Challenges of Claims and Frauds in Insurance (III)

Third part of this series will continue with challenges in claims processing in insurance industry.

Claims processing is a comprehensive process of handling and managing insurance claims made by policyholders and includes all the steps during which the insurer checks the necessary information about loss, policy and the event to calculate and pay out its liability to the policyholder. The goal of claims processing is to assess the validity of a claim, determine the coverage and benefits payable and facilitate the payment of settlement to the policyholder efficiently and accurately.

The fact that insurance claims is of a more than considerable size, e.g., more than 530K millions dollars claims were done in US alone only for Life Insurance in a single year (there are lots of other data available to cement the size of claims), it is not untouched by its own challenges.

• Claim registration process involves huge amount of paper work and lengthy process at times which besides being data intensive, is repetitive as well.

• Claim settlement can be time consuming for both insurers and customers

• Claim settlement and processing can be error prone with much human intervention involved at various stages

• Frauds during claims

• Claims backlog could be another challenge for some of the insurers

How AI Helps in Addressing Claims Challenges

Process Automation: It will help in easing the process claims registration and settlement through automation of many of the steps which need human achievements. RPA can automate repetitive and rule based tasks and processes in claims processing.

Data Integration and Analytics: With the help of AI and ML algos, data from various sources can be easily accumulated, integrated and analyzed which insurers can use to derive fruitful information for themselves.

Claims Segmentation: AI algorithms can help segment claims cases by complexity using factual and predicted claims characteristics. Based on this segmentation, claims can be assigned to specific downstream handling processes- either one of the fully digital self-service journeys or a claims handler for more complex cases.

Predictive Analytics: Prediction of claims characteristics. Leveraging the benefits, historical data and patterns can be analyzed to predict potential claim risks and hence mitigating the associated claims. AI can help infer as-yet-unknown characteristics of a claim, such as the likelihood of fraud, total loss, or litigation, to speed up its downstream handling.

Chatbots and Virtual Assistants: AI powered chatbots can handle customer inquiries, share real time updates with them or claim process and status and provide support 24*7, thus enhancing customer experience.

Computer Vision: Computer vision would help analyzing the images and videos related to claims thus facilitating faster assessments.