Enhancing claims reserving with SmartClaim

Contacts: Simon Dean, Karim Derrick

12-12-23

Setting an appropriate reserve for insurance claims is a critical aspect of claims handling. While it’s common for claims handlers to establish a standard reserve based solely on the injury as described in the Claim Notification Form (CNF), there are additional factors to consider for a more accurate reserve assessment. In this article, we explore the significance of accurate reserves and the potential consequences of even a minor under-reserve.

The importance of accurate reserves

At Kennedys IQ, we emphasise the pivotal role of precise reserve calculations in successful claims management. A seemingly insignificant under-reserve of £1000 can lead to a staggering £5 million discrepancy across a portfolio of 5,000 pending claims. Considering the current high inflation rates and the anticipated 20% Judicial College Guidelines (JCG) update in January 2024, it becomes evident how easily claims can end up under-reserved.

In collaboration with Manchester University, we have developed SmartClaim, a sophisticated decision-making tool that significantly enhances the consistency and accuracy of decision-making within the claims process.

SmartClaim’s innovative approach

SmartClaim is meticulously crafted to empower claims professionals, functioning as a hybrid expert system that seamlessly integrates human expertise with the capacity to handle complex, non-linear relationships and navigate uncertain scenarios. This tool is enriched with expert rules and leverages cutting-edge techniques, including modern machine learning, data analytics, intelligent modelling, and decision support systems, to elevate the efficiency and precision of insurance claims processing.

SmartClaim’s impact on reserving

Kennedys IQ has conducted an extensive analysis of over 50,000 claims, scrutinizing all data points within the CNF to determine if they can collectively provide an accurate reserve for claims. While some data points, such as injury type, may appear obvious to directly influence final outcomes, the impact of factors like the accident month, age of claimant, and employment status on the ultimate claim resolution is less apparent.

Analysing each data point in isolation yields intriguing insights. For instance, when examining accident month’s correlation with claim outcomes, it is evident that claims from October, November, and December tend to settle at higher amounts compared to those occurring in March, April, and May.

However, the full picture emerges when we consider multiple data points simultaneously. For example, how does the correlation change if the accident occurred in October, there were mixed injuries, and the claimant is a minor? This is where SmartClaim’s technology excels; by employing evidential reasoning in conjunction with a belief rule-based approach, SmartClaim can comprehensively assess all data points and provide an accurate prediction based on CNF data. When combined with IQ Platform’s Fraud Detector solution, it enables the creation of an initial claims triage report for handlers before they even open the claim.

Ongoing reserving

SmartClaim is designed not just for setting initial reserves but also for refining them as anew information emerges during the claim’s lifecycle. This adaptability is crucial, especially when certain information is delayed indicating a potentially more serious claims than initially assessed.

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