Unstructured data can be your biggest challenge - or your greatest opportunity. Managing raw datasets can feel as challenging as playing golf in a hurricane.
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The decision for an insurance company to build its own software platform is akin to a bakery deciding to start its own farm to grow and harvest wheat to produce its own flour.
While vertical integration might make sense for a large organization with a thousand bakeries (or a bakery mogul with a green thumb), it's not a viable strategy for most insurance companies. Read on to know why.
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STP systems are designed to work within a specific set of parameters, which can limit their flexibility. If any changes to the data being processed or the analysis are required, the system may only be able to accommodate them with significant reconfiguration.
With STP, the entire process is automated.
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Despite attempts from several InsureTech firms, the AI & ML solutions available today are mainly effective on the more standard formats, with some obligatory mundane pre-processing. Yet, most SOVs are still cleaned manually by offshore teams. Why?
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Ugly Data (semistructured data) is still a massive problem for insurance companies today. Relying on a moderately successful solution to standardize this semi-structured data data is extremely risky.
It's not as easy as solving a Rubik's cube. So what would it take to create this truly comprehensive yet seemingly impossible solution to the SOV problem?
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There are several initiatives an Insurance company can take to drive higher profits. They can increase Net Income, lower their Combined Ratio, or increase their Policyholder Surplus.
But none of these are by any means enough. At the end of the day, sustainable and assured profit boils down to just these 5 things...
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