TrackStar Predictive Credit Technology

Insurance fraud can be committed by either the buyer or the seller of an insurance policy.

The seller may offer policies from non-existent companies, fail to submit premiums, and churn policies to create more commissions. The buyer exaggerate claims, falsify medical history, post-date policies, sell their policy to for cash when they are diagnosed with a terminal disease, or fake their death or kidnapping. We will focus on the buyer insurance fraud in this post.

Historically, insurers have relied on linear regression of a small number of risk factors, largely reported by the policy-holder on a trust basis, to determine an insurance premium. However, a good prediction model of individual future insurance costs is becoming a business essential as competition in the insurance industry and low customer switching costs have become key drivers for insurers to build a pricing structure which covers their incurred costs.

B2C fraud includes insurance fraud, payment fraud, identity theft, etc. and reviewing claims is so time-consuming and difficult that many insurers do little more than a cursory review on small claims. Fraudsters know this and will file—and win—small claims for losses that didn’t really occur.  

Credit scoring is a statistical analysis performed by lenders and financial institutions to assess a person’s creditworthiness for mortgages, credit cards, and private loans. Credit scoring is used by lenders to decide whether to extend or deny credit.
Traditionally, a person’s credit score determined by credit bureaus is a number between 300 and 850 with 850 being the highest credit rating possible. As new types of lenders and insurers emerge, however, the traditional credit score becomes just one parameter joined with a large variety of alternative data that helps determine a person’s creditworthiness.