Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion Understanding Commissions Motivated Advice: Evidence from Indian Life Insurance Santosh Anagol (Wharton), Shawn Cole (Harvard Business School), Shayak Sarkar (Harvard) Wharton, February, 2012
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Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Understanding Commissions Motivated Advice:Evidence from Indian Life Insurance
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Pilot Script
• Introduce self, express need for life insurance
• Not looking for investment product• Seeking maximum risk cover at minimum cost• If need to save, prefer to save in a bank
• What policy do you recommend?
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Pilot Script: Proportion of Term Recommendations
Recommendation Risk Coverage Script(1)
Only Term Policy Recommended .09Any Term Policy Recommended .16Only Whole Type Policies Recommended .31Any Whole Type Policy Recommended .64Any Other Policy Type .18Observations 60
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Agents Talk Down Term Insurance
• “You want term: Are you planning on killing yourself?”
• “Term is throwing money away”
• Term is not for:
• Women• Middle class
• Term is only for:
• businessmen• government employees
• Offered endowment policy, calling it a term policy
• Only one instance of explicit debiasing “Don’t buy whole, it’sa rip-off”
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Quality of Advice: Multiple Recommendations
• Most term recommendations come as a part of multiplerecommendations (a package)
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Quality of Advice: Suitability and Catering• Do agents provide advice based on client’s actual need, or
client’s beliefs about what is the right product?• Important question in context where clients are unlikely to
understand differences in products
• Vary need:• Whole: “I want to save and invest money for the future, and I
also want to make sure my wife and children will be taken careof if I die. I do not have the discipline to save on my own”
• Term: “I am worried that if I die early, my wife and kids willnot be able to live comfortably or meet our financialobligations. I want to cover that risk at an affordable cost.”
• Vary beliefs:• “I have heard that whole insurance is a really good product. I
think it may be suitable for me. Maybe we can explore thatfurther? ”
• “I have heard that term insurance is a really good product. Ithink it may be suitable for me. Maybe we can explore thatfurther? ”
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Quality of Advice: Responding to Needs & Beliefs
• Overall low rate of recommending term insurance - even when auditor says theywant risk coverage and have heard term is a good product
• But needing risk coverage does cause about 12% higher probability of receiving
term recommendation
• Even when customer initially believes whole may be better for them
• At least some agents know that term insurance is better for risk coverage
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Catering vs. Quality Advice: Term InsuranceDependent Variable Any Term Only Term
(1) (2)
Belief Term 0.10*** 0.02*[0.03] [0.02]
Need Term 0.12*** 0.016[0.04] [0.01]
Belief Term * Need Term .024 .052*[.059] [.031]
Government Underwriter -0.12*** -.01[.041] [.02]
Constant -0.06 -0.01[0.05] [0.01]
Auditor FE YES YESObservations 511 511Adjusted R-squared 0.10 0.034Mean of Dep Var 0.13 0.03
• Agents do cater advice to both customer preferences and need for risk coverage
• Not just whole recommending machines• But catering mainly by adding on a term policy on top of a whole policy
• Following the ”path of least resistance”
• Government underwriters less likely to mention term plans overall
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Wide Range of Risk Coverages Recommended
Belief & Need = TermRisk Cover (U.S.D) Premium (U.S.D)
Whole Life Type Policies 12,997 629Term Type Policies 44,494 619
• Only 10% of auditors get a term recommendation
• But the amount of risk coverage they get recommended is approx 4 times larger
• Possible theory: agents cater to premium amount that can be paid
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Improving Advice: Natural Experiment on Effect ofDisclosure
• Natural experiment on ULIP disclosures
• Prior to July 1, 2010, agents required to inform buyers abouttotal ULIP costs/charges
• As of July 1, 2010, agents are required to provide separatebreakdown of commission costs
• Allows us to isolate disclosure of agency problems
• Measure agent reaction
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Field Experiment Overlaid on Natural Experiment
• Overlay with field experiment
• Agent expresses knowledge of agency problems
• “Can you give me more information about the commissioncharges I’ll be paying?”
• Agent does not express knowledge of agency problems
• [No statement]
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Results
Table: 8-Effect of Disclosure on Product Recommendations
Dep Var = Ulip Recommended (1) (2)Post Disclosure Regulation -0.22*** -0.21***
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Disclosure Results
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Typewritten Text
Dramatic reduction in ULIP recommendations Agents instead recommend Whole insurance
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Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Improving Advice: Competition?
• Competition and bad advice: does the threat of losing a saleto another agent make an agent more likely to match needs ofcustomer?
• Vary level of competition by varying source of beliefs:
• “I have heard from a friend that whole (life)...”• “I have heard from another agent from whom I am considering
purchasing...”
• Does agent try to win business by correcting another agent?
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Does Competition Matter for Type of Advice?
• Agents de-bias when advice comes from another agent
• Statistically significant at 5 percent level
• Note that this de-biasing is mainly through recommending term in addition to whole
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Improving Advice: Sophisticated vs. Un-SophisticatedCustomers
• High level of sophistication:
• “In the past, I have spent time shopping for the policies, andam perhaps surprisingly somewhat familiar with the differenttypes of policies: ULIPs, term, whole life insurance. However, Iam less familiar with the specific policies that your firm offers,so I was hoping you can walk me through them andrecommend a policy specific for my situation.”
• Low level of sophistication:
• “I am aware that Life Insurance products are complex, and Idon’t understand them very much. However I am interested inlearning, what type of policy may be right for me?”
• Delivered in introduction of auditor to agent
• Remainder of script unchanged
• In particular, stated income held constant
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Typewritten Text
Motivation and Context Quality of Advice Improving Advice Objective Advice Conclusion
Sophistication Results: Product Recommendation
(1) (2) (3) (4)Dependent Variable: Any Term Only Term Ln(Coverage) Ln(Premium)Sophisticated 0.10* 0.10 * 0.21* -0.06