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Adoption of predictive analytics can help organizations to have competitive advantages in terms of cost, customer relationships (customer satisfaction), and market leadership.
Predictive analytics will empower the insurers to understand their customer profiles accurately, which can be used to provide highly tailored and personalized services across sales, service and marketing channels.
The claim handling processes are much simplified and insurers can provide fast track claim settlements for low risk claims, directly resulting in increased customer satisfaction and significant savings in claim handling costs.
The policy risk scoring will enable insurers (Actuaries) to accurately determine the premium rates, which can result in improved overall profitability of the business.
A well modeled predictive analytics can also help the insurers to accurately determine the claim subrogation success model and hence reducing the overall liability of the claim (by increased subrogation recovery), which can result in increased profitability. Such models can also help to improve accuracy of claim reserves.
Most importantly, the predictive analytics can reduce the operational costs, in policy cycle management and in claim handling operations (loss to expense ratio), and such savings can be passed on to the customers, in terms of lower premium rates and faster claim settlements
Focus Areas
The following discussion of applications of predictive analytics focuses on the core functions such as marketing, underwriting, and claims
Marketing
Property- casualty insurers can use predictive analytics to analyze the purchasing patterns of insurance customers. This information can be used to increase the marketing function’s hit ratio & retention ratio
Underwriting
Insurers can use predictive analytics to filter applicants who do not meet a pre-determined model score. This type of screening can greatly increase an insurer’s efficiency by reducing the employee hours it may have spent researching and analyzing an applicant who ultimately is not a desired insured. If an applicant’s model score is sufficient for consideration, then the model score can be used as a rating mechanism on which the insurer can base a variety of price/product points
Claims
Insurers can use predictive analytics to help identify potentially fraudulent claims. It also can be used to score claims based on the likely size of the settlement, enabling an insurer to more efficiently allocate resources to higher priority claims
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