Insurance industry depends on loads of data to structure and decide on shaping their policies while adhering to industry rules and regulations. This makes the sector heavily dependent on big data, predictive analysis to incorporate new changes in policies and ideas.
Most of these data are collected from multiple sources and channels including websites, social network channels, live chats, third party sources and agents. The massive data flow is raw, unfiltered and unstructured.
The information collected includes several surveys, customer’s current insurance policies, needs and expectations, analysis of results from surveys, related interactions between people in social-networks and can come in the form of images, text documents, and videos amongst others. The data has to go though several stages of cleansing, consolidation, storage and analytics before it becomes machine readable.
Processing the huge volume of data on a day to day basis is a tedious, time-consuming affair for the insurance companies. AI could just be the game changer here facilitating ease and speed in this process in the following ways:
- Organizing and structuring the data for agents
- Help agents in making correct decision through predictive analysis
- Help in detecting frauds
- Better quality service
AI technologies are coming in handy for many insurance companies to help them make the best insurance policies. Over 50% of the top 20 insurers in the US use machine learning technology offered by Captricity, an AI start-up, as insurers attempt to reduce their reliance on paper and legacy processes.
Here are some of the ways AI is helping the insurance companies:
Automation and predictive analysis
Insurance companies have to go through several layers of data collection, queries to specific clients, filling up of forms, analyze consumer behavior, understand consumer intent, provide customized solutions, process claims, underwriting etc. All of these are strenuous and time consuming. With automation, there are sophisticated ways to interact, question, and deal with paperwork.
Additionally, automation is enabling analysis of consumer behavior pattern, thereby reducing time and effort to collate various data. Machine learning can successfully complete tedious cognitive tasks and are better enabled to disseminate information at a much lesser time.
Streamline data and risk analysis
AI can collect data, study consumer pattern and identify cases that involves higher risks. Constant machine learning ensures rapid pattern spotting, identifying big losses, litigation, and expenses management through complex algorithms that compare information gathered from clients. AI can make recommendation within seconds for agents thereby saving time while ensuring accuracy.
Provide customized solutions: Text Mining or Natural Language Processing (NLP)
Insurance agencies are set to benefit massively from Text Analytics, Text Mining or Natural Language Processing.
As per Oxford definition, Text Mining is, “the process or practice of examining large collections of written resources in order to generate new information.”
Natural language processing (or NLP) is a component of text mining that performs a special kind of linguistic analysis that essentially helps a machine “read” text.
It uses methods like automatic summarization, part-of-speech tagging, natural language understanding and recognition.
Companies are now relying on virtual agents and NLP to ensure more value added talks, improve services, solve external and internal business problems and also use customer sentiment analysis to improve customer experience.
Chat bots help in analyzing customer agent interactions and further analyzing customer sentiment to a product.
Customer Experience
AI can ensure better customer experience on many levels by saving time and giving accurate decisions for an insurance company and their consumers.
According to one survey, most customers don’t have an issue with interacting with a bot. As per data, 74% of consumers welcome insurance advice that are computer generated and 78% of consumers don’t mind taking investment advice from a virtual assistant.
Chatbots and messaging apps would stay to help resolve claims and settle queries. AI is being used to improve this process and move claims through the system from initial report to communicating with the customer. These services are round the clock, 24-hour-support that saves time, cost on human resources, plus providing zero-error report.
Insurtech, said to be the next big thing in insurance innovation — a fusion of insurance, health and wellness, and technology with various insurance companies working in tandem with such firms that enables rapid innovative engagement models with customers to ensure customized and personalized expectations of each consumer.
Underwriting made easy
Underwriting is one of the most crucial segment of an insurance company that involves evaluating risks and exposures of potential clients. The analysis is used to set premium pricing for insurance policies, amount of insurance cover the client should receive and if the risk is worth it.
AI is accelerating the speed to access lengthy history and view complete picture of applicants and analyze information while providing fast-track solution to underwriters.
Further, AI is actively being put to use in disease management programmes.
Streams of information using algorithms and machine learning are being converted to actionable insights using AI. Medical and non-medical data are providing precise underwriting while ensuring healthier lifestyle of the insured.
Additionally, fight fraud
A recent study found that nearly 80% of insurance executives believe artificial intelligence will revolutionize the way insurers gain information from their customers, with more than half saying the biggest benefit is being able to leverage better data for improved insights into the customers.
Self-learning machines can be of great use in detecting fraudulent claims as AI technologies can accurately access historical data and predict future damages and associated cost detection.
For instance, car insurance companies are leveraging on AI to detect fraudulent claims on vehicle crashes or collisions and detecting good drivers to ensure minimum cases of road accident claims and improving premiums across the board for their customers.
Another example is of a Paris-based start-up, Shift Technology, which uses AI to mitigate insurance fraud, announced a $28 million series B funding round in 2017 to grow its business. This shows that even VCs are keen to get on board.
Finally, AI has increasingly expanded scope for tech-savvy professionals working for the insurance industry by ensuring more efficiency and accuracy at the core functions in the company, further freeing up insurance teams to focus on more creative strategic work.
