Liability Management : Autopilot Refinancing

1. Liability Management: Autopilot Refinancing Jonathan Zinman Dartmouth College and IPA’s U.S. Household Finance Initiative Financial Products Innovation FundWorking Group Meeting

2. What’s This Talk About? • Huge opportunity to add value by helping people manage their borrowing decisions • Asset Management model for Liability Management • Take a segment of Liability Management: “Personal Loan Shopper” • Focus on slice of that segment: “Autopilot Refis”

3. Debt is Where the Money Is • Huge market for asset management • Brokers, financial advisers/planners, private bankers, etc. • Yet debt is where the money is for most Americans • $13 trillion on household balance sheets • Many more people participate in debt market(s) than in, e.g., stock market • Borrowing costs > asset yields • Higher stakes

4. Household Mismanage the Liability Side of Their Balance Sheets • (Or at least evidence suggests that they do) • Potential sources of “decision inefficiency” • Overspending • Misallocation • Credit cards • Student loans • Failure to take-up workouts (e.g., HAMP) • *Undershopping • Upfront contract choice (e.g., overpaying) • When refinancing, or not • Money on table => Money to be made

5. Is There Really Money to Be Made? • Focus just on overpaying. Take a household that: • Has $10k in credit card debt and pays +500bp • Has $20k in student loans and pays +200bp • Has $20k in auto loans and pays +100bp • Has $200k in mortgage and pays +100bp • This household is paying >$3,000 in excess interest per year • Annuity value of $15,000-$100,000, depending on discount rate • Could get just a piece of this-- e.g., just auto loans– and be viable

6. A Segment of Liability Management:Personal Loan Shopping • There is a growing market for this already. Examples: • Problems with existing products: • Limited personalization (key for risk-based pricing) • Limited coverage: a single site/app/service rarely credibly covers all (low-cost) providers in the market • Biased coverage: nearly all business models are kickback-based • Limited/no coverage of refinancing Where there are gaps, there are opportunities!

7. A Slice of Personal Loan Shopping:Autopilot Refinancing Problem: People don’t refinance (auto, mortgage, student loans) when they should • Sen. Gillibrand seeks automatic refinancing of student loans at 4% rate (Examiner) • Agarwalet al on mortgages Why? • Inattention post-origination • Procrastination (fed up by complexity of option value)

8. A Slice of Personal Loan Shopping:Autopilot Refinancing (Cont’d) Solution: Find a better decision point -> at origination Putrefis on autopilot • Allow borrower to set a refinancing rule at origination • Like a limit order in asset management • Delegate mechanics to liability manager • Manager shops and negotiates on borrower’s behalf • Manager handles paperwork • Maybe even signing off under power-of-attorney

9. Making Autopilot Refis Work:Some Design Issues (These issues apply to loan shopping more broadly…) • Getting personalized data on consumers • How much? • Getting accurate data on offers • Accurately mapping consumer characteristics into offers • Moving money • Fiduciary standards

10. Making Autopilot Refis Work:What’s the Business Model? • My premise: get borrowers to pay for it • Kickback model dominates, so differentiate • Wouldn’t transparent pricing be better? • Branding • Regulatory constraints/threat • Signaling value proposition • So how do we get there? • Issue for value-added services more generally

11. Making Autopilot Refis Work:Will borrowers pay? How? “People won’t pay out-of-pocket for value-added financial services… they expect freebies” • But people do pay out of pocket for credit report management, identity theft protection, tax prep, etc. Pricing Models that have worked in other contexts • Upfront lump-sum • Natural for cash-out refinancing? • Otherwise paid by credit card? • Monthly subscription • Teaser? • Periodic “debt under management” fees

12. Pricing Autopilot Refis (and beyond):Unlocking borrower willingness-to-pay Behavioral research offers some insights… • Willingness-to-pay depends a lot on framing, timing • E.g., on marketing and choice architecture • Content • Timing of offer • Ease of take-up (on-ramping) • Effectiveness can vary across contexts • So R&D needed to successfully apply these insights to autopilot refis • To liability management more broadly • To financial product development even more broadly

13. Summing Up • Huge missing market for liability management • Personal loan shopping is a big piece • With autopilot refis a big piece of loan shopping • Many technical challenges • Some design/behavioral challenges, with the most important being business model • Unlocking willingness-to-pay • My bet is that these challenges are solvable • Some will require R&D of the traditional variety • Others will require behavioral R&D, including the sort of piloting and RCTs (AB-testing) that is supported by IPA’s Ford-funded work

15. Extra Slides Follow

16. Unlocking Consumer Willingness-to-Pay: Marketing Content • Informative appeals • How to frame cost savings? • How to signal quality/credibility? • Emotional appeals • How to capture attention? • How to counter procrastination? • Behavioral evidence suggests that: • Both informative and emotional can be effective • Context and customer-particulars matter => Optimizing content requires experimentation

17. Where do Consumers Go Wrong?(Product Design and Marketing) What leads to undershopping, overspending? • Behavioral factors: self-control costs, limited attention, price misperceptions • Confusion (financial illiteracy/innumeracy) • Disutility from personal financial management (distaste, time costs) How to solve for these pain points? R&D