Insurers Can Use Alternative Data to Better Understand “Invisible” Consumers
Insurers may face a conundrum when it comes to assessing a new policyholder’s prospective risk, especially if they lack a traditional credit footprint. As a result, they’re forced to strike a balance between the risk (loss exposure) and the reward (premium growth) with less than desired information.
If you’re looking for a better solution, there is one: alternative data.
Traditional Credit Data vs. Alternative Data
Let’s begin with traditional credit data, which includes payment history on things like credit cards, mortgages, student loans and more. It’s the foundation of most credit-based account relationships because it can show:
1) whether a consumer has any existing credit balances and what his or her payment history is on those open accounts
2) how the consumer is managing his or her overall credit position
This data can be highly predictive of a consumer’s behavior, namely, how he or she will handle future financial obligations and insurance risk.
Besides traditional credit data, there’s non-traditional payment data. This alternative type of payment data is generally not reported to the credit bureaus; however, it reveals how people pay their everyday bills, such as utilities, pay TV and cell phone services.
Since the vast majority of U.S. consumers have these basic services, the data coverage is wide-ranging, and can be highly predictive of future account performance, as well as general risk performance.
More Data is Better
Research shows that up to 26 million adults lack credit files or the number of trade-lines they possess is negligible1. This represents roughly 10% of the U.S. adult population. For these consumers, evaluating their risk exclusively on traditional credit data alone is less than ideal.
This is where alternative data can change how insurers evaluate risk on these “invisible” consumers. Alternative data complements credit data and can improve visibility for millions of previously hidden consumers. It can make them visible and segment them by their prospective risk.
The more data you have (credit data, plus alternative data sources), the better you can:
- Accurately classify all customers based on risk
- Set appropriate risk-based rates
- Offer a more personalized customer experience
- Better understand the market allowing for more profitable growth
Enhancing your quoting process to include nontraditional payment information in addition to traditional credit information can improve underwriting segmentation, help ensure more profitable pricing, and may improve your overall customer acquisition rates.
Learn more about our solutions for the insurance industry, helping insurers cover more consumers.
1 Consumer Financial Protection Bureau https://www.consumerfinance.gov/about-us/newsroom/cfpb-report-finds-26-million-consumers-are-credit-invisible/
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