Improving Claim Processing

Efficient claims processing increases insurance companies' profitability and policyholder satisfaction. Effective claims handling is connected to effective insurance fraud detection and prevention, as most frauds occur at claims processing-related times. Around 90 per cent of claims handled are regarding customer problems, such as tragic incidents. As a result, most customers consider claim processing effectiveness as a criterion for switching providers. Several technologies directly improve claims processing. Such technologies facilitate and improve particular claims processing steps.

Chatbots

NLP-driven chatbots facilitate the FNOL and payment arrangement claims processing steps. Chatbots can also be used in an insurance company’s customer service, website, or mobile application. They can be policyholders' first point of contact when they want to make a claim. They guide customers to take videos and photos of the claim and inform them of the required documents they need to submit, speeding up the FNOL submission. Chatbots also help insurers by contacting policyholders to arrange payment and automating customer relations.

It is essential to note that not all customers prefer to contact chatbots for claims processing. For example, many commercial insurance customers choose to be closely connected with brokers. Moreover, depending on the claim level, customers may need human contact. Depending on the customer segment, claims are handled through chatbots, improving customer retention.

Optical Character Recognition (OCR)

OCR is another NLP-based technology extracting meaning from handwritten documents and is used to categorise them. This improves the initial claim processing and policy claim processing check steps. The initial investigation and the policy check involve processing handwritten documents, including witness and policyholder statements, police and medical reports, etc. Insurers can automate the data extraction from such documents and focus on the claims processing parts requiring human intelligence through OCR.

Computer Vision

Computer vision models obtain results from visual inputs such as images and videos to assist with the initial claim investigation step. Computer vision models can assess the loss cost by evaluating data from videos and images captured by policyholders or claims adjusters. This aids insurance company in predicting their liabilities and managing their financial resources accordingly.

Some insurance firms have already started using

autonomous things (AuT) for the initial claim investigation. The intelligent drone, equipped with computer vision models, examines the insured object. Today, such tools are rarely used in insurance practice but expect more intelligent drones performing claims investigations in the near future.

Advanced Analytics

Advanced analytics are algorithms helping users better predict the future. Such tools identify and interpret correlations and, thus, are useful for the initial claim investigation, policy checking, calculating payment to a customer, and claim processing steps.

Insurers can use adjusters’ and professionals’ reports as input data for advanced analytics to predict actual claim costs. Advanced analytics are effective fraud detectors as they identify patterns between fraudulent acts. Behavioural analytics, in particular, can assess whether or not the claim complies with the terms of the policy. Such tools check to browse histories, click locations, etc., helping insurers determine if policyholders’ claims are relevant or not. As fraudulent claims cause significant expenditures, it is imperative to understand the technological devices available to improve claim processing methods.