Unravelling the power of data analytics for effective claims handling

claims

In a recent post by Cognitive View, the company provided complaint insights to reduce claims disputes and compliance issues. 

The General Insurance Code Governance Committee (CGC) of Australia has recently conducted a detailed thematic inquiry into optimising claim decision processes. This comprehensive investigation has resulted in several key recommendations.

Initially, the CGC suggests the identification of patterns within complaint data, which could shed light on trends in claim denials. Cognitive View’s AFCA insights reveal that “Denial of claim” tops the list of reasons for customer grievances in the General Insurance sector. By examining this data and understanding the reasons behind these complaints, insurers can uncover critical opportunities for improvement. To achieve this, it is essential to standardise the complaints metadata and KPIs and leverage this standardisation to compare claims performance with industry norms.

Additionally, the CGC advocates for improvements in processes and practices, based on the insights obtained from this data analysis. It is clear that complaint analytics can pinpoint issues within the product, process, and compliance procedures. To implement effective compliance, insurers should consider integrating both process and cognitive automation. The use of AI and advanced analytics in complaint analysis can uncover recurrent issues and reveal the underlying causes, which can then be addressed through systemic changes.

Further, the CGC emphasises the need for a thorough analysis of how deficiencies in processes can lead to compliance gaps or breaches of the Code. For instance, if customers consistently struggle with understanding specific terms or exclusions in their policies, the company must review and revise its policy documentation to prevent future disagreements. An introspective approach to this issue, combined with a continuous feedback loop, can result in robust monitoring capability and help meet compliance requirements more effectively.

Lastly, the CGC encourages the establishment of clear metrics to measure the success of any improvements made as a result of data analysis. Such metrics could include the identification of patterns, understanding policy ambiguities, and recognising potential product or service improvements. This, in turn, will enable a more efficient, transparent, and customer-friendly claim experience.

In summary, the CGC’s recommendations emphasise a proactive and data-driven approach to improve claim decision processes, with the ultimate goal of reducing claim disputes and compliance issues.

Read the full post here.

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