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Page 1: Liability Management : Autopilot Refinancing

July 26, 2013

Liability Management:Autopilot Refinancing

Jonathan ZinmanDartmouth College and

IPA’s U.S. Household Finance Initiative

Financial Products Innovation FundWorking Group Meeting

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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”

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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

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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 cardsStudent 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

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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

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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!

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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)

• Agarwal et al on mortgages

Why?

• Inattention post-origination• Procrastination (fed up by complexity of option value)

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Solution:Find a better decision point -> at origination Put refis 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

A Slice of Personal Loan Shopping:Autopilot Refinancing (Cont’d)

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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

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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?

BrandingRegulatory constraints/threatSignaling value proposition

• So how do we get there?– Issue for value-added services more generally

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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 subscriptionTeaser?

• Periodic “debt under management” fees

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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

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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

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Extra Slides Follow

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Unlocking Consumer Willingness-to-Pay: Marketing Content

• Informative appealsHow to frame cost savings?How to signal quality/credibility?

• Emotional appealsHow 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

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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