1. July 26, 2013 Ford Financial Products Innovation Fund Working Group Meeting Behavioral Design 101 Jonathan Zinman Dartmouth College and IPA’s U.S. Household Finance Initiative

2. Symptoms (focus on household finance) Diagnoses: what can go wrong (“behavioral factors”) Treatments Design principles for treatments Outline

3. Lots of borrowing (overborrowing?) – Credit card debt per household ~= $10,000 – Student loan debt per household ~= $10,000 – Mortgages, auto loans – Share of consumers with subprime credit: 56.4% 1 Many without savings (undersaving?) – Households with insufficient liquid assets to subsist for three months at the poverty line in absence of income: 43.9% 2 – Households that reported no saving in the previous year: 48% 3 Many pay premia for financial services (overpaying?) 4 – Assets – Loans – Advice Symptoms

4. Diagnosis: Struggles in Managing Desires Factor: Self-Control problems (carpe diem!) – Treatments: commitment, support, on-ramping Factor: Loss-aversion – Treatments: pre-commitment, change the frame Factor: Projection bias – Treatment: help people visualize the future

5. Diagnosis: Bandwidth Constraints Factor: “limited attention” -Failing to consider contingencies -Tuning out/not engaging -Forgetting Treatments: -Default options -Pre-commitment -Automation -Reminders

6. Diagnosis: Biased Forecasting Many types: -Factor: Belief in Law of Small Numbers -Factor: Non-belief in Law of Large Numbers -Factor: *Excessive optimism Treatment: -Information/debiasing?

7. Factor: Exponential Growth Bias -People underestimate growth and decline when interest compounds  Saving appears less renumerative  “Low monthly payments” appear deceptively cheap Treatments: -Saving: Show future values -Borrowing: APRs and other apples-to-apples comparisons Factor: Low Numeracy Treatments: -Simple, intuitive information? Diagnosis: Getting the math wrong (even when there’s little uncertainty)

8. Factor: Low Financial literacy -Lack of basic knowledge  Of key concepts: diversification, inflation  Of how products work: e.g., ARMs, term vs. whole life Treatments: -Default options -Simple/intuitive disclosures Diagnosis: Getting the facts wrong

9. About finance, about oneself. Why? 1. Limited opportunities On high-stakes decisions (mortgage, job, auto financing) Even high-frequency decisions can have uncertain long-run implications -Credit card use (what’s right debt load for me/my family)? Changing life circumstances creates moving targets 2. Difficult subject matter 3. Sensitive subject matter and motivated ignorance Factor: Confirmation bias and other asymmetric learning Diagnosis: limited learning

10. Delegation: works pretty well in medicine, auto repair, etc. But financial advice markets are a mess -Questionable quality: Lots of biased, even fraudulent advice -Limited scope: Who covers the household balance sheet? -Limited coverage: mass market? Competition: often brings prices down, but does not seem sufficient to eliminate yield-spread premia, $39 overdraft fees, etc. Diagnosis: “Killer Apps” don’t work as well as in other markets

11. Simplify Streamline (on-ramping) Just-in-time (reach people at decision point) Meet people where they’re at –Facilitating, nudging much more effective than felt-change Diagnose and treat Be humble: we still have a lot to learn –Mixed and limited evidence, especially outside the lab –A premise of behavioral social science is that context matters Developing Treatments: Design Principles

12. Jonathan Zinman US Household Finance Initiative Innovations for Poverty Action www.poverty-action.org/ushouseholdfinance www.dartmouth.edu/~jzinman/ jzinman@dartmouth.edu Thank You!

13. Taxonomy of Behavioral Factors (see DellaVigna JEL) DECISION Biases in preferences Time- inconsistency Loss aversion Biases in expectations Overconfidence Over-optimism Biases in price perceptions/valuation Exponential growth bias Anchoring “Cross-cutting” biases/heuristics/ limitations: Anchoring, Limited attention, Innumeracy

14. DECISION Preferences Biases/limitations in cognition that affect perceptions about how to maximize utility subject to constraints ( Affect other key parameters we might model: expectations, prices, transaction costs…) Alternate Taxonomy