Managing health insurance claims - a game of Whac-A-Mole?

Every day, insurers work through thousands of individual claims for services provided by a complex network of providers to identify claims overpayment, also known as Fraud, Waste and Abuse / Errors (FWA). This process is complex and demanding and, despite heavy investment to reduce FWA, many insurers are often dissatisfied. Some in the industry akin this process to the game of Whac-A-Mole, where insurers identify an issue one day only to find a different issue emerge the next. 

FWA is estimated to range from 3 to 10% of all claims paid, and even more in some markets.

Accelerated digitalisation as a result of the pandemic has driven a wave of consumer expectations for instant gratification. Insurance policyholders today expect quick, seamless, and positive interactions with their insurers - from the point of purchase to claims payment. If those expectations are not met, consumers will not hesitate to move on.

Customer acquisition in insurance is estimated to cost seven times more than customer retention, so naturally, insurers turn to claims triage and automating claim payments to meet this expectation and manage operating costs. Delivering great customer service outcomes requires more than artificial intelligence to make automated decisions. Claims assessors need the best analytical insights to enable them to confidently and quickly make the best decisions.

Claims triage rules can improve service times and address some elements of FWA. However, the underlying environment is highly complex and dynamic. In addition, we operate in an ever-changing world of best practice treatments and financial incentives for individual service providers as well as sales agents. To address this, insurers need much more than a claims rules engine to assess individual claims; they need to apply analytics to understand all aspects of the environment, each service provider, and constantly update the triage rules for individual claims.

Although effective risk scoring individual claims is an essential capability, it is not as easy as it sounds.

There are many interrelated risk factors to consider, including less obvious patterns in the behaviour of individual customers, doctors, service providers, and sales agents that emerge and change over time. Only when we consider the individual and combined risk factors for each claim, can we effectively triage every claim.

These risk ratings need to be dynamic – they must constantly learn and adapt to changing clinical environments and behaviours of all participants. Rules engines can become a maintenance nightmare as the number of rules to make good triage decisions quickly goes from hundreds to thousands. Machine learning models that replicate claims decisions largely embed FWA by speeding up existing decision processes while the world around us changes.

The deployment of an intelligent analytics platform to understand this ever-changing environment is essential. Not only does this ensure greater accuracy in triaging claims, but it also provides claims accessors with risk insights specific to every claim. This use of advanced analytics supports claims assessors to make good quality and timely decisions, leading to increased customer satisfaction. Swiss Re's Impact+ Medical Intelligence platform does precisely this by combining the best medical expertise with analytical models in real time.

Claims triage is just the first of two challenges when tackling FWA. To identify which service provider has elevated FWA, insurers also need to trawl through massive amounts of claims data to look for trends and outliers. 

Managing the integrity of all elements of your medical network requires a team of professionals armed with the best analytical intelligence. A comprehensive risk score for each claim can be aggregated to rate the riskiness of each component in your network, including doctors, medical service providers, individual customers, corporate plans and sales agents. Afterall, if one service provider routinely has high risk claims then that must be investigated. This process of continually identifying the weakest/poorest performing parts of your network and influencing behavioural change can substantially reduce claims cost over time.

Failure to use advanced analytics to spot issues early and respond effectively can ultimately cost insurers tens of millions every year. We've seen FWA of individual providers, trends in medical practices and abusive behaviour by sales agents go unnoticed for years until it is widespread and visible for all to see in the insurer's results. 

At Swiss Re, we aim to help insurers proactively manage issues as they emerge and shift the dynamics back in favour of closing the Protection Gap through innovative and valuable products delivering better customer experiences.

Please contact us if you'd like to find out more about Swiss Re's Impact+ platform and the opportunities for you to efficiently deploy advanced analytics.