1 why low credit scores predict more auto liability claims: two theories patrick butler* american...
TRANSCRIPT
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Why Low Credit Scores Predict More Auto Liability
Claims: Two Theories
Patrick Butler*American Risk & Insurance Association
August 7, 2007
*National Organization for [email protected]
#774.7804
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Policy dilemma: get “A” w/o getting “B”
A. Mandatory liability insurance– Public demands it
– Insurers oppose it because of “B”
B. Price regulation– To keep mandatory insurance affordable
– Recent example is initiatives to ban or regulate credit score (CS) pricing
– In response auto insurers commissioned a large study completed in 2003
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Claims per 100 car years: +90% to -25% of average
1.90 / 0.75 = 2.5 times
+90%
-25%
Figure 1. Liability Claims vs. Credit Scores(from Miller & Smith 2003)
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Theory 1 “More driver negligence”
• Basis for theory
– Each liability claim requires a negligent act by insured car’s driver
• Logic
– Cars of low CS drivers average more liability claims
– Therefore these drivers are more negligent
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Theory 1 (continued)Explanations
• Miller & Smith 2003 (insurance industry explanation)
“[Credit-based] scores seem to provide an objective means
of measuring personal responsibility and its effect on
insurance losses.”
• Brockett et al. 2005 (1st academic study)– Presented at WRIEC, Salt Lake City
– Published 2007
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Theory 1 (continued)biological explanation
Brockett & Golden 2007 (J. Risk & Insurance)
• Title (underline added):
“Biological and Psychobehavioral Correlates of Credit
Scores and Automobile Insurance Losses: Toward an
Explication of Why Credit Scoring Works”
• Conclude that the research examined by their study
“suggests that the discussed individualized biological and
psychobehavioral correlates provide a connection between
credit scores and automobile insurance losses.“
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Model for Theory 1 is the biological explanation for correlation with driver age
Driver Age
Similar age effects confirmed per worker hour of exposure
Involvement Rate =Accidents per 1,000,000 miles
(from Williams 1999)
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Theory 1 Unaddressed Matters
• Claims & accidents are referenced to driver- and car-years, but individual annual-miles exposures vary widely
• A conflict with risk aversion theory
– Greater financial constraint predicts more risk aversion, i.e., less negligence
• Insurers report that lower CS also predicts more uninsured motorist (UM) claims.
– But a UM claim requires non negligence by the insured car’s driver
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CS Theory 2“More miles per insured car year”
• UM & Liability Claims must correlate (+):– The more miles a group of cars averages, the more
claims per 100 car years the group produces
• more negligence claims, and also
• more non-negligence (UM) claims
• This means that the cars of financially-constrained drivers must be averaging more miles. Why so?
• But first some basics:
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Basics for Theory 2
• Given – Accidents are a cost of car operating
• Given – Premiums are a cost of car owning
• But is the range in annual miles enough to explain the 2.5 times CS variable range in claims per 100 car years?
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Fig. 2. Yes. Household Cars Distributed by Odometer Miles Shows Range
• Subgroups by car age, and by driver sex and age (despite difference in averages) span entire annual-miles range
• So cars within insurance classes span low- to high-miles
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%>
0-2
>2
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>6
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>1
2-1
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>1
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>3
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Annual Miles (000)
Cars
4.4% > 32K miles
Mean = 11,801 milesMedian = 9,448 milesN = 32,153 carsN = 32,153 cars
1.0% = 0 miles
WOMEN DRIVERS AVG = 10,143 MILES
MEN DRIVERS AVG = 16,553 MILES
Figure 3 (Recasting of Figure 2)
12 The CS range in claims: 2.5 times = 15,000 mi / 6,000 mi
Figure 4. Why miles must be individually measured
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Avg miles explain why new cars average more liability claims than old cars But distribution shows many new cars are driven fewer miles than old cars
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Logic of Theory 2 illustrated(Hard but sure way to economize)
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Theory 2 fits other predictors
1. Zip code income (-)2. Education & occupation (-)3. No prior insurance (+)4. Installment plan (+)
X. Any marker of tight budgets predicts more liability claims per 100 car years
Therefore, the highest per-car premiums are charged to those who can least afford them
Theory 2 recommends
• Informed by Theory 2, the strong public demand for enforcing mandatory liability insurance could be accompanied by
– A strong demand that automobile insurers provide the audited odometer-mile exposure unit as an option
– At cents-per-odometer-mile class prices this option would constitute a free-market remedy for the upward cost-price spiral that the traditional car-year exposure unit sets off for groups of economizing drivers
– With this option drivers could car pool or take the bus to save on insurance while keeping their own cars insured and available for use
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Table 2. What’s at stake – the challenge for both theories
Range: $1,136 / $258 = 4.4 times
Insurance Company PremiumALLSTATE PROP & CAS INS CO 258
GEICO 318
PROGRESSIVE NORTHEASTERN 326
STATE FARM MUT AUTO INS CO 375
GEICO IND CO 492
METROPOLITAN GRP P&C INS CO 641
AUTOONE INS CO 854
ALLSTATE IND CO 1,136
e. g., Albany, NY: lowest and highest quoted for one car class profile (same driver age, record, sex, and marital status).
Conclusion – Research questionWhich policy response to the dilemma
“free-market vs. affordability vs. mandatory insurance”
• Theory 1, some issues– Identify the negligent driver groups on an
accidents-per-1,000,000-mile basis– Find incentives to reduce negligence per-mile
• Theory 2, some issues (discuss in Q & A)– Federal surveys show average miles per car year
decreases moderately as household income decreases– Some high premiums for adult-driver-class cars may
reflect not only higher miles per car, but also the higher per 1,000,000 mile accident involvement rates of “undisclosed” young and old drivers sharing the cars
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