Big Data in Big Insurance

Insurance companies, over the decades, have been overwhelmingly dependent on credit scores for judging customers’ credit worthiness. Analysis of credit scores are in practice long before big data acquired a firm foot in the consumer analytics industry. However, they have often been criticized of being biased against the most credit-worthy individual. Not neglecting the obvious imperfection of these credit score based actuarial algorithm models, to make nuanced decisions regarding the credit risks of their customers, insurers have resorted to using big data. There may be certain variables incorporated in credit scoring algorithms that overstate customer dependability. A person with a good credit score, even if he faces a couple of repayment defaults due to sudden financial breakdown, would have his current credit score unaltered. Several other reasons have made insurers skeptical of using credit rating in the era of big data. With the help of big data Insurers now recognize that credit based insurance policies have increased the risk of unjust racial profiling. Limitations and fallacies of credit-scoring are being continually exposed by analytics modeling compelling insurance actuaries to upend existing policies and have greater reliance on data-intensive approach.