What is Happening with Personal Loan Losses?

Ram Ahluwalia

CEO, PeerIQ

2

P E E R I Q I N T R O

PeerIQ is a NYC-based data & analytics firm that enables lenders and institutional investors to transact with confidence.

Risk Management

1. R isk Analytics

Benchmarking / P ortfolio Mgmt

Valuation S ervices

C redit Facility Management

2. Data

• TransUnion Derived C redit Ins ights

• 25+ lenders in a standardized

T O D A Y ’ S C O N S U M E R C R E D I T P A R A D O X

3

Macro conditions

are strong…

…yet credit

performance is

weakening

How can better data help us reconcile this contradiction?

R E N O R M A L I Z A T I O N O F C R E D I T P E R F O R M A N C E

4

• C ons umer credit charge-offs are reverting to their long -term average

• Derogatory outcomes like delinquencies , defaults and bankruptcies are falling off the credit file due to Fair C redit R eporting Act R equirements

• Models are fighting the last war:

• Trained off his torical data sets in a benign credit environment

• Miss turn-around points and tend to under/over shoot

S ource: PeerIQ; Trans Union

% Delinquency on Unsecured Consumer Loans

Long-term Avg ~3%

I N C R E A S E D S U P P L Y O F C R E D I T

5

• C redit availability is at an all-time high – driven by new entrants and rising credit scores

• C redit growth Y O Y (8% ) has outpaced growth in G DP and personal income

• C ompetition for the customer can lead to looser underwriting standards

• Availability of unsecured personal loans can increase borrower indebtedness post-origination (especially if the loans are not used for debt consolidation)

S ource: PeerIQ; Trans Union

S ource: PeerIQ; S t. Louis Fed

P E R S O N A L L O A N S A R E N O T S U B S T I T U T I N G F O R C R E D I T C A R D O R O T H E R D E B T

6

• P ersonal loans are used to refinance high rate debt less than 20% . Borrowers see the personal loan as another type of borrowing instrument

• Behavior varies by segment. Initial analytics indicates super-prime borrowers are taking down personal loans ; where as subprime has more paydown

S ource: PeerIQ; Trans Union

% of Balance Used to Refi Other Debt

P R I O R I T Y O F P A Y M E N T S I S S H I F T I N G

7

• Delinquencies on Unsecured Consumer Loans are second only to those on Auto loans

• P ayment priority has shifted 3x in the case of auto

• New channels and technology are leading to more rapid shifts in consumer behavior (e.g., the “Lyft effect”, cell phones , etc.)

% Delinquency

D R I V E R S O F C R E D I T P E R F O R M A N C E

8

• R enormalization of credit performance

• Increased supply of credit / underwriting

• P ersonal loans shifting from debt refi to general purpose

• P riority of payments is shifting

• Outlook

9

P E E R I Q C O N S U M E R C R E D I T I N S I G H T S S

ABS/Whole Loan

Investor

Customer Segment Objectives Addressed

• Investors have differing levels of sophistication, some may be satisfied with Fed reports

• No platform solutions for AB S investors today

• S mall number of investors looking to actively purchase whole loans

Considerations

• Buy/S ell a bond or res id

• Provide capital to/purchase loans from originator

Sample Questions Addressed

• How is the are loans in a particular credit tier performing? Has performance improved or deteriorated over time?

• What returns should I expect if I invest in a given asset class/credit tier?

• How has underwriting changed over time?

Macro Funds,

Large PE,

Economists

• May want to engage with the data programmatically as well as via a GUI

• R esearch is typically a cost center, and as such is more price sens itive

• Consumer credit is not particularly dynamic, need to demonstrate the value of monthly data

• Assess the overall state of the economy

• Identify trades based on larger macroeconomic trends

• S trategic view into portfolio companies or potential targets

• How “healthy” is the US consumer?

• Is credit more or less available than in the past?

• How has consumer behavior changed over time? Are credit dollars being allocated in the same way as the past?

• How does US consumer credit compare to other macro data items (GD P , etc.)

Non Bank

Originators,

Regional Banks, &

Credit Unions

• Banks and other institutions typically have large internal datasets

• Adjust pricing/marketing strategy based on macro factors

• Asses risk to existing portfolio based on consumer behavior

• How has the source of credit changed over time (bank vs . non bank, etc.)

• Are there particular credit tiers/sub segments of the population that are over/underperforming?

• Is my pricing in line with the market?

• Are consumers seeking out more or less credit than in the past

10

C O N S U M E R C R E D I T I N S I G H T S E X A M P L E

• Analyze multiple vintages and observe borrower attributes at various points over the life of the vintage.

• Utilization on revolving products reveals significant differences across the vantage bands, with Subprime borrowers decreasing their utilization and Prime borrowers increasing theirs.

S ource: PeerIQ; Trans Union

O U T L O O K

11

Consumer Relationship

“Big Tech”

Money Center Banks

/ Wealth Management

“FinTech”

Community Banks /

Credit Unions

• Competition to own the Customer

• New entrants: “Big Tech” (e.g., Intuit, P aypal, Amazon, G oogle)

• S ecured Lending - $300 Bn – in a few short years , is now half the size of the credit card industry by targeting S uper Prime borrowers

• Lenders with captive customer acquisition channels and novel data are selecting quality borrowers. A few examples:

• Amazon Lending -$3 Bn in small-bus iness loans originated

• Big Tech + Big Bank: Chase/Amazon; Barclays/Uber

• F inTech + S mall Banks : unique origination channels (PO S ), new products

Q & A

12

Ram Ahluwalia, CFA

Founder & CE O

917.363.3747

ram@peeriq.com

1. Subscribe to our newsletter

2. Visit our blog for commentary

3. Download public research

4. Request a demo

www.peeriq.com/sign-up

www.peeriq.com/blog

www.peeriq.com/research

www.peeriq.com/demo

Contact Stay Connected

Kevin Walsh, PhD

Chief Commercial Officer

917.450.1232

kevin.walsh@peeriq.com

Brian Roncoroni

Head of S ales

917.627.5766

brian@peeriq.com

A P P E N D I X : M O D E L S F I G H T I N G T H E L A S T W A RWhy FICO is flawed

13

• Traditional credit scores are backward lookingand are des igned to rank-order credit risk

• Not cash-flow oriented and does not captureunderwriting quality of the loan

• Not time-homogenous: A credit score of 700immediately post-crisis is much strongerthan a 700 credit score pre-cris is

• Wrong measurement: The credit-score doesnot evaluate the probability of a specific loandefaulting, but rather the probability of theborrower defaulting (e.g., ignores paymentpriority and the relationship of lender to theborrower)

• Cannot be summarized via averages: FICO isdefined on a logarithmic basis – weightedaverages distort interpretations

• Credit scores have blind spots (ex: ignore infofrom 7 years per the FCR A)

Distribution of credit scores on Avant shelf have not changes significantly over the las t two years

However, Avant has :

• Tightened credit quality

• R educed size of the loan 20% from $5,348 from $6,589

• R educed Weighted Average Term – 94% loans are below 36-month term vs . 47% in Avant 2016-C

S ource: PeerIQ