WEBINAR: COVID-19 AND IMPACT ON THE US FINANCIAL SYSTEMPandemic Modelling and Consumer Credit

April 22nd, 2020

Please note that this session was held at a particular point in time (Wednesday April 22,2020, 4pm-5pm EDT), and in light of the rapidly evolving Covid-19 situation, it is possible these discussions are no longer accurate after that date.

CONFIDENTIALITYOur clients’ industries are extremely competitive, and the maintenance of confidentiality with respect to our clients’ plans and data is critical. Oliver Wyman rigorously applies internal confidentiality practices to protect the confidentiality of all client information.

Similarly, our industry is very competitive. We view our approaches and insights as proprietary and therefore look to our clients to protect our interests in our proposals, presentations, methodologies and analytical techniques. Under no circumstances should this material be shared with any third party without the prior written consent of Oliver Wyman.

© Oliver Wyman

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WEBINAR AGENDA

01 Epidemiologic Perspectives 10 min

02 Pandemic Navigator 15 min

03 Policy Response Update and Macro Roll-up 5 min

04 Consumer Credit Risk and COVID-19 10 min

05 Additional Q&A Remaining time

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OUR PANELISTS

Til SchuermannPartner & Co-Head – Risk & Public PolicyNew York

Helen LeisPartner, Health & Life SciencesNew York

Deepak KollaliPartner & Co-Head – Risk & Public PolicyNew York

Ugur KoyluogluPartner and Vice Chairman, Financial Services AmericasNew York

EPIDEMIOLOGY, SUPPRESSION SCENARIOS, AND ‘BACK TO WORK’Panelist: Helen Leis

01

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EPIDEMIOLOGY AND SUPPRESSION MEASURES SUMMARY

• The epidemiology of the novel coronavirus impacts containment efforts

– R0 estimates range between 2 and 5.7, meaning each infected individual infects at least 2, and up to 5-6 others

– Median 5.5 day incubation period (from exposure to symptom onset) is longer than that of a disease like the flu, which means a longer window when unsuspecting individuals can infect others

– Studies suggest that anywhere between 18% and 60% of infected individuals remain asymptomatic for the duration of the disease, further complicating containment efforts

– Individuals have been shown to test positive and demonstrate viral shedding for 6-12 days (or more) post resolution of symptoms, creating a large window during which an individual is contagious

• Several capabilities can enable countries to relax suppression and avoid a severely damaging second wave– Healthcare system capacity recovered to the extent that normal care can be provided without overburdening

facilities or personnel– The capacity to do extensive testing, both for presence of the virus as well as for antibodies to indicate who may

have already had the disease, in order to manage the spread of the disease in a controlled manner as we try to begin opening parts of the economy

– Contact tracing, to allow a more surgical approach to managing the disease– A centralized surveillance system, at the regional or national level, that will provide an early warning and allow

quick management of new outbreaks

• Preliminary analyses suggest that parts of the US and much of Europe is several weeks to a month from scaling these capabilities

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COVID-19 WILL EXERT ITS INFLUENCE ON OUR ECONOMY FOR MANY MONTHS AHEAD

~2 Months 12+ MonthsInitial Outbreak Long Haul of Suppression

Case

Gro

wth

per

Day

Therapeutic breakthroughs (treatment, vaccine) and scaled public health tools (diagnostic

testing, contact tracing with selective quarantine, national

surveillance system) allow return to New Normal with emphasis on immediate Containment at

first sign of new outbreaks

• Cycles of relax/tighten suppression measures. Social distancing acts as the only ‘brake’ and we learn from each cycle what has greater/lesser impact on virus spread

• Ramp up diagnostic and serology testing to have sensing posts for resurgence of virus as restrictions are relaxed - The more scaled and sophisticated the public heath infrastructure, the less you have to rely on blunt instruments of stay home orders

Phase 1 Phase 2

Containment

Phase 3

Miti

gatio

n/Ec

onom

y • Closure of non-essential businesses

• Community-wide stay-at-home mandates

• Widespread remote work • Border closures and travel

restrictions

• Gradually reopen some business (e.g., retail / restaurants/ manufacturing with social distancing and cleaning/protection protocols)

• Strict quarantine guidelines for confirmed cases, close associates and travellers• Stay-at-home order for at-risk people• Remote work and mask-wearing still the norm• No large gatherings (e.g. no events >50 people) so churches, sports,

entertainment venues remain closed• Travel to / from hot spots restricted

• All businesses re-open, under mandated safety protocols

• Stay-at-home reinstated in areas with renewed outbreaks

• Prevalent use of vaccines, perhaps annually

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WHERE ARE WE NOW? EARLY CONTAINMENT MEASURES APPEAR TO HAVE WORKED

0

500

1,000

1,500

2,000

2,500

2/27 3/5 3/12 3/19 3/26 4/2 4/9 4/16 4/23 4/30 5/7 5/14 5/21

ItalySpain

UK

France*

Germany

Lockdown timingUK 3/24

US shelter at home advisories vary by state, starting 3/16 (SF)

IT 3/10

DE,3/22

ES 3/14

FR 3/17

US

*Note: Projections for France are abbreviated due to high volatility in recently reported cases

OW COVID-19 Projections (select countries) – Active cases per millionApril 20, 2020

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WHERE ARE WE NOW? EARLY CONTAINMENT MEASURES APPEAR TO HAVE WORKED

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

2/27 3/5 3/12 3/19 3/26 4/2 4/9 4/16 4/23 4/30 5/7 5/14 5/21

Shelter in placetiming

DFW, NYC, Seattle 3/22

SF3/16

CHI3/20 Detroit, 3/23

Boston, 3/24

NYC

Boston

DetroitChicagoSeattleSF, DFW

OW COVID-19 Projections (select MSAs) – Active cases per millionApril 20, 2020

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HOW LONG SHOULD WE CONTINUE WITH CURRENT CONTAINMENT MEASURES? A number of factors impact how quickly a geography can consider it ‘safe’ to reopen

Local pandemic progression examples1

0

8k

2k

4k

6kWuhan beginning to relax suppression ~10 weeks post peak

Hubei ~ 7-8 weeksSharp peak of very high case load, sharp decline

Italy ~ 7+ weeksSharp incline, just now beginning

to decline from peak

Norway ~ 4+ weeksCase growth flattened

immediately

Local pandemic progression examples1

8k

0

2k

6k

4k Wuhan beginning to relax suppression ~10 weeks post peak

Hubei ~ 7-8 weeksSharp peak of very high case load, sharp decline

Italy ~ 7+ weeksSharp incline, just now beginning

to decline from peak

Norway ~ 4+ weeksCase growth flattened

immediately

0k

5k

10k

Boston ~ 8+ weeksGradual peak; appears to

be tapering off

DFW ~ 5+ weeksCase growth flattened

immediately

New York City ~ 6+ weeksSharp incline, just now beginning to

decline from peak1. Example charts are derived from real data as reported by Johns Hopkins University spanning 01/22/2020-04/01/2020. Bars represent new confirmed cases by day. Grey arrows symbolize time span

from ramp-up of new case load to point of control and are approximate

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Controlled outbreak

Scenario 4

Minimally invasive measures (e.g. mask wearing, contact tracing) can be successful

Scenario 1

Moderate, on and off again partial social distancing

measures can be successful

Scenario 2

Full, blunt “lockdowns” are needed to be successful

Scenario 3

Virus resurges Maintain course & monitor

Are economic consequences acceptable?

No, approach proves too difficult to

operationalize or doesn’t work well

enough

SOCIETIES AROUND THE WORLD WILL BE LOOKING TO CONTAIN THE PUBLIC HEALTH DISASTER WHILE MINIMIZING IMPACT ON THE ECONOMY UNTIL A VACCINE EMERGES

Stylized decision tree for public policy actions to contain the epidemic

No, moderate measures prove

ineffective

Yes

Yes

No

Yes

Yes

No

Decision criteria will be impacted by political factors, virus characteristics,

and breakthroughs in therapeutics/vaccines yet unknown

We are continuously monitoring global government responses and results across the world, incorporating them into our COVID-19 Pandemic Navigator, and creating sophisticated “what-if” scenarios

Success in each scenario defined as keeping projected active cases below hospital system capacity

12© Oliver Wyman

Minimally invasive measures Moderate social distancing Blunt lockdowns Controlled outbreak

• We sacrifice privacy and some freedoms, but suppress the virus

• Regional borders remain controlled/closed to avoid contagion

• We have few slower-growth outbreaks over the next 18+ months

• When case counts reach a critical threshold against hospital capacities, stricter lockdowns imposed

• We will periodically be in ‘today’s world’ over the next 18+ months

• Fiscal and monetary stimulus measures expand significantly to account for future outbreaks

• The virus spreads quickly through the general population

• Potential for future outbreaks depends significantly on the immunity of those previously infected

Targets for no future outbreaks occur, and we are

able to maintain a reasonable level of economic activity

Economic impacts are significant but lower than that

with minimally invasive measures

Impact on most affected sectors of the economy will be

deep and long-lasting

Immediate impact on economy is severe, but the pandemic is

relatively short-lived

321 4

SMART SCENARIOS FOR THE FUTURE COURSE OF THE EPIDEMIC CAN BE DEVELOPED AT COUNTRY AND STATE LEVEL AND USED TO PROJECT CONSEQUENCES OF POLICY AND BUSINESS CHOICES

Lockdown

Outbreak

13© Oliver Wyman

SCENARIOS SHOULD ACCOUNT FOR RELATIVE ‘BANG FOR THE BUCK’ ECONOMICALLY…

$81$240 $376

$887$1,120

$2,832

Prof

essio

nal

serv

ices

$663

$352

Reta

il tr

ade

$1,250$488$1,660

FIRE

1

$1,278

$1,492

$1,720

$862

Man

ufac

turin

g

$169

Agric

ultu

re

$756

Heal

thca

re

$685$532

$746$445

Who

lesa

le tr

ade

$311$685

$74

$989

Info

rmat

ion

$721

$4,492

Cons

truc

tion

$335

$2,742

Tran

spor

tatio

n /

war

ehou

sing

Food

, bev

erag

e, &

ho

spita

lity

Oth

er

$287

$320

Util

ities

Min

ing

Educ

atio

n

Ente

rtai

nmen

t &

recr

eatio

n

$2,360

$1,618

$1,173$457

$264

$640

$236

Small businessesLarge businesses

1. FIRE includes Finance, Insurance, real estate, and rental Source: US Bureau of economic analysis; US small business administration

United States GDP by Industry, 2019$ BN

How disrupted by suppression measures

Very disrupted: business is nonexistent or severely disrupted

Somewhat: Most can at least continue a large portion of their businessLess: Nearly all can continue the much of their business

Healthcare sector has been negatively impacted by the replacement of high margin

elective care with lower margin COVID care

14© Oliver Wyman

… AS WELL AS GETTING PEOPLE BACK TO WORK.

8.2

10.0

0.70.9

Heal

thca

re

11.3

0.9

6.9

1.5

5.58.3

Man

ufac

turin

g

6.9

1.73.84.5

5.9

Oth

er re

tail

trad

e

Food

, bev

erag

e,

& h

ospi

talit

y

Tran

spor

tatio

n &

war

ehou

sing

Who

lesa

le tr

ade

5.2

Prof

essio

nal s

ervi

ces

3.0

5.5

3.4

4.9

12.4

FIRE

1

1.9

Oth

er

2.6

1.3

Cons

truc

tion

5.3

1.02.4 1.2

1.8

3.31.9

6.2

1.8

Educ

atio

n

2.70.9

Min

ing

Info

rmat

ion 1

Reta

il tr

ade:

Gene

ral m

erch

andi

se

Reta

il tr

ade:

Food

& b

ever

age

0.8 0.4

3.3

Agric

ultu

re

0.4

Util

ities

18.2

8.9 8.47.2

Ente

rtai

nmen

t &re

crea

tion

5.1

3.32.7

2.01.2 0.7 0.5

5.7

United States Employment by Industry, 2018Full Time Employee equivalents, MM

Small businessesLarge businesses

1. FIRE includes Finance, Insurance, real estate, and rental Sources: 1. US Bureau of economic analysis; 2. US small business administration

How disrupted by suppression measures

Very disrupted: business is nonexistent or severely disrupted

Somewhat: Most can at least continue a large portion of their businessLess: Nearly all can continue the much of their business

Healthcare sector has been negatively impacted by the replacement of high margin

elective care with lower margin COVID care

(61) (18) (417) (52) (30) (1) (29) 1 (5) (24) (10) (6) 2 (8) (7) 1

Job Changes, March Jobs Report

15© Oliver Wyman

~2 Months 12+ Months

Case

Gro

wth

per

Day

THE LONG HAUL OF SUPPRESSION IS MARKED BY PERVASIVE RISK OF DISRUPTION

Seemingly “random” regional

shutdowns

20%+ absenteeism,

with some employees severely ill

Significant mental health and wellbeing challenges for

employees

Unequal economic

impact across sectors

1 2 3 4

HALLMARKS OF THE ROAD AHEAD

Current Peak Long Haul of SuppressionSystematic, scaled, and sophisticated tools to enable near real-time

monitoring of the disease become well-established

Initial period of volatility when reopening begins, before testing and monitoring

mechanisms are perfected

Changed customer behaviors (perhaps

permanently)

5

16© Oliver Wyman

‘CRISIS MANAGEMENT’ ISN’T ENOUGHCritical considerations/impacts Key questions

01 Seemingly “random” regional shutdowns

• Supply chains and facility locations

• Travel risks

• Customer demand

• Do I have adequate insights to anticipate risks and act early (vs. just react like in Phase 1)?

• Have I begun to diversify my supply chain and distribution channels?

• Do I have adequate resiliency plans, including for locations not impacted in Phase 1?

• Do I understand my financial risks at scale?

0220% absenteeism, with some employees severely ill

• Staffing challenges and need for redundancy

• Adequate protection, and the company’s role in monitoring

• Scalability of policies and benefits

• Whom do I allow back onsite and when?

• Do I know where my “hot spots” for employee risk are?

• Do I have flexible staffing and executive coverage plans?

03Significant mental health and wellbeing challenges for employees

• Cultural fractures as employees cope with social isolation, childcare responsibilities, health concerns, and financial stresses

• Video, email, and calendar overload

• Reduced productivity and impaired decision-making

• Have I invested in culturally-appropriate, virtual mental health support for my employees? Are they using it?

• Are current work-from-home support mechanisms durable for 12-15 months?

04 Unequal economic impact across sectors

• Significant small business failure

• Some sectors never bounce back

• New services and categories arise as customer needs are shaped by COVID-19

• How are my customers and business partners affected, and how will that impact my business?

• How has strategic control in my sector shifted?

• Do I have strategic opportunities for partnership or M&A?

05Changed customer behaviors (perhaps permanently)

• Preference for digital vs. physical

• Generational risk aversion

• Reduced trust in institutions

• Doubling down on local experiences

• Do I understand how customer and employee perceptions are like to shift?

• What are the opportunities for my business?

• What are the risks for my business?

PANDEMIC NAVIGATORPanelist: Ugur Koyluoglu

02

18© Oliver Wyman

OVERVIEW OF OLIVER WYMAN’S PANDEMIC NAVIGATOR

Supports private and public sector clients

• Draws on expertise from our Health & Life Sciences and Financial Services practices

• Underlying models are physics-informed, data-driven yet causally confirmed and use-case specific

Projects detected and undetected cases under different containment choices

• Estimates future outcomes for both Detected (tested and officially confirmed) and Undetected (e.g. asymptomatic) cases

• Compartmental model covers 40 countries and the 50 US states, updated continuously for emerging data

Evidence-based causal links• Linkages with mobility and government response – core model index

compared to Google’s Community Mobility indices as well as Oxford’s Government Stringency Index

Generates 18-36 month scenarios linked to underlying epidemiology and suppression

• Primarily descriptive in nature, rather than ‘predictive’

• Validated via near-term predictive powers for a given strategy – if the model doesn’t give sensible forecasts for the next 30 days (given a set of assumptions) then I’m less likely to trust it

Economic impacts by sector modelled for scenarios

• Health outcomes are fed into modules which estimate the economic impacts on 40+ sectors of the economy

19© Oliver Wyman

Google Mobility Indices reveal what has changed in movement activity; Oliver Wyman COVID-19 transmission rate measure confirms that social distancing worked in reducing spread of COVID-19 in confirmed/detected cases

0

0.1

0.2

0.3

0.4

0.5

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

10

Transit Stations -- Mobility Index Change vis-à-vis Baseline

OW Covid-19 Transmission Rate Based on Reported Universe (5-Day Average -- RHS)

Mobility Index% change compared to baseline

OW Covid-19 Transmission Rate Based on Reported Universe

5-day average

Grey line shows index data from Google showing drop in mobility through Transit stations in Italy following lockdown measures

Red line shows OW model for COVID transmission intensity. Our model links policy choices and impact on interaction intensity to understand choices in certainty of containment vs economic impact

OUR MODEL IS PHYSICS-INFORMED, DATA-DRIVEN YET CAUSALLY CONFIRMED (1/2)We have linked our transmission rate model to independent, observable metrics for human interaction

Example: Italy

20© Oliver Wyman

0

20

40

60

80

100

0.00

0.10

0.20

0.30

0.40

0.50

5-Day Moving Average Beta (Left Handside) Stringency Index - 7 Days Earlier (Right Handside)

Beta Values Stringency Index

Example: Italy

OUR MODEL IS PHYSICS-INFORMED, DATA-DRIVEN YET CAUSALLY CONFIRMED (2/2)For example, the transmission rate model has been linked to the Oxford University Government Response Stringency Index

21© Oliver Wyman

OUR PANDEMIC NAVIGATOR CAPABILITY PROVIDES THE BASIS FOR MAXIMIZING MANAGEMENT LEAD TIME AND EFFECTIVENESS DURING THE PANDEMIC

Time and size of the next peak

1

Maximizing lead-time

Predicting policy failure

Scenario generationand sensitivity testing

capabilities

2

3

4

1 City X or Country Y is experiencing a lockdown, when will be the peak level for daily New Cases?

What will be the peak level for daily New Cases?

Will local hospital capacity be enough?

2 Providing real-time (daily updated) predictions of the duration of the next lockdown to maximize lead-time for businesses

3 Projecting where containment policy choices in City X or Country Y will likely fail and result in either a bigger peak or another near-term lockdown and loss of confidence

4 Providing a coherent, consistent set of planning scenarios which evolve as data emerges over coming weeks and months – enabling robust contingent action plans

Sensitivity tests with respect to parameters to support the comfort level in decision making

22© Oliver Wyman

OUR MODELS HAVE BEEN GENERATING STABLE AND ACCURATE RESULTS. WE TRACK STATISTICAL TESTS EVERY DAY - RESULTS FOR NEW YORK STATE 4/10/2020

Forecasted trajectories for Confirmed Cases from yesterday (T0) and earlier projections from the previous 7 days

Forecasted trajectories for New Cases

Out-sample test results comparing Actuals 4/9/2020 with historically calibrated versions from the past

Forecast trajectories for Active Cases (confirmed-death-recovered)

Past predictions have been highly accurate

Forward projections of new cases fall exhibit high stability

Active cases are core driver of hospitalization rate and ICU needs

Ultimate confirmed cases fall within a stable range of estimates.

1. Time and size of the peak

23© Oliver Wyman

OUR PROJECTIONS ARE GRANULAR AND ALLOWS FOR SOPHISTICATED DECISION-MAKING – RESULTS FOR UNITED STATES AT COUNTY LEVEL 4/17/2020

Source: Oliver Wyman Pandemic Navigator

Days from April 17, 2020 until county reaches 14-Day downward trajectory in New COVID-19 cases

2. Maximizing lead time

24© Oliver Wyman

WE KNOW SOCIAL DISTANCING POLICIES WORK. BUT HOW WILL INFECTION RATE CHANGE WHEN GOVERNMENT / STATE POLICIES ARE LIFTED?

0.00

0.10

0.20

0.30

0.40

3/2/2020 3/9/2020 3/16/2020 3/23/2020 3/30/2020 4/6/2020 4/13/2020 4/20/2020 4/27/2020 5/4/2020 5/11/2020 5/18/2020 5/25/2020

5 Day Moving Average Transmission Rate for Italy

Public transportation opens

Schools open

Schools and workplaces open?

3/20: Reduction of public transport by 75%, but remain operational throughout the country

3/10: Countrywide lockdown

3/4: Closure of all schools and universities

1/30: Barring of all commercial flights to and from China, Hong Kong, Macau and Taiwan1/31: Declaration of state of emergency2/23: Cancellation of public events in targeted municipalities and restrictions on entering and leaving these municipalities

3. Predicting policy failure

25© Oliver Wyman

OUR SCENARIO GENERATION AND ANALYIS CAPABILITY COVERS A HOST OF SCENARIOS

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21 Jun 21

U.S. – Active CasesU.S. – New Cases

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21 Jun 21

4. Smart scenarios

Example Scenario1. Infection rate managed for a while, but not until the end of summer2. The second peak is lower3. No seasonality is experienced4. Asymptomatic cases contribute to broader immunity5. Vaccination becomes available July 2021

26© Oliver Wyman

PRIVATE SECTOR PUBLIC SECTOR

More targetedpolicy responseDesign-led anddata-driven approach

Assessing hospital capacityInitial use case

Monitoring key metricsUnderstandingthe impact of decisions

PANDEMICNAVIGATOR

Decision support toolsControl tower

COVID strategy operational delivery Models, processes, capacity

Challenge to macroeconomic viewsMore granular approach

OLIVER WYMAN HAS DEVELOPED A FULLY INTEGRATED “ANALYTICAL STACK” WHICH CONNECTS COVID SCENARIOS THROUGH TO ECONOMIC AND BUSINESS IMPACTS

Epidemiology (by country)

Industry Earnings (by sector)

Fiscal/Monetary Stimulus

Risk/Loss Transmission

Banking/Insurance/Funds/PE

Lockdown Patterns

Please visit the Oliver Wyman Coronavirus Hub for more information on the Pandemic Navigator.https://www.oliverwyman.com/our-expertise/insights/2020/apr/covid-19-pandemic-navigator.html

POLICY RESPONSE UPDATE AND MACRO ROLL-UPPanelist: Til Schuermann

03

28© Oliver Wyman

• Worker protection and support like improved/extended unemployment

• Credit support for business, especially SMEs, through direct grants, subsidized credit

• Targeted support to specific industries (e.g. airlines)

01Fiscal response on both sides of the Atlantic has been massive, on the order of 6–10+% of GDP

02Central bank actions are exceeding those from the financial crisis

03Banks remain central to effective transmission of monetary and fiscal policy

• Central banks have taken many programs from the financial crisis off the shelf

• Significant intervention to support liquidity and credit formation

• ….. in the face of interest rates that are already near or below zero

• In financial crisis they were the problem, now they need to be part of the solution

• While in better shape than 2007, some systems are fitter than others….

FISCAL & CENTRAL BANK RESPONSE DESIGNED TO BRIDGE OVER THE WORSTHow long should the bridge be, and what’s on the other side?

Last updated: 4/21/2020

29© Oliver Wyman

March 27

CARES Act is signed into law, with $349 B for PPP

April 10

SBA begins accepting apps for contractors and self-employed

April 9

Treasury releases app for non-banks; Fed announces PPP loans will have a risk weight of 0% for capital requirements, and releases term sheet on facility to take PPP loans off of lender books

April 3

PPP goes live; SBA publishes affiliation guidance; $5.4 B in

loans processed, mostly by

community banks

April 11

Square, Intuit and PayPal approved as non-bank PPP lenders, with more to follow

April 14

SBA releases clarifying guidance on sole proprietorships, contractors, self-employed

April 16

PPP runs out of first $349 B tranche of funding; Fed liquidity facility goes live

April 2

SBA publishes interim rule on PPP

April 6

Fed announces intent to take PPP loans off of lender’s balance sheets

April 7

Treasury announces intent to add $250 B in additional funding to PPP

April 21

Congress reaches tentative agreement on additional $310 Bin funding for PPP

THE PAYCHECK PROTECTION PROGRAM’S WINDING PATHCongress’s small business support package has taken many turns, with new information coming out along the way

Updated as of 4:00 PM ET on 4/21/2020

30© Oliver Wyman

U.S. Real GDP Growth Forecasts – Q1, Q2, Q3, and annualAnnualized growth rate, by select economic analysts (9)1,2

Key observations from estimates

• Forecast updates have been frequent and sizable –Consensus is that bad news on the virus continues to outweigh good news on policy actions

• Forecasted Q2 qoq annualized growth rate in the US (~25–40% drop) will be the worst since we have quarterly data available

• Key indicators to track include:– Trend for percent of U.S.

population infected (scenarios ranging up to 80%)3

– Reliance on “smart” mitigation strategies (e.g., mass testing, use of analytics)

– Recovery speed in China, Europe

March 25-30 Apr 1-17

Q1 2020 Q2 2020 Q3 2020 2020 (annual)

Median -5.1% -30.0% 15.0% -5.5%

Average -5.9% -31.4% 12.6% -5.3%

Max/Min -2.2/-10.0% -24.8/-40.0% 23.0%/-1.0% -2.0/-7.7%

Latest consensus

Mid-march consensus

Q2 2020

-10

20

30

10

2020 (annual)Q1 2020

-30

0

-40

-20TD

JP MorganTD

Goldman

Citi

Annu

aliz

ed g

row

th ra

te

Goldman

Citi

Goldman

Moody’sBofA

JP Morgan

UBS

Morgan Stanley

Goldman

Morgan Stanley

Last updated: 4/21/2020

LATEST GDP FORECASTS INDICATE A SEVERE SHOCK IN THE U.S. ECONOMYThe escalation of the Covid-19 crisis has lead to significant downward revisions in GDP forecasts globally

Sources: Bank of America (Apr 2), Moody’s (Mar 25), UBS (Apr 15), Goldman Sachs (Mar 31), Morgan Stanley (Apr 3). TD Securities (Mar 25), UBS (Apr 2), Citi (Apr 3), JP Morgan (Apr 17).Quarterly estimates in terms of qoq% seasonally adjusted annual rate (saar)Imperial College COVID-19 response team

Q3 2020

31© Oliver Wyman

`

U.S. Unemployment Forecasts – Q1, Q2, Q3, and annualQuarterly unemployment rate, by select economic analysts (7)1

Key insights

• The annual unemployment forecasts assume a linear economic recovery starting in June, and do not account for the possibility of secondary waves of infection

• 22 million unemployment claims have been filed since the start of the COVID-19 lockdown, wiping out the last eleven years of job gains3 4

• The CARES Act has allocated $349 ($659?) Bn in forgivable loans to cover small business payroll expenses, padding against additional job losses in the short term

Apr 1-17 March 25-31

THE DOWNWARD SHOCK TO GDP FORECASTS IS MIRRORED IN UNEMPLOYMENTThe escalation of the Covid-19 crisis has lead to significant bearish revisions unemployment forecasts globally

2020(annual)Q1 2020

10

Q2 2020

0

5

20

15

TD

Goldman

UBS

Une

mpl

oym

ent r

ate

TD

JP Morgan

UBS

JP Morgan

Goldman

MS BofA

TD

UBS JP MorganGoldman

Peak unemployment during financial crisis2

1. Sources: Bank of America (Apr 2), UBS (Apr 2), Goldman Sachs (Mar 31), Morgan Stanley (Apr 3). TD Securities (Mar 25), Deutsche (Apr 13), JP Morgan (Apr 17).2. Sources: U.S. Bureau of Labor Statistics3. Source: Federal Reserve Bank of St. Louis4. Tracking unemployment forecasts against unemployment reports may be misleading – unemployment reports only record jobless workers actively searching for employment

Last updated: 4/21/2020

Q1 2020 Q2 2020 Q3 2020 2020 (annual)

Median 4.3% 15.5% 12.5% 8.9%

Average 3.9% 15.3% 14.3% 8.8%

Min / Max 3.6%/5.7% 11.7%/20.0% 6.6%/14.7% 7.5%/10.3%

Q3 2020

32© Oliver Wyman

91

88

92

89

90

95

96

94

98

97

93

99

100

Q6 (2Q 21)

2020 Covid Crisis consensus1

CCAR 2020

Start(4Q 19)

Q1 (1Q 20)

Q2 (2Q 20)

Q3 (3Q 20)

Q7 (3Q 21)

Q4 (4Q 20)

Q5 (1Q 21)

Financial Crisis

U.S. Real GDP relative to Q4 2019 (100) and compared to CCAR and Financial crisisEstimates as of Apr-31, US GDP Indexed to P0 (CCAR 2020)2 and 4Q07 (Financial Crisis)

“Spanish Flu” 1918-20 (4.25% - 5.5%)3

CCAR projected quarter2020 COVID Crisis projection

1. Consensus as the average of Goldman Sachs (Mar 31), JP Morgan (Apr 17), Morgan Stanley (Apr 3), Deutsche (Apr 3) forecasts2. Source: “CCAR 2020 data release” - Federal Reserve3. Source “Economic Impact of an Influenza Pandemic on the United States” – Federal Reserve Bank of St Louis

PROJECTIONS FOR THE U.S. ASSUME A RETURN TO PRE-COVID LEVELS BY LATE-2021We continue observing downward adjustments: as of last week, the expectation was to recover by Q3 2021

Last updated: 4/21/2020

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LATEST GDP ESTIMATES IN SELECT REGIONSThe escalation of COVID-19 crisis has lead to significant downward revisions in GDP forecasts globally

Consensus 2020 Real GDP Growth Forecasts, Nov 20191 vs Apr 20202

% growth YoY, median

2.9%2.0%

1.0% 1.0%

5.7%

-1.1%

-5.5%-3.9% -4.5%

1.5%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

Global US U.K. Euro China

2020 est. (in Nov 2019) 2020 est. (from Apr-21, 2020)

Last updated: 4/21/2020

1 Source: OECD.2. Sources: Bank of America (Apr 2), Moody’s (Mar 25), UBS (Apr 15), Goldman Sachs (Mar 31), Morgan Stanley (Apr 3). TD Securities (Mar 25), UBS (Apr 2), Citi (Apr 3), JP Morgan (Apr 17). GDP growth forecasts obtained as the median of estimates.

2020Q1: -6.8%

CONSUMER CREDIT RISK AND COVID-19Panelist: Deepak Kollali

04

35© Oliver Wyman

3/150%

2%

4%

6%

3/8 4/53/1 3/22 3/29 4/12

Dec-19 Mar-20Oct-19 Nov-19 Jan-20 Feb-20

-10

-5

0

5

Nov-19Oct-19 Jan-200

Dec-19 Feb-20 Mar-20

-10

-5

5

WHILE THE FIRST WAVE OF COVID APPEARS TO BE NEAR PEAKING, THERE IS A LONG SLOG AHEAD IN THE CONSUMER CREDIT ARENA

Leading indicators of challenges ahead…Consumer confidence index, % change MoM (Oct ‘19 – Mar ‘20)1

… And big impacts on consumer-related bank reservesQ1 reserve impact – consumer bank only ($BN)4

Advance retail sales, % change MoM (Oct ‘19 – Mar ‘20)2

Mortgage loans in forbearance, % (weekly) 3

27

51

16

9

2019 Q1 CECL Day 1impact

2020 Q1reserve build

2020 Q1 total

21% increase in reserves

1. Source: CEIC. 2. Source: FRED, seasonally adjusted. 3. Source: Mortgage Bankers Association. 4. Source: Q1 earnings releases for BAC, C, JPMC, WFC; Oliver Wyman analysis.

36© Oliver Wyman

Auto Card Residential Student

• No market for repossessions (auctions closed, extended lease terms, mfgr. incentives)

• Card spending down

• Reputational tradeoffs with line management

• Position in wallet and payment hierarchy for customers with many cards critical

• Impediments to operational processes (appraisals, closings, verifications)

• Stress on servicers – liquidity (forbearance), ops (call volume)

• Significantly greater volumes and structural changes since the last crisis creates potential blind spots

THE COVID-19 CRISIS POSES A HOST OF NEW CHALLENGES FOR CUSTOMER AND RISK MANAGEMENT

• Scale and sharpness of pandemic is creating unprecedent volumes of distressed customers seeking help, with high financial, reputational, and operational stakes

• Level of uncertainty is high, with wide range of epidemiological, economic, and policy scenarios to accounted for… including path to recovery and potential subsequent flare-ups

• Responses will be under many microscopes and must balance customer needs, government rules, employee safety, and shareholder expectations, among others

• Existing analytics and strategies are unreliable as macro factors, policy action, and changes in customer behavior go far outside historical range

• The premium on rapid response and switch to digital channel increases susceptibility to fraud and cyber risks• Coordination across numerous systems in a remote environment is stressing existing infrastructure and processes, and making seamless

customer journey management even more challenging

Example product-specific challenges

37© Oliver Wyman

Emergency response (In the past)

Mobilizing for sustainable response (Next 1-3 months)

Navigating through and beyond the crisis (3+ months)

• Support customers: Respond to immediate queries

• Put tactical measures in place: Implement government support measures, payment holidays, and suspend decisions

• Initial impact assessment: Understand high-level P&L and Balance Sheet

• Set bank purpose and principles

• Develop customer offering and credit strategy

• Enable operational delivery at-scale

• Learn fast – real-time feedback loops

(see next page)

• Continue to learn and refine: Continue to refine risk and customer management strategies as the COVID-19 scenario unfolds

• Define your strategy and capabilities for a new normal: Look forward to the process and capabilities that must be transformed for the potentially long tail of the crisis and beyond

AS THE COVID CRISIS PERSISTS, IT IS CRITICAL FOR BANKS TO BEGIN DESIGNING AND PLANNING FOR MORE SUSTAINABLE RISK MANAGEMENT RESPONSES

Banks have already moved quickly to offer forbearance to customers, while tightly controlling new credit extensions – these actions buy time, giving some breathing space to customers and banks alike

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Operational delivery

Acquisitions & underwriting Customer management Workout

Central purpose and principles

Customer offering and credit strategy design

Setup COVID control tower to dynamically respond to ever-changing epidemiological, economic, and policy environment

Define crisis response objectives, considering the bank’s financial capacity and risk appetite, and external requirements

Define key customer segments and archetypes based on key crisis drivers and expected impact on customer well-being

Determine treatment waterfall and ‘offramps’ to provide solutions to customers at different level of distress

12

34

Design customer journey for each segment with initial outreach, information gathering, and follow up5

Approval Pricing

Line assignment Cross-sell

Modifications Line management

Retention

Collections Collateral management

Application fraud

Optimize process and controls, including processes and procedures key compensating measures

Build execution capacity to deliver effective customer assistance across both internal and third party resources

Design and implement reporting, monitoring, and data collection to support control tower and decision making

Modify underlying systems, technologies, and tools to support updated processes

78910

WHAT AN EFFECTIVE RESPONSE LOOKS LIKE

Re-examine BAU credit risk management to identify models/processes/strategies requiring adaptation to the new environment6

39© Oliver Wyman

CUSTOMER ASSISTANCE: LESSONS LEARNED FROM THE LAST CRISIS

• Duration of hardship is a key driver of lasting solutions… And solving payment affordability is key to stabilizing performance– Payment deferral helps smooth over a few of months, but “catching up” can quickly fall further out of reach for some– Sustainable alignment of payment with capacity is needed to address longer income shortfalls; there are many ways to get

there, with potentially very different costs to the bank

• Importance of a customer-level view– Many of the hardest-hit customers have several forms of debt – understanding the full picture is critical to structuring

realistic payment plans– Coordination across lenders, or with investors, create complex incentive and operational issues

• Behavioral changes under stress– Last crisis saw the rise of the “strategic default” in mortgage arena– This time the “new normal” may change relative prioritization of e.g. home vs. auto payments– Also be wary of increased attempts at fraud, cyber

• Process complexity and lack of clarity can quickly become a problem – especially given scale– The last recession left a long tail of regulatory and legal troubles for banks– Some complexity is unavoidable, i.e. imposed by overlapping regulatory and third-party requirements– Banks must design their internal offerings and processes proactively to manage and complexity, and allow scalability

• Operational teams should be prepared and cross-trained for rolling surges in load across different processes

• A well-managed customer journey can win lasting loyalty

40© Oliver Wyman

READ OUR LATEST INSIGHTS ABOUT COVID-19 AND ITS GLOBAL IMPACT ONLINE

Oliver Wyman and our parent company Marsh & McLennan (MMC) have been monitoring the latest events and are putting forth our perspectives to support our clients and the industries they serve around the world. Our dedicated COVID-19 digital destination will be updated daily as the situation evolves

Visit our dedicated COVID-19 website:https://www.oliverwyman.com/coronavirus

QUALIFICATIONS, ASSUMPTIONS AND LIMITING CONDITIONSThis report is for the exclusive use of the Oliver Wyman client named herein. This report is not intended for general circulation or publication, nor is it to be reproduced, quoted or distributed for any purpose without the prior written permission of Oliver Wyman. There are no third party beneficiaries with respect to this report, and Oliver Wyman does not accept any liability to any third party.

Information furnished by others, upon which all or portions of this report are based, is believed to be reliable but has not been independently verified, unless otherwise expressly indicated. Public information and industry and statistical data are from sources we deem to be reliable; however, we make no representation as to the accuracy or completeness of such information. The findings contained in this report may contain predictions based on current data and historical trends. Any such predictions are subject to inherent risks and uncertainties. Oliver Wyman accepts no responsibility for actual results or future events.

The opinions expressed in this report are valid only for the purpose stated herein and as of the date of this report. No obligation is assumed to revise this report to reflect changes, events or conditions, which occur subsequent to the date hereof.

All decisions in connection with the implementation or use of advice or recommendations contained in this report are the sole responsibility of the client. This report does not represent investment advice nor does it provide an opinion regarding the fairness of any transaction to any and all parties. In addition, this report does not represent legal, medical, accounting, safety or other specialized advice. For any such advice, Oliver Wyman recommends seeking and obtaining advice from a qualified professional.