We all dwell upon the past, try to live in the present and worry about the future. Well what if technology can look into your past and present and predict the future and enable you to just live. Predictive Analytics can do just that and more and can make a significant difference to your business.
The Insurance industry being extremely data intensive is one of the key customers for Analytics & Big Data. In today’s times insurance companies have to deal with exponentially multiplying data by the year. Predictive Analytics too finds big opportunity in Insurance and could be one of the key differentiators between these companies. This technology is one that really fascinated me and I was really keen to understand how this works.
Predictive Analytics is basically use of certain sophisticated statistical and analytical techniques such as advanced regression, time-series model, etc. to develop models that predict future events or behaviors. The form of these predictive models will vary depending on the behavior or event predicted. Most predictive models generate a score (such as a credit score), higher the score the greater probability of the behavior or event occurring. The technology looks into data from multiple sources Data Mining is a key component of predictive analytics which includes analysis of data to identify patterns and relationships.
Well impressive though it may sound, how much of a difference can Predictive actually make? A lot actually, at least to start with. It has key applications in Underwriting, Marketing, Claims, etc. For starters, in Underwriting it offers more than automated Underwriting and Straight Through Processing and automates underwriting by applying business rules. For example, based on a pre-determined model score, it will filter out applicants who do not meet the score. It can create real-time insights, helping fine-tune products to meet evolving customer needs, predict future losses and price the products against those losses and much more. For marketers, it can identify potential customers for different product line and analyze purchasing patterns of customers and thereby increase Hit Ratio and Retention Ratio. Not to forget its biggest advantage is probably in Claims which is a key area for Insurers and it can be pretty effective in identifying fraudulent claims. It scores claims based on likely size of settlement enabling insurer to more efficiently allocate resources to higher priority claims.
Now the question of accuracy is what lingers in my mind and I am sure it does in most Insurers’ minds too. Yes technology is also not fool proof, it can make mistakes but the whole point is to minimize them and make a start for a more secure future. How good are companies doing today without it anyways? When you can at least guarantee 80-90% of the predicted output why not give it a try. Am sure as it evolves, the accuracy will only increase and in times to come I am sure it will be used to predict everything from sales to profit margins to solvency to investments etc. It could become a one shop stop for actuaries, underwriters and policymakers to help carry out their daily activities and will ultimately become an addiction.
This is the Predictive advantage that I see and I hope will be widely adopted by Insurers in the recent future. It has been accepted much more in the west but is yet to generate much interest in developing economies such as India.
Hopefully the prediction will see traction and turn into an addiction soon.
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