2013 Predictive Modeling Benchmarking Survey Infographic - Towers Watson


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This infographic reflects the Towers Watson's fifth annual Predictive Modeling Benchmarking Survey and examines how North American property & casualty insurers are embracing predictive modeling.

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2013 Predictive Modeling Benchmarking Survey Infographic - Towers Watson

  1. 1. 2013 Predictive Modeling Benchmarking Survey P&C Market Leaders Rely on Data-Driven Product Strategies North American P&C insurers are keenly aware that predictive modeling offers a competitive advantage. At least 85% reported a positive impact on rate accuracy, nearly 80% on profitability and at least 74% on loss ratios. Predictive modeling use increased in 2013 for nearly every line of business over 2012. Commercial lines Nearly half of commercial carriers are exploring or already using models to help flag claim fraud, set more accurate case reserves, evaluate claims for litigation potential and triage claims for adjusters. Many carriers supplement modeling with internal non- rating variables to improve underwriting risk selection and price accuracy. At least 73% use predictive models to revise underwriting rules. Commercial lines carriers leverage product comparisons as a key component of their competitive market analysis (CMA). What We Found Why You Should Take the Next Step What’s on Their Minds? Who’s Doing What Personal lines 45% of personal auto carriers use or will use usage-based insurance (UBI). 59% of personal lines carriers are exploring or already using models to detect potential claim fraud. 95% of personal auto and homeowners carriers use or plan to use predictive models for underwriting and pricing. Qualitative, quantitative and product reviews are essential elements of competitive market analysis for personal auto and homeowners carriers. Insurers have a variety of concerns about underwriting. Personal lines carriers worry most about competitive alignment, while commercial carriers look more at pricing discipline. Just the Start Our survey finds strong evidence that the benefits of data-driven analytics have not yet been fully explored, especially by smaller carriers. Discipline in pricing execution Geographic segmentation Monitoring/Metrics Class segmentation Competitive alignment Greatest level of concern with current underwriting approach Personal lines Commercial lines 70% 31% 49% 48% 49% 46% 46% 21% 25% 63% Percentage not applying claim-related predictive analytics for these purposes Small carriers Large carriers Detect potential claim fraud Triage claims for adjuster assignment Evaluate claims for potential litigation Case reserving 77% 30% 35% 48% 57% 92% 92% 92% Don’t Be Left Behind: Take Action 85% of small personal lines carriers say predictive modeling is required to compete in their main business lines, and 61% of small commercial lines carriers say there is a competitive advantage for early adopters. Serious market players will: Assess their current programs Commit to finding new ways to leverage data-driven analytics Act to create or improve a flexible predictive modeling framework For more information, contact: Brian Stoll | +1 860 843 7129 | brian.stoll@towerswatson.com or Klayton Southwood | +1 309 452 6845 | klayton.southwood@towerswatson.com or visit towerswatson.com/pmsurvey. Personal auto Homeowners Workers comp General liability — CMP/BOP Commercial property/ CMP/BOP Commercial auto Personal lines Standard commercial 7% 17%7% 27%24% 7% Percentage currently modeling 80% 62% 47% 33% 32% 28% Increase in 2013 Renewed commitment to predictive modeling could positively impact both top- and bottom-line indicators. Top line Personal lines Commercial lines 25% 52%48%45% 35% 39% Expansion of underwriting appetite Market shareRenewal retention Rate accuracy Loss ratio improvementProfitability 96%85% 78%80% 74%80% Bottom line