In Claim Management Best Practices, Technology

Since the recovery of the financial meltdown in 2010, the IT industry has experienced a steady growth rate of 6% per year. This year, in 2016 the rate of increase is expected to taper to 2%. This shift reflects an emerging trend in the marketplace of IT investment; while businesses are still looking to the IT industry for vital technological solutions, they want more than mere hardware, software, and tools. Companies are looking to invest in technology that offers analytical solutions that helps them to optimize business practices.

Many businesses have silos of data stored away that contain troves of valuable information. Yet, without an analytics solution in place to systematically assess and use this data to inform strategic business decisions, this information remains an untapped resource and is ultimately useless to the business. Choosing to implement a technology solution that analyzes both structured and unstructured data opens opportunities for businesses to improve bottom line, particularly in the world of insurance.

You may be wondering – so how exactly do analytical solutions relate to me as an insurer?

Well, experience tells us that, as an insurer, you are focused on optimizing the claims process and ensuring no resources are wasted during the claim lifecycle. Analyzing historical and current claim data will help you more effectively ensure that all claims are assigned to the right person at the right time for timely processing and maximized productivity.

Analytics and Low Hanging Fruit

Analytics drives business decisionsAs an insurer, low-risk claims probably come through your door daily. Based on industry experience, you can likely detect these types of claims straight away, determining they require little administration. Having an analytical solution in place helps you flag these types of claims during intake based on your specific tell-tale signs, and immediately route them to the correct claims examiner for timely processing. Using automated workflows to route these claims to the correct claims examiner enables you to minimize the lifecycle of a claim.

This may seem simple, but think about the effect that using analytics has on your business process:

  1.     Quicker processing of low-risk claims.
  2.     Fewer resources required to process the claim, improving your bottom line.
  3.     Improved customer satisfaction, improving loyalty and retention.

Analytics to Detect Fraudulent Claims

But what about the high-risk claims? These claims require a bit more work by claims administrators. Depending on your setup, you may even have a team dedicated to dealing with these types of claims.

Based on your business processes and experience, you already know the red flags to look out for to determine if a claim is potentially fraudulent. Using an analytical solution can help you compile and assess these red flags, to detect and signal high-risk claims up front. For example, if several claims a year come in from the same physician for the same diagnosis, you may decide to flag these claims for further examination. Or if a claimant has made a number of claims over the past few years, these claims may need further explanation.

While you may end up finding these claims are legitimate, an investigation can ensure you have made payment for a valid claim. Insurance fraud in the US totals an estimated $40million annually so focusing on claims that appear high-risk is a top priority. Without a way to analyze red flags of incoming high-risk claims, you are at risk of paying out unnecessarily, which ultimately hurts your bottom line and can affect the cost of insurance premiums for other customers.

Although overall IT investment is in decline globally, employing technological solutions that aid business development is critical in today’s competitive market. Investing in an analytical solution can help reduce business costs, improve claims processing time, reduce costs, and improve the bottom line for any insurer.

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