The insurance industry operates on a lot of data – contracts, claims, invoices, financial statements, emails, medical information, and more. Unstructured and structured information – data arrays suitable for further analysis – comes from the divisions to the head office.
The most suitable tool for working with large amounts of data is artificial intelligence. The ai for insurance companies system identifies patterns in documents, forms templates, structures information, etc. As a result, the workflow in the company is automated, and human participation is required only to control the work of AI.
Of all the qualities of intelligent cars in the insurance industry, the most relevant are:
- Data management;
- detection of cases of fraud;
- handling claims.
AI collects information from many sources: chat with customers, feedback forms on company websites, messages on social networks, emails, reports on financial transactions, and more.
The AI system determines which department of the insurance company to send the processed data to – for example, the claims department or the service department. Such a mechanism of work will lead to a quick reaction of the employee to a letter or complaint, therefore, will increase customer satisfaction from contacting the company.
Machine learning and semantic search algorithms are tuned so that the system instantly recognizes which department of the insurance service to send a letter or contract to. This process is called document routing – it saves time for employees and streamlines the process of company operations.
According to Insurance Europe, 10% of all insurance claims in European countries are fraudulent. For example, in the UK, insurance companies annually ignore payments for non-existent insured events of $ 2.48 billion, and in 2011 the French Insurance Federation identified fraudulent claims in the country in the amount of about $ 195 million.
AI systems extract data from all insurance claims or claims, determining the amount required and verifying the legality of the damages. This is how bad faith claims for monetary compensation are defined. Several decades earlier, such an analysis was simply impossible – a person performs similar tasks for a very long time, it would take people several years to find patterns or inconsistencies. In addition, using semantic analysis, AI can detect sentences in claims for various incidents that completely coincide with each other (another sign of deception).
Large insurance companies constantly work with claims, and timely responses to them are part of the routine daily activities that take about 40% of the insurance specialist’s time.
Working with claims is included in the functionality of the AI systems of each insurance organization, as is the processing of applications for medical insurance. The structure of these documents is similar, but applications contain diagnostic terminology in addition to simple text, for example, medical abbreviations and abbreviations. Machine intelligence quickly recognizes the text, classifies the application or claim by subject, and forwards it to the appropriate department.
Among other possibilities of artificial intelligence development solutions is the assessment of car damage after an accident. The AI system assesses the condition of the car, based on the analysis of images from the accident scene, links the history of payments for previous accidents (if any) to the existing case. This method of assessing damage was tested by the Belgian insurance company Ageas. At the end of the trial period of the AI system, Agean representatives reported that with the help of AI, agents significantly reduced the total time for evaluating cases, and also immediately established the exact amount of compensation payments.