To stay competitive, property insurance carriers are continually seeking more sophisticated pricing strategies and overall rating adequacy. One solution many carriers are more closely evaluating is the use of data traditionally used for auto insurance underwriting.
We recently discovered critical reasons to consider using alternative data during homeowners underwriting assessment. The key finding of this internal analysis was that court record violation data is predictive of future homeowners losses or claims. Alternative data gives personal property insurance carriers unique insights that can help improve pricing and rating effectiveness and achieve a better loss ratio. Understanding all occupants of an insured property can further enable more sophisticated pricing and underwriting decisions to improve profitability.
Expanded insight into household risk
When analyzing homeowners policy and performance data, our study identified 25% of policies had recorded violations stemming from the Primary Named Insured (PNI). We then identified and confirmed additional household members on 60% of policies. This expanded view that included additional household members found 34% of policies had violations.
We identified violations from verified household members in addition to the Primary Named Insured (PNI) to enhance household performance classifications
This provides valuable information to underwriters because PNIs are not the only occupants who can cause non-weather losses.
The predictive power of combining criminal and traffic violations data with TransUnion’s proprietary household matching allows for better segmentation and improved pricing.
To get the complete findings, download our free Insight Guide, The Power of Alternative Data.
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