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

July 26, 2013Ford Financial Products Innovation Fund

Working Group Meeting

Behavioral Design 101

Jonathan ZinmanDartmouth College and

IPA’s U.S. Household Finance Initiative

• Symptoms (focus on household finance)

• Diagnoses: what can go wrong (“behavioral factors”)

• Treatments

• Design principles for treatments

Outline

• 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

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

Diagnosis: Bandwidth Constraints

• Factor: “limited attention”

- Failing to consider contingencies

- Tuning out/not engaging

- Forgetting

• Treatments:

- Default options

- Pre-commitment

- Automation

- Reminders

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?

• Factor: Exponential Growth Bias- People underestimate growth and decline when interest compounds

Þ Saving appears less renumerative

Þ “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 whenthere’s little uncertainty)

• 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

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 targets2. Difficult subject matter3. Sensitive subject matter and motivated ignorance• Factor: Confirmation bias and other asymmetric learning

Diagnosis: limited learning

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

• 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

Jonathan Zinman

US Household Finance Initiative

Innovations for Poverty Action

www.poverty-action.org/ushouseholdfinance

www.dartmouth.edu/~jzinman/

jzinman@dartmouth.edu

Thank You!

Taxonomy of Behavioral Factors (see DellaVigna JEL)

DECISION

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

DECISIONPreferences

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