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Borrow Less Tomorrow

Apr 03, 2018



Lorelei Mares
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  • 7/28/2019 Borrow Less Tomorrow





    Dean Karlan, Yale University

    Jonathan Zinman, Dartmouth College

    June 2011

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    Problem: Household DebtManagement

    Low household savings rate (sometimes)

    High debt loads/reliance in emergencies

    Highest, safest return for many households:pay down expensive debt

    But getting/staying out of debt is hard,

    psychologically, cognitively, etc.

    o Consumers may need helpo Yet many face limited, unattractive options in

    market for debt management services

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    Potential Solution:Borrow Less Tomorrow (BoLT)

    Design Strategy:o Use behavioral insights to develop a new product

    that helps people reduce/manage debt

    o Save More Tomorrow as a guideo SMaRT: 401k enrollments

    o Important institutional/market differences between retirementsaving and debt reduction

    Kitchen sink/behavioral engineering approacho

    Design product to counter multiple potential biases:o In price perceptions, attention, preferences

    o Product/choice architecture approach

    o (Ideally/eventually complemented with robust advicemarket)

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    BoLT Features

    Motivate: Help consumers identify whetherthey should borrow less

    Plan: Help consumers make a concrete plan

    to borrow less Commit: Offer client option(s) to incentivize

    sticking to the plano Current options include peer supporters/referees

    o Harder commitment options to be added soon

    Communicate: Send feedback/reminders tostay on track

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    Pilot Testing So Far

    Small-sample concept test: Jan 2010- April2011o Convenience sample: tax preparation clients, Community Action

    Project (CAP), in Tulsa Pilot addresses two threshold questions

    Will borrowers use BoLT if offered simple, freeversion?

    (Also: who wants BoLT? Demand analysis)

    Potential for cost-effectiveoperation/administration?

    Also trying to build large enough sample totest BoLTs effectiveness

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    Operations/Field Experiment Flowfor Pilot Testing

    Person enters tax prep site Offered survey, consent form for soft pulls of credit

    report Randomly assigned to Treatment (some version of

    BoLT) or Control (no BoLT, or BoLT later) BoLT group:

    Counselor works with client to identify whether suitabledebt

    Uses repayment calculator to come up with a plan Offers opportunity to enlist peer support Peer supporters contacted

    Later: Regular reminders to make payments Client notification and peer notification if fall off-track

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    Pilot Sample Characteristics:Year 1 N =505 with auto loan or credit card debt

    From baseline credit report:Credit score: mean 603, standard deviation (95)

    Credit card balances: mean $2,408, SD ($5,103)Auto loan balance: mean $5649, SD (7626)

    From baseline survey: 70% at least some college

    >20% report using fringe loan product in last 2years

    High prevalence of various financial distressproxies

    But 57% say financial situation >= OK

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    Pilot Threshold Question 1:Demand?

    Are borrowers interested in using BoLT? Yes!

    38% take-up rate among CAPs tax prepclients with a credit card or auto loan at

    baselineo This is without doing any pre-screening or target

    marketing for high-interest debt

    Among BoLT takers, 48% enlist peer support Given that have some BoLT takers, and lots of

    baseline data on everyone, can do somedemand analysis

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    Question 1a, Demand Analysis:Behavioral Demand Factors?

    Baseline data on N = 173 assigned to BoLT offer

    Univariate corrs with behavioral measures: Often regret spending: 0.19 (0.08)

    Standard time-inconsistency: 0.04 (0.09) Exponential growth bias: 0.03 (0.08)

    Think about financials < a lot: -0.11 (0.08)

    Denial proxy: 0.08 (0.08)

    Similar multivariate results when include all ofabove behavioral factors

    Will add other RHS variables as sample sizegrows.

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    Question 1b, Demand Analysis:Description of BoLT plans

    58% of takers use for a credit cardo Estimated mean interest rate: 18%

    o Estimated principal amount: $4,000


    Mean plan to accelerate repayment: $23/montho Median payoff time with vs. without BoLT: 17 vs. 35


    42% of takers use for auto loano Estimated mean interest rate: 12%

    o Estimated principal amount: $10,000

    o Mean plan to accelerate repayment: $41/month

    o Median payoff time with vs. without BoLT: 32 vs. 45months

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    Pilot Threshold Question 2:Delivery?

    Can BoLT be marketed cost-effectively? Probably yes. More speculation on this later.

    Feasible to monitor whether someone is on track

    with paydown schedule?o Yes, using credit report soft pulls (with client consent

    obtained up front)o Finding cost efficiencies key to scale-up

    Peer supporters actually reachable when a BoLTclient falls off track?o Yes, though there is some room for improvement;

    e.g., give a heads-up to peers up front

    Text message reminders deliverable? Yes.

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    Beyond Threshold Questions:Is BoLT Effective?

    Why is random assignment important for answeringthis?

    After 6 months, 29% of BoLT users were onschedule

    59% of BoLT users stayed on schedule for >= 1month

    Are these proportions low or high? Unknown!

    o Depends on the counterfactual what wouldbalances look like in absence of BoLT?

    o If difficult to pay down expensive debt thencounterfactual = continued high balanceso Analogy to smoking: most attempts to quit fail

    o So we implement BoLT as part of field test that

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    Measuring Effectiveness:Some Outcomes of Interest

    Outcome measurement from follow-up softpulls of credit report. So can measure:

    Credit score

    Balances *1/0 plausible-sized reduction in balances*

    In other settings might be able to do some

    short follow-up surveys by web or phoneMeasure self-assessed financial condition, etc.

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    o ec veness on ear sample:

    12-month treatment effects OLS-estimated effects of BoLT offer on: 5%, 10% reduction in card debt: -0.05(0.04), -


    5%, 10% reduction in car debt: 0.03(0.05),0.03(0.04)

    Propensity score matching (person-level)estimates: 5%, 10% reduction in card debt: 0.00(0.05),


    5%, 10% reduction in car debt: 0.14(0.06),0.15(0.06)

    Small sam le is a challen e but:

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    sample:Preliminary thoughts on

    interpretationWhy might this version of BoLT work for car, notcard?

    Most people have many cards, one car loan

    Explore this hypothesis going forward using Loan-level matching estimators: that way can look at

    whether BoLT takers pay down targeted card, butcharge up other(s)

    Heterogeneous treatment effects: conditional on otherbaseline characteristics, is BoLT less effective forthose with more cards

    If this whats going on, suggests important goingforward to offer BoLT across multiple loans

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    Going Forward: DesignPermutationsMuch more development and testing worth doing!

    Consumermotivation through direct marketing

    Expand and improve set of potential plans. Examples:o Plans over aggregated balances (e.g., across all cards)

    o Plans to restrict new borrowing (e.g., no new trades)

    o Extend to products not covered in traditional bureaus?o Improve repayment planning using algorithm-based advice to set

    default options

    Expand set of potential commitments. Examples:o Performance bonds


    Cut me offso Link peer support to social networking

    Refine communication strategy Content, timing, frequency, duration, channel, client customization

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    Going Forward: Business Model

    Reach scale with partners who have comparativeadvantage in deliveryo Bureaus/credit report monitoring services

    o Credit counseling agencies

    o Online financial management aggregators/advisors

    o Debt buyers/collectors (back-end for clients whorepay)

    o Payments platformso Mobile walletso Bill payers

    Identify revenue modelso Subscription (as part of a larger bundle?)

    o Cross-sell/bundling

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    BoLT and Beyond:Debt Management Market Opportunities

    BoLT but one example of a focus on market solutions for

    Helping consumers take control of their finances

    In particular on the liability side of balance sheet Huge asset management industry

    Wheres the debt management industry? Trillions of dollars in U.S. household debt

    Return (cost) dispersion much bigger on liability than on assetside Hall and Woodward (2010); Stango and Zinman (2011a, b)

    Helping consumers reduce borrowing levels, costs is where themoney is: hundreds of basis points

    Existing solutions limited in scope (CCS), value (debt settlement,brokers)

    (Wheres household balance sheet management industry?) Private banking for Main Street