Artificial intelligence (AI) has emerged as a disruptive technology that has made automation in various levels possible. Any industry that involves amassing large volumes of data and analysing them would benefit from a touch of AI. Insurance analytics solutions of today are the perfect examples of how AI can be used to add to many financial sectors.
AI in insurance analytics – an overview
There are various applications of analytics in the insurance industry. As a preliminary aspect there is the sale of various insurance products to the relevant customers. Then comes the background analysis that goes into identifying the different types of services to add to the scope. Finally, there is the most crucial application, the processing of insurance claims. In all these aspects AI can be used to provide faster and more accurate analysis of gathered data. This strategy would keep the best interests of the insurance company as well as the customers.
Why insurance companies actually consider AI integration
Optimized products and services
As more and more fintech services have now become digital, customers find it easy to compare the various insurance companies and the policies offered. As the competition is stiff, if you really wish to make a sale happen, you should have a portfolio of products that are designed relevant to the market demands. Traditional insurance policy structures might not always work with the current generation of insurance policy holders. To take cues from historical data and fine tune the policies to create products optimized for the users, AI comes in handy. Predictive Analysis is a part of the broad spectrum of AI technologies. Based on the common customer behavior, it helps insurance companies frame the right insurance policy pricing.
Insights for claim processing
The role of predictive analytics and AI in general, does not end with putting the products out there in the market. We live in an era where insurance frauds are very common. As most processes have now been digitized some of the insurance policies can be issued online entirely. Having a fake digital identity is easy for some people. So, while onboarding a new customer, AI can be used to verify the submitted proofs and look for gaps that could indicate credibility issues. These can observe customer behavior from the moment the interaction begins. All through the policy tenure if any malicious pattern occurs, the system can give timely warnings. This helps insurance companies take timely action. Finally, there is the step where a policy holder submits a claim request. Fraudulent claims are easier to identify with smart analytics tools. Behavior analytics and other strategies come in handy for ruling out false claims. At the same time, for genuine claims, these systems shorten the timeline for processing. Faster claim processing means better reputation for the firm and better convenience for the customers.
Augments employee productivity
Insurance company personnel are often busy with mundane paperwork and data analytics jobs in a conventional system. When AI lifts this burden off their shoulder, they are free to focus on better value tasks. Fatigue errors in the case of complicated claims are also less with this. Data-driven decision making becomes a reality and this can greatly alter the workflow in an insurance company. One other notable advantage here is that AI in insurance analytics solutions will also provide unbiased claim proceedings.
Every single decision that the system makes will be based on the historical data fed as well as the rules that the company defines. This means that better decisions are possible by learning from past mistakes. This can greatly reduce the workload of insurance company employees. Customer interactions are quicker and more valuable as the system manages to capture customer information. This data is very useful for the employees to understand their policyholders and thus provide them better service.
Besides all of the above mentioned AI benefits in insurance analytics solutions prioritising the claim requests is another advantage. This way, AI makes processes more user-friendly for the genuine insurance holders and the system more reliable for the insurance companies. On the whole, AI in insurance analytics can save both time and money and thus lead to more flexible and relevant policies.