Communications Review, and the International Journal of Contact centers. He has written
numerous articles for Service Agility's and ICMI’s websites, and was a contributor to the
latest edition of Contact Center Management on Fast Forward, by Brad Cleveland.

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Appendix B: Prior Publications (March 2014 to Present)
All of the articles listed below were published in Contact Center Pipeline, an industry
publication:
“A Second Chance”, March 2024
“Revisiting Schedule Adherence,” July 2019
“Taking a Deep Dive into FCR,” November 2018
“Survey Erosion,” July 2018
“Re-Gifting for 2018,” December 2017
“Consultative WFM,” November 2017
“What the Frontline Supervisor Survey Says,” October 2017
“The SBR Balancing Act,” September 2017
“Technology Worth Following,” August 2017
“Cost Efficient 2018,” July 2017
“Selling and Promoting the Contact Center,” June 2017
“Nailing Priorities,” May 2017
“Optimizing the Exceptions,” April 2017
“Valuing the Agent,” March 2017
“Balancing the Contact Center Brain,” February 2017
“Looking Ahead to 2020,” January 2017
“Re-Gifting for 2017,” December 2016
“A Culture of Trust,” November 2016
“The Moment of Truth,” October 2016
“First Step: Showing Up,” September 2016
“Getting Closer to the Customer,” August 2016
“The Work Environment 2016,” July 2016
“Five Ways to Improve Engagement,” June 2016
“When Dysfunction Strikes,” May 2016
“Conversing or Transacting?,” April 2016
“The Profession of Contact Center Management,” March 2016
“The Phone System App,” February 2016
“Accountability in the Center,” January 2016
“Re-Gifting for 2016,” December 2015
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“Welcome To Our Contact Center!,” November 2015
“Coaching: The Radical Next Steps,” October 2015
“Speech Rec…or…Speech Wreck?,” September 2015
“Four Ways to Expand the Value of Quality Monitoring,” August 2015
“Outbound Calling in Today's Contact Center,” July 2015
“Prepping for Next Year's Budget,” June 2015
“Setting Service Level Objectives,” May 2015
“Top Performer Modeling,” April 2015
“Some Love for ANI,” March 2015
“To NPS or Not NPS,” February 2015
“The (Near) Death of Workforce Management,” January 2015
“Re-Gifting for 2015,” December 2014
“Organizational Structure: Survey Highlights,” November 2014
“The Here and Now,” October 2014
“Agent Attrition: Time for a Change,” September 2014
“Long Term Cost Management,” August 2014
“Video in the Contact Center,” July 2014
“The Outsourcing Decision,” June 2014
“Speech Analytics and Quality Monitoring,” May 2014
“Proactive Do's and Don'ts,” April 2014
“Training Frontline Leaders,” March 2014

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Appendix C: Prior Testimony (January 2020 to Present)
Alorica v. Sam’s Club, JAMS, JAMS Reference No. 1200056432
• Deposed, May 7, 2021.
• Testified, September 7, 2021.

RDI v. Dentalplans.com, 17th Judicial Circuit of the County of Broward, Florida, Case No.
CACE 18-29136
• Deposed, October 21, 2021.

Genesys v. Talkdesk, United States District Court for the Southern District of Indiana, Case No.
1:19-cv-00695-TWP-DML
• Deposed, June 3, 2021.
• Testified February 28, 2023

Skyview Capital and Continuum Global Services v. Conduent, Supreme Court of the State of
New York, County of New York, Case No. 650761/2020
• Deposed, May 25, 2023

Case 3:21-md-02992-GPC-MSB Document 386-3 Filed 12/02/24 PageID.20506
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Appendix D: Materials List
In addition to sources cited in the Report and accompanying Exhibits, I considered the following
in developing my opinions:
Declarations and Deposition Transcripts and Accompanying Exhibits
Declaration of William Golden, April 20, 2021
Deposition of William Golden, February 22, 2024
Deposition of Shane Daniels, February 6, 2024
Call Center Industry Documents and Other External Sources
Avaya Call Management System Database Items and Calculations, Release 18, July 2016
The 2021 U.S. Contact Center Decision-Makers Guide, ContactBabel, 13th Edition, 2021
The 2023 U.S. Contact Center Decision-Makers Guide, ContactBabel, 15th Edition, 2023
Payment Card Industry Data Security Standard, Requirements and Security Assessment
Procedures, Version 3.2.1, May 2018
Protecting Telephone-Based Payment Card Data, PCI Security Standards Council, Version 3.0,
November 2018
https://investor.bankofamerica.com/profile as of February 26 2024
https://www.bankofamerica.com/deposits/rebate-cards/commercial-prepaid-card/ as of February
26 2024
Support Technology without an Analyst Is Like a Car without a Driver, Lori Bocklund, CONTACT
CENTER PIPELINE (May 2021)
Metrics Roundup, Susan Hash, CONTACT CENTER PIPELINE (Oct. 2019)
cc-Modeler Lite, Erlang-C calculator by KoolToolz
Pleadings and Other Case Documents
First Amended Master Consolidated Complaint, June 13, 2023
Consent Order in the Matter of: Bank of America, N.A., Consumer Financial Protection Bureau,
File No. 2022-CFPB-0004, July 14, 2022
Bank of America’s Responses and Objections to Plaintiff Yick’s Fifth Set of Interrogatories,
February 2, 2024

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Documents Produced by Defendant (1 of 3)
BANA_EDD_MDL-00001502
BANA_EDD_MDL-00001935
BANA_EDD_MDL-00002018
BANA_EDD_MDL-00012792
BANA_EDD_MDL-00012793
BANA_EDD_MDL-00012797
BANA_EDD_MDL-00012800
BANA_EDD_MDL-00012803
BANA_EDD_MDL-00012816
BANA_EDD_MDL-00012875
BANA_EDD_MDL-00013074
BANA_EDD_MDL-00013082
BANA_EDD_MDL-00013086
BANA_EDD_MDL-00013096
BANA_EDD_MDL-00013110
BANA_EDD_MDL-00013111
BANA_EDD_MDL-00013174
BANA_EDD_MDL-00019264
BANA_EDD_MDL-00019266
BANA_EDD_MDL-00019362
BANA_EDD_MDL-00019373
BANA_EDD_MDL-00019476
BANA_EDD_MDL-00019555
BANA_EDD_MDL-00021102
BANA_EDD_MDL-00025811
BANA_EDD_MDL-00027536
BANA_EDD_MDL-00028134
BANA_EDD_MDL-00038694
BANA_EDD_MDL-00056667
BANA_EDD_MDL-00056832
BANA_EDD_MDL-00057091
BANA_EDD_MDL-00060229
BANA_EDD_MDL-00060339
BANA_EDD_MDL-00060417
BANA_EDD_MDL-00061383
BANA_EDD_MDL-00061582
BANA_EDD_MDL-00062838
BANA_EDD_MDL-00065924
BANA_EDD_MDL-00065985
BANA_EDD_MDL-00066408
BANA_EDD_MDL-00067169
BANA_EDD_MDL-00067224
BANA_EDD_MDL-00067590
BANA_EDD_MDL-00067592
BANA_EDD_MDL-00068789
BANA_EDD_MDL-00068790
BANA_EDD_MDL-00068834
BANA_EDD_MDL-00069576
BANA_EDD_MDL-00076747
BANA_EDD_MDL-00090023
BANA_EDD_MDL-00090034
BANA_EDD_MDL-00090040
BANA_EDD_MDL-00090498
BANA_EDD_MDL-00090577
BANA_EDD_MDL-00090657
BANA_EDD_MDL-00091919
BANA_EDD_MDL-00091923
BANA_EDD_MDL-00092646
BANA_EDD_MDL-00093262
BANA_EDD_MDL-00093422
BANA_EDD_MDL-00094056
BANA_EDD_MDL-00095514
BANA_EDD_MDL-00100634
BANA_EDD_MDL-00101725
BANA_EDD_MDL-00102812
BANA_EDD_MDL-00103075
BANA_EDD_MDL-00103150
BANA_EDD_MDL-00103312
BANA_EDD_MDL-00104599
BANA_EDD_MDL-00105110
BANA_EDD_MDL-00105477
BANA_EDD_MDL-00106092
BANA_EDD_MDL-00106236
BANA_EDD_MDL-00106487
BANA_EDD_MDL-00107706
BANA_EDD_MDL-00108517
BANA_EDD_MDL-00109298
BANA_EDD_MDL-00115804
BANA_EDD_MDL-00118438
BANA_EDD_MDL-00118460
BANA_EDD_MDL-00126413
BANA_EDD_MDL-00126428
BANA_EDD_MDL-00126635
BANA_EDD_MDL-00127312
BANA_EDD_MDL-00127367
BANA_EDD_MDL-00127457
BANA_EDD_MDL-00127480
BANA_EDD_MDL-00127980
BANA_EDD_MDL-00127988
BANA_EDD_MDL-00130192
BANA_EDD_MDL-00130232
BANA_EDD_MDL-00140261
BANA_EDD_MDL-00140417

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Documents Produced by Defendant (2 of 3)
BANA_EDD_MDL-00140419
BANA_EDD_MDL-00140627
BANA_EDD_MDL-00140691
BANA_EDD_MDL-00141482
BANA_EDD_MDL-00141458
BANA_EDD_MDL-00141618
BANA_EDD_MDL-00141919
BANA_EDD_MDL-00142001
BANA_EDD_MDL-00142490
BANA_EDD_MDL-00142764
BANA_EDD_MDL-00143155
BANA_EDD_MDL-00145888
BANA_EDD_MDL-00148891
BANA_EDD_MDL-00155082
BANA_EDD_MDL-00162954
BANA_EDD_MDL-00163453
BANA_EDD_MDL-00171905
BANA_EDD_MDL-00172236
BANA_EDD_MDL-00172538
BANA_EDD_MDL-00172855
BANA_EDD_MDL-00173603
BANA_EDD_MDL-00173993
BANA_EDD_MDL-00175335
BANA_EDD_MDL-00177361
BANA_EDD_MDL-00182381
BANA_EDD_MDL-00187216
BANA_EDD_MDL-00187433
BANA_EDD_MDL-00188414
BANA_EDD_MDL-00188572
BANA_EDD_MDL-00191003
BANA_EDD_MDL-00198653
BANA_EDD_MDL-00199253
BANA_EDD_MDL-00200185
BANA_EDD_MDL-00206316
BANA_EDD_MDL-00210000
BANA_EDD_MDL-00217469
BANA_EDD_MDL-00217549
BANA_EDD_MDL-00218450
BANA_EDD_MDL-00225648
BANA_EDD_MDL-00234529
BANA_EDD_MDL-00235537
BANA_EDD_MDL-00235706
BANA_EDD_MDL-00235714
BANA_EDD_MDL-00236111
BANA_EDD_MDL-00236846
BANA_EDD_MDL-00236848
BANA_EDD_MDL-00236865
BANA_EDD_MDL-00240054
BANA_EDD_MDL-00243363
BANA_EDD_MDL-00246363
BANA_EDD_MDL-00261052
BANA_EDD_MDL-00261375
BANA_EDD_MDL-00261795
BANA_EDD_MDL-00261884
BANA_EDD_MDL-00262582
BANA_EDD_MDL-00263582
BANA_EDD_MDL-00263806
BANA_EDD_MDL-00288598
BANA_EDD_MDL-00288637
BANA_EDD_MDL-00288640
BANA_EDD_MDL-00290235
BANA_EDD_MDL-00293070
BANA_EDD_MDL-00314421
BANA_EDD_MDL-00315852
BANA_EDD_MDL-00352749
BANA_EDD_MDL-00352985
BANA_EDD_MDL-00355584
BANA_EDD_MDL-00356316
BANA_EDD_MDL-00358108
BANA_EDD_MDL-00359360
BANA_EDD_MDL-00359361
BANA_EDD_MDL-00359362
BANA_EDD_MDL-00359363
BANA_EDD_MDL-00359364
BANA_EDD_MDL-00359365
BANA_EDD_MDL-00368111
BANA_EDD_MDL-00372269
BANA_EDD_MDL-00373514
BANA_EDD_MDL-00374770
BANA_EDD_MDL-00375717
BANA_EDD_MDL-00376191
BANA_EDD_MDL-00377118
BANA_EDD_MDL-00379986
BANA_EDD_MDL-00379991
BANA_EDD_MDL-00382181
BANA_EDD_MDL-00383694
BANA_EDD_MDL-00405979
BANA_EDD_MDL-00424944
BANA_EDD_MDL-00436069
BANA_EDD_MDL-00438429
BANA_EDD_MDL-00455530
BANA_EDD_MDL-00455608
BANA_EDD_MDL-00455649
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Documents Produced by Defendant (3 of 3)
BANA_EDD_MDL-00482670
BANA_EDD_MDL-00491397
BANA_EDD_MDL-00491410
BANA_EDD_MDL-00498025
BANA_EDD_MDL-00503278
BANA_EDD_MDL-00510120
BANA_EDD_MDL-00517105
BANA_EDD_MDL-00522406
BANA_EDD_MDL-00548592
BANA_EDD_MDL-00549619
BANA_EDD_MDL-00589505
BANA_EDD_MDL-00616368
BANA_EDD_MDL-00616664
BANA_EDD_MDL-00618616
BANA_EDD_MDL-00639950
BANA_EDD_MDL-00640402
BANA_EDD_MDL-00641997
BANA_EDD_MDL-00643469
BANA_EDD_MDL-00648284
BANA_EDD_MDL-00657359
BANA_EDD_MDL-00657367
BANA_EDD_MDL-00657370
BANA_EDD_MDL-00659985
BANA_EDD_MDL-00662478
BANA_EDD_MDL-00669718
BANA_EDD_MDL-00678495
BANA_EDD_MDL-00681274
BANA_EDD_MDL-00681616
BANA_EDD_MDL-00694815
BANA_EDD_MDL-00694825
BANA_EDD_MDL-00694835
BANA_EDD_MDL-00694845
BANA_EDD_MDL-00694847
BANA_EDD_MDL-00694848
BANA_EDD_MDL-00694849
BANA_EDD_MDL-00697114
BANA_EDD_MDL-00697318
BANA_EDD_MDL-00712063
BANA_EDD_MDL-00718992
BANA_EDD_MDL-00719114
BANA_EDD_MDL-00719115
BANA_EDD_MDL-00719116
BANA_EDD_MDL-00643363
BANA_EDD_MDL-00002286
BANA_EDD_MDL-00153667
BANA_EDD_MDL-00061799
BANA_EDD_MDL-00107356
BANA_EDD_MDL-00205620
BANA_EDD_MDL-00859710

Also, the excel file titled “TTEC Servicing and Fraud Call Metrics 2020-2021” (no Bates No.)

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Appendix E: Survey Results, The 2021 US Contact Center Decision Makers’ Guide, Page
46
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Appendix F:
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Appendix F:
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Appendix G:

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Appendix G:
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Exhibit 3 — In re Bank of America California Unemployment Benefits Litigation (Dkt. 386-3, S.D. Cal. No. 3:21-md-02992)

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