What AI can do in insurance

Insurance is one of the most conservative branches of the financial market. Perhaps that is why many insurance companies were in no hurry to introduce new technologies, even when colleagues in the financial market had already successfully tested them. But a few years ago, the most advanced insurers nevertheless began to introduce various InsurTech solutions, including ai in insurance industry and machine learning.

Main features

Insurance begins with the search for clients, which the "machine" carries out no worse than a person. AI finds users on the Internet who are interested in buying, for instance, CMTPL policies, and makes them a targeted offer. The artificial intelligence is based on search history, data from social networks, and another open and closed sources available to it. He helps not just the security corporation in promoting services, but also the client - in auto-filling the insurance application, if the case occurs, for example, on a partner site.

A separate "ocean of possibilities" is chatbots and voice assistants. They provide instant communication with both potential and existing clients. As they learn, technologies are becoming better at recognizing the needs “at the other end of the line”, giving more accurate answers and building a correct dialogue. Voice robots of the latest generation are sometimes indistinguishable from a real interlocutor. Such "assistants" do not get tired and do not get annoyed, do not require a salary for their work and, if necessary, process thousands of requests per day. They have beautiful voices and impeccable diction. They are improved to such an extent by machine learning that they eliminate the need for insurance firms to recruit a large and expensive call center team. Such optimization, of course, in the future changes the attractiveness of insurance prices for consumers.

AI tasks

AI supports insurance organizations in the scoring and onboarding period. With its maintenance, insurance corporations give a reasoned judgment on admitting a patient for protection plus set a reasonable price. Insurers use machine learning to evaluate the likelihood of consumer fraud at the moment of purchase and subsequent monetary damages. The calculation takes into account all data regarding the customer, which he reports about himself, and data from other sources. Arguments “against” the policyholder can be, say, the provided inaccurate data, bad credit history, or data regarding the initiated legal claims. The algorithms for searching and analyzing data can be different and are limited only by the imagination of the developers and the tasks meeting the insurance company. Data science consulting firm can describe the process more.

Machine learning benefits you get:

• knowledge that was not previously noticed; 
• accurately evaluate opportunities; 
• foretell consumer practice. 

Technologies, although their integration is not affordable, subsequently greatly avoid the expenses and circumstances of the protection business. AI has been strongly related to record administration, claims settlement, and constant action. All this with minimal or no human involvement. The automatic adjustment involves taking a digital application, checking security coverage, examining the completeness of submitted papers, and indexing needs. 

One of the tasks of AI is to identify subtle relationships between unprofitableness and hidden factors. Artificial intelligence can collect and systematize a large amount of information about the various characteristics of the insured objects and their owners, as well as regarding the developments taking place with them.