Transcript Behavioral Design 101 Jonathan Zinman Dartmouth College and IPA’s U.S. Household Finance Initiative 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
July 26, 2013
Ford Financial Products Innovation Fund
Working Group Meeting
Outline
•
Symptoms (focus on household finance)
•
Diagnoses: what can go wrong (“behavioral factors”)
•
Treatments
•
Design principles for treatments
Symptoms
•
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
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?
Diagnosis: Getting the math wrong (even when
there’s little uncertainty)
•
Factor: Exponential Growth Bias
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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 facts wrong
•
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: limited learning
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: “Killer Apps” don’t work
as well as in other markets
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.
Developing Treatments:
Design Principles
• 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
Thank You!
Jonathan Zinman
US Household Finance Initiative
Innovations for Poverty Action
www.poverty-action.org/ushouseholdfinance
www.dartmouth.edu/~jzinman/
[email protected]
Taxonomy of Behavioral Factors
(see DellaVigna JEL)
“Cross-cutting” biases/heuristics/ limitations:
Anchoring, Limited attention, Innumeracy
Biases in
preferences
• Time-inconsistency
• Loss aversion
Biases in price
perceptions/valuation
• Exponential growth bias
• Anchoring
DECISION
DECISION
Biases in expectations
• Overconfidence
• Over-optimism
Alternate Taxonomy
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…)
Preferences
DECISION