Predictive Analytics for Property Insurance Carriers

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1 INSIGHT GUIDE Predictive Analytics for Property Insurance Carriers Michelle Jackson, Product Development Manager, TransUnion Lisa Volmar, Senior Director, Product Development, TransUnion 2015 TransUnion LLC. All Rights Reserved

2 Table of contents Introduction... 3 The homeowners market...4 Mitigating fraudulent property claims at the point of sale...4 Monitoring for changes at renewal... 5 Data and the future of underwriting...6 Targeting fraud with analytics... 7 Fast-tracking to lower risk...8 Responding to new market demands TransUnion LLC. All Rights Reserved

3 Introduction As the economy, the American public, and the U.S. housing market evolve, property insurance solutions must become more dynamic and proactive. Since the housing bubble burst, affected consumers have recovered and returned to the market, causing an increased demand for homeowners insurance. However, as the rate of new mortgages rises, the rate of fraud has risen as well. Current estimates show that an increasingly high number of property claims are fraudulent, with most going undetected. Fraudulent claims account for a significant portion of all claims received by insurers, costing $80 billion a year, as estimated by the Coalition Against Insurance Fraud. 1 Point of sale underwriting is a critical time to identify high-risk policies. By using predictive analytics and property risk verification solutions to confirm occupancy and ownership information, insurers can identify fraud before it leads to costly losses. Similarly, monitoring for changes at renewal and claims presents an opportunity to fight fraud with analytics. Responding to new market demands with risk verification tools and predictive insights can contribute to an enhanced consumer experience and better informed decisions, while limiting risk. 1. Coalition Against Insurance Fraud, TransUnion LLC. All Rights Reserved

4 The homeowners market According to data from the National Association of Realtors, purchases of previously owned homes rose in July 2015 for the third consecutive month, reaching the highest level since February A strong labor market and low mortgage rates fueled demand, resulting in a 2.7% increase in sales of existing singlefamily homes, bringing the annual rate to 4.96 million. 2 Parallel to these findings, a recent TransUnion study showed an increase in consumers looking for homeowners insurance since the housing bubble burst. During the mortgage bubble in 2006, 78 million consumers, or 43% of credit-active consumers in the U.S., had a mortgage, and more than 8% of these consumers were impacted when the bubble burst. As defined in the study, impacted consumers, or Boomerang Buyers, refers to those who were 60+ days past due on a mortgage loan; lost their mortgage through foreclosure, short sale or other non-satisfactory closure; or had a mortgage loan modification between the bubble and the burst. The study found that 18% of consumers who were impacted had recovered by December 2014, meaning that over the next five years, 2.2 million Boomerang Buyers would be ready to re-enter the mortgage market. 3 With the uptick in mortgages increasing the demand for new homeowners policies, insurance carriers must improve new business underwriting performance to limit losses while meeting revenue growth objectives. A carrier s prefill solution may help facilitate the quote process, enhance the consumer experience and improve conversions, but does it accurately identify exposure? To make better informed decisions, insurers are turning to alternative data to improve the application process, determine unacceptable risks and price policies more accurately, all while identifying fraudulent activity. Mitigating fraudulent property claims at the point of sale Regardless of channel, verification of application data is key to developing the most accurate premium. Identification of address discrepancies at the point of sale helps reduce premium leakage and improve profitability. With property fraud on the rise, it is critical to focus on fraudulent identity and occupancy information at the point of sale. The first step is to validate consumer-provided information correctly to make better informed decisions. A policy can only be as strong as the data it is built upon. To write homeowner policies accurately, 7 million consumers that had a mortgage were impacted in 7 MILLION CONSUMERS WHO HAD A MORTGAGE WERE IMPACTED IN THE BURST the Burst Number of consumers Number of consumers (in millions) (in millions) % Bubble (2006) 72 Burst (2009) 92% 7 8% % Current (2014) 82% Title With a mortgage Not impacted Impacted Recovered Not Recovered With mortgage Not impacted Impacted Recovered Not recovered Source: TransUnion credit database Source: TransUnion depersonalized credit database 2015 TransUnion LLC All Rights Reserved Bloomberg Business News, 8/20/ TU 2015 Mortgage Study TransUnion LLC. All Rights Reserved

5 a risk verification solution is vital to flag possible misinformation. Carriers receive notification at the point of sale if an applicant s identity, address, mortgage or property information triggers a possibility of fraud, unauthorized transaction or other misrepresentation. Analytics from the TransUnion Property Risk Verification Platform SM solution have shown we can classify 5% of new business policies as high risk from an occupancy, identity, mortgage, property or insurable interest perspective. These risks have 1.5 to 2 times the loss ratio relativity compared to the less risky 95%. A current TransUnion customer who implemented this solution was able to identify three times the claims frequency in the high- and medium-risk groups. Monitoring for changes at renewal Some solutions primarily leverage current or prior policy data. If rate evasion was practiced on a current policy, it perpetuates to the next policy. With so much at stake, actionable underwriting steps are needed to accurately identify policies with the highest potential for claims. Beyond the initial underwriting process, carriers must monitor their portfolios and address changes in risk. A TransUnion customer recently achieved very favorable, actionable results when running TransUnion Occupancy Alert against their renewal business. By addressing high-risk occupancy exposures, they saw their non-weather loss ratio decrease 29% in less than a year. 12MM NON-WEATHER LOSS RATIO INDEX 12MM Non-weather loss ratio index TransUnion Occupancy Alert implemented 29% decrease Apr 12 May 12 Jun 12 Jul 12 Aug 12 Sept 12 Oct 12 Nov 12 Dec 12 Jan 13 Feb 13 Mar 13 Apr 13 May 13 Jun TransUnion LLC. All Rights Reserved

6 Data and the future of underwriting Insurers estimate that up to 20% of claims are fraudulent, some of which are never detected. Recent trends show an increase in claims occurring for unidentified and unverified properties. Adapting to the future of homeowners insurance starts with data. The speed at which data and analytic tools are becoming available within the personal property insurance market is faster than ever, making it easier to improve underwriting performance. On an annual basis, about 3-4% of a property portfolio will have a non-weather claim that will account for approximately 50% of the insurer s total paid losses. As a result, small changes in underlying risk that increase the insurer s exposure to unanticipated losses or increase the potential for large losses could have a significant impact on underwriting performance. In fact, insurers spend millions of dollars each year inspecting properties to identify potential changes in risk to mitigate unknown exposures. In order to be responsive and optimize the consumer experience while providing accurate rates, carriers must have a comprehensive, configurable solution to detect fraud and validate rating and eligibility factors. This needs to include sophisticated subject selection with the necessary algorithms and match logic for identity, property, occupancy and mortgage. DETECT FRAUD AND VALIDATE RATING AND ELIGIBILITY FACTORS WITH A COMPREHENSIVE DECISIONING SOLUTION PROPERTY Information regarding the ownership status and use of the property Identity Verification on the identity of the policyholders GAin Insights that are: Predictive Timely Easily digestible Usable in existing processes Occupancy Insight into the occupancy status of the property Mortgage Confirmation that policyholders are not currently in foreclosure or mortgage delinquent TransUnion LLC. All Rights Reserved

7 Targeting fraud with analytics To ensure a profitable fraud strategy for improving underwriting performance, carriers should target properties with the highest potential for loss. With the right data and analytics, carriers can predict large losses those that are greater than or equal to 80% of coverage. TransUnion s performance analytics database has shown there is a 140% higher occurrence of large losses in the 1% of properties with the highest risk score. 4 The key is to use insights that are predictive, timely, easy to understand and implementable through existing carrier processes. Leveraging analytics in fraud strategy helps to more accurately identify policies with the highest potential for claims. IMPROVE UNDERWRITING PERFORMANCE BY TARGETING PROPERTIES WITH HIGHEST POTENTIAL FOR LOSS There is a significant opportunity to take action on a small percentage of your book and gain high returns. Pricing inadequacy for risk Low Medium High Inadequately priced but low risk of loss Some pricing inadequacy but low risk of loss (discounts) No issues Higher pricing inadequacy and risk of loss Some pricing inadequacy and risk of loss Higher risk of loss but priced adequately (surcharge) Highest underpriced and highest potential for unexpected losses Higher risk of loss and pricing inadequacy High risk of loss but adequately priced (poor insurance score) Low Medium High Potential for unexpected losses 4. TransUnion Performance Analytics Database: Risk Verification Platform data studies, Standard and Non-Standard Policies, Not all states included TransUnion LLC. All Rights Reserved

8 TransUnion uses property and billing addresses, tradeline, non-credit and credit inquiry data, in conjunction with powerful algorithms, to highlight and return more current, accurate and highly actionable data. Scores and results provide predictive value and actionable underwriting steps. By using property risk verification solutions, carriers can take action on a small number of high-risk applications that have a high probability of loss. These solutions help carriers quickly identify ineligible risk and avoid binding business that could be costly. Using these tools at point of sale, you can conduct a pre-inspection and complete upfront underwriting on an applicant with a high-risk score and multiple flags. At that point an applicant may decide to purchase insurance from another insurer, and adverse selection would be avoided. Responding to new market demands In today s fast-moving and ever-changing economy, predictive value and actionable underwriting steps must be further automated and implemented to meet new market demands. The competitive advantages include a positive experience for your clean homeowner applicants and a process that allows underwriters and inspectors to more efficiently and effectively leverage predictive insights to reduce risk. The data and analytical capabilities outlined here can allow you to focus on those segments with unfavorable characteristics in order to plot a new course for profitable and sustainable business as the mortgage market resurges. IMPLEMENTATION OF RISK VERIFICATION PLATFORM Risk Verification Platform output 5 10% High score 10 15% Med score 80% Pass Take action only on the small number of applications that have high probability of loss Quickly identify ineligible risks Configure output based on state, region, agent, channel, etc. Sample outcome Applicant has a high-risk score with multiple flags being generated BUT Insurer stops policy from being bound so a pre-inspection and upfront underwriting can be completed Applicant decides to purchase insurance from another insurer With Property Risk Verification Platform: Adverse selection avoided Fast-tracking to lower risk A significant benefit to carriers is the opportunity to identify and segment out the 80%+ of clean policies with no verification issues. These policies are prime candidates for fast-tracking any of the quoting and binding workflows for faster processing, as well as any efforts to improve the customer experience. These policies might also be preferred candidates to offer cross-sell or multi-line sales opportunities TransUnion LLC. All Rights Reserved

9 About TransUnion (NYSE:TRU) Information is a powerful thing. At TransUnion, we realize that. We are dedicated to finding innovative ways information can be used to help individuals make better and smarter decisions. We help uncover unique stories, trends and insights behind each data point, using historical information as well as alternative data sources. This allows a variety of markets and businesses to better manage risk and consumers to better manage their credit, personal information and identity. Today, TransUnion has a global presence in more than 30 countries and a leading presence in several international markets across North America, Africa, Latin America and Asia. Through the power of information, TransUnion is working to build stronger economies and families and safer communities worldwide. Our insurance solutions help carriers mitigate risk, improve underwriting, fight fraud and reduce costs. We call this Information for Good. Questions? For more information on TransUnion s complete insurance solutions, please visit or inssupt@transunion.com 2015 TransUnion LLC. All Rights Reserved