Consulting and customer service
The claimed ability of AI to perform creative, human functions excites the imagination of many researchers. Representatives of Google Brain posted a publication in which they described how they taught the program to gather information on a given topic, analyze, and summarize it. At the end, the artificial intelligence forms the result in an article format. Thus, students can count on help in research paper writing. Using a virtual assistant for insurance opens up new business opportunities. Examples of the use of artificial intelligence include the implementation of chatbots for customer communication, customer-driven insurance claims, or internal operations, including calculations. Processing claims for insurance claims is one of the most important functions of an insurance company. The speed and convenience of accepting applications directly affect the reputation. By sending requests via the chatbot, the client does not waste time on the way to the company’s office and processing documents. And the business gets the opportunity to standardize this process and store documents in an easy-to-use format. AI helps insurance companies during the scoring and onboarding phase. With its help, insurance companies make a reasoned decision about accepting a client for insurance and assign a fair rate. Thanks to the user segmentation function, chatbots can implement an individual approach for each client. From providing basic insurance services to personalized offers and discounts. That is, artificial intelligence can propose the best offers for the customer based on their profile and input data. Chatbots can educate customers. The bot answers basic questions, such as how to take out insurance, and then shows different insurance options. There are several AI programs from Great Learning that you can enroll yourself in to learn more about AI applications in the insurance industry. A recent study found that 74% of customers would like to use chatbots to message and receive computerized advice. Messaging is the preferred channel for consumers worldwide. Automation brings efficiency.
Handling claims and appeals
AI can help create structured sets to organize claims data and process them quickly. Intelligent solutions can recommend templates for incoming claims. This helps insurers collect all the data at once. Artificial intelligence devices can convert speech-based claims into written text. This makes it easier and more efficient to document and manage claims. Machine learning helps to capture information that was previously overlooked. Insurers will be able to assess risks and predict customer behavior with great accuracy. The technology, while not cheap to integrate, saves the insurance company a great deal of cost and time later on. AI has been successfully used in document management, loss adjustments, and even litigation. All this with little or no human involvement. Automated settlements include accepting a digital claim, verifying insurance coverage, analyzing the completeness of documents provided, and indexing losses. AI is particularly useful when it is difficult to provide an object for inspection or to confirm certain circumstances. For example, neural networks used by insurers simplify and automate the process of self-inspection of a car. The technology also allows for remote estimation of damage, identification of hidden damage, clarification of information about the events that occurred.
Fighting fraudsters
In the United States, fraudulent claims cost $40 billion annually. Namely, to weed out fraudsters before an insurance policy is issued. The AI can study information about the client, solvency ratings, social connections, history of calls to fraudulent numbers, and other data. And based on that, it can assess the trustworthiness of a particular person. The robot can distinguish tampered insurance cases. Algorithms record a suspicious claim and flag it for further investigation. Many companies implement analysis of losses similar in profile to fraudulent by the presence of non-obvious connections between participants in accidents, vehicles, or insurance contracts. By the way, in this case, AI is useful not only for the insurance company itself but also for “good customers”. After all, the prices of insurance products are formed based on the loss ratio of the company’s portfolio. This means that the less an insurance company loses on fraudulent actions, preventing them in their infancy, the cheaper its products can be.
Personal tariffing and risk accounting
A classic example of using AI for more efficient personal billing is the analysis of telematics data. This data is obtained by using special complexes installed in insured cars. Telematics collects real operating factors in the form of clear data. These include speed compliance, sudden acceleration/braking, nighttime operation, mileage, total driving time. As a result, calmer drivers who drive less often can get a better fare. AI is used in building rate models and adjusting the cost of a policy for a particular customer. For example, in auto insurance, AI applies coefficients considering a driver’s age and experience, accident-free driving record, place of residence, time of year, and traffic situation. It also considers the state of the market, the level of wages in the region, and forecasts of customer outflows. Based on the instant analysis of both linear and non-linear relationships, a real personalization of the fare is made. We can observe the usage of AI in customer service in VHI. Telemedicine applications have recently become an almost integral part of it. They allow not only video consultations from doctors but also act as a kind of doctor in your pocket. The app analyzes the client’s state of health in real-time with the help of fitness gadgets and data that the client enters himself. The gadget prompts the client when something is wrong with his pulse, blood pressure, or other indicators. It suggests changing the daily regimen, adjusting the physical activity, and making an appointment with specialists. All this already improves the user experience. It also makes it possible to individualize rates for regular customers.
InsureTech is a golden opportunity for insurers
The number of business processes in insurance that apply AI and machine learning is constantly expanding. Comprehensive IT platforms for insurance business management are appearing. Thanks to this, market players are improving their production cycle. And clients receive better service and favorable rates. The insurance industry is on the threshold of digital technology. The growth of InsurTech projects poses a serious threat to traditional insurance. But it also provides a great opportunity to leverage cutting-edge technology to meet new challenges. By working alongside InsurTech rather than against it, insurers can thrive in the digital age if they act decisively and quickly. Here are some worth projects in the insurance industry: TRACTABLE: a deep learning visual inspection tool that can work more accurately, cheaper, and faster than humans in analyzing images before assessing the damage. It is currently used by global insurance companies such as Ageas, Covea, Tokio Marine, and Talanx-Warta. SPIXII: the company offers chatbot solutions that automate dialog processes. By doing so, it provides a scalable and secure way to ensure proper customer service while improving the efficiency of business operations. Reducing your risks and maximizing your income is, as you know, the main goal of any insurance company. But how to do it without having enough information on the client? At what price to offer insurance? SOCIAL INTELLIGENCE offered banks and insurance companies a unique solution. It claims that 55% of the new generation is willing to share their personal information on social media. That’s why the startup offers to assess insolvency and other risks by analyzing a customer’s social media behavior. At the request of an insurance company or bank, it can answer questions related to the client’s health, his addictions to alcohol and drugs, and tell about life events and professional achievements.
Summing up
How long will it take the insurance market to reach a new technological stage? It is difficult to give a definite answer. But, many market participants started more or less actively implementing AI in their operations about three years ago. The best way to stay up-to-date with the constant evolution in this field is to choose a Great Learning AI and Machine Learning Course that fits your career needs.It will probably take longer to develop and widespread use of more complex scenarios. Especially considering all the difficulties that the business faced in 2020. This can be compared to cryptocurrency and bitcoin. Until recently, people did not understand what it was and did not believe in their effectiveness. But today many industries are already implementing this technology, and sophisticated people are actively using the best crypto trading bots.
