To mitigate these risks from the beginning and to ensure customer satisfaction, the process of "Closed File Review" has been established in large insurance companies. Thereby, insurers are already screening closed claims files to discover and analyze past errors in handling. The audit of these closed cases is called “Closed File Review”. Claims reviewers manually search for files with conspicuous features that indicate anomalies. It has been proven that when different claims experts handle an identical case, a discrepancy arises in the payment calculation. This discrepancy is called “Claims Leakage”.
Claims leakage can result from the misinterpretation of policy terms or the incorrect allocation of losses to an accident as well as undetected regression cases. Additional discrepancies can occur due to subjective decisions and handling of the claims experts (soft leakage). The high volume of manual processing will result in increased vulnerability and a higher number of errors. In addition, deficiencies in the insurance company's IT structure drive discrepancies in claims management. Outdated core systems that are still in operation can also generate claims leakage because of the lack of data quality.
NTT DATA Germany launched the Claims Leakage Identification Platform (CLIP) to address those challenges. CLIP supports the insurers´ claims management in the identification, measurement, and analysis of leakage along the whole value chain with the main objective being to quickly improve their economic results. CLIP analyses include detailed, automated, and quantitative analyses of claims leakage. The knowledge of this potential can be used to address inefficient claims practices and to plan improvement initiatives within the claims process.
NTT DATA Germany also provides natural language processing (NLP) capabilities to increase the closed file review process's automation potential The NLP mines the taxonomy and ontology of the submitted documents and stored data, it can automatically filter key phrases to find patterns and associations. NLP is not only useful for filtering and finding striking claims files, but it can also be extended to detecting future risks, identifying fraud signals, speeding up processing, and improving outcomes. The natural language processing ensures a high automation potential for the assisted closed file review.
The automation of the closed files review process frees up employee’s capacity increasing efficiency: processes are optimized, and training is provided based on the findings of the closed file review. This ensures that a standardized procedure is used by all claims handlers. A fast and efficient discovery of claims leakage also leads to significant cost savings. The closed files review can be performed 50% to 80% faster by using CLIP. Practical experiences have shown that insurers are facing an average cost-saving potential of 6% to 12% for motor insurance. This potential reaches 18% in home insurance Line of Business.
Across the insurance market, Claims represent the insurer's largest cost center. Then claims payouts and claims settlement costs accounting up to 80% of the insurer's revenues. Thus, it is even more important that insurers position themselves in a cost-efficient manner. The need for smart solutions, including a high amount of automation potential, is more important than ever. By utilizing the Claims Leakage Identification Platform, which now includes the capability of automated claims leakage recognition, insurers can optimize their claims handling processes, and reduce claims leakage that resulted from inefficiencies in the claims process and thus, stay competitive in the insurance market.