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Author: Ashwin Sooraj Kudwa |05/21/18

How Artificial Intelligence is Re-inventing Insurance Industry

Artificial Intelligence (AI) is transforming lives and businesses by offering personalized experiences and services across the world. It is fostering faster and accurate decision-making capability to help brands align with customer expectations.

AI systems such as Google One and Amazon Echo are becoming smarter and simpler to use. With touch screen and voice command technology, interaction is becoming easier and natural. We have been using AI systems in one way or another in our day-to-day lives and these systems are constantly evolving.

What is driving this evolution? Rapid advancements in technology, coupled with availability of enormous volumes of data, especially in the insurance domain, has sparked this evolution. Irrespective of one’s expertise with data or the domain, this data bank is too enormous for a human to navigate and it is close to impossible to identify meaningful patterns in the data. This is where AI comes into picture.

AI facilitates identification of sensible data by creating sophisticated techniques and training algorithms, thus providing us with tools to help make better-informed decisions. These decisions closely mimic human intelligent behavior to quickly solve critical business problems.

What is Artificial Intelligence?

Artificial Intelligence or AI is a broad term used to describe a group of technologies that make machines think intelligently and carry out tasks & activities at par with humans. AI incorporates the ability to carry out these activities along with other tasks at a much faster pace beyond human capability.

Artificial Intelligence in Insurance Industry

There is a lot of interest and debate surrounding AI and the insurance industry. The insurance industry has been lagging in terms of AI implementation, when compared to banking and financial services sectors. Most of the insurance companies have realized the need to innovate and identify areas of business where AI can be applied. They now utilize and embrace AI to remain competitive and be more effective in driving customer engagement and their strategic & operational business goals.

Robotic Process Automation (RPA), Chatbots and Personal/Virtual Assistants, Machine Learning, Deep Learning, and Natural Language Processing are some of the AI technologies used by insurance companies. They are utilizing these technologies to identify gaps in customer needs, reduce cost to customer and serve their needs optimally.

Furthermore, insurance executives worldwide believe that AI is about to radically reshape the industry. They also believe that AI will revolutionize customer interactions and become the digital face of the insurance brands.

Insurance solutions related to customer interactions, claims processing and underwriting rules engines are some of the promising areas that have experimented with AI technologies. Lets us see each of them in detail:

Customer Interactions:

Relationship between an insurance company and its customers is very important in this industry. Due to the traditional time-consuming processes, customers are disappointed with their interactions with executives, which often involves waiting for long hours. To overcome this issue, AI powered chatbots or virtual assistants enable users to interact directly with the business through natural, human-like conversations and address their queries in a more personalized manner. Human assistants are being replaced by chatbots to deliver fast, efficient and continual customer service. They assist customers in answering basic queries and providing guidance to identify the ‘right’ products, detect if they are over insured or under insured, find out if the correct suite of coverages are applicable to the customers’ needs and ensure proper crisis cover.

Chatbots use Natural Language Processing (NLP) rule-based algorithms to assess the customer needs based on question and answer patterns related to the customer location, historical data, etc. They answer the customers in a natural human-like language with great accuracy. Highly advanced chatbots do much more than chatting during their interaction with customers. These virtual assistants calculate rates and carry out rate comparisons, accept insurance renewal payments and sell policies too!

As AI technologies mature, the chatbots will be capable of serving most of the customer needs, leading to happier customers. Customer comfort and preference for using these chatbots is driving business opportunities for insurance companies.

Mindtree’s conversational chatbot, MACAW provides quotes for life insurance products using Skype messenger. Mindtree also provides a ‘sales bot’ for auto insurance. Chatbots can be used to address the First Notice of Loss (FNOL) in claims processing, wherein customers submit their claims by answering few questions and sending photos of the damaged property. The chatbot then runs some algorithms that include referring its past data of customer claims and executing fraud identification algorithms to determine the correct cost of the claim settlement. It also helps the customer to estimate the cost of the damage by providing details of the approved vendors. Some chatbots also enable customers to submit a video of the FNOL. All of this without a claims adjuster!

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Underwriting Rules Engines:

The underwriting process (handled by agents and underwriters) has traditionally been slow and time-consuming, thus affecting both the insured as well as the insurer. In the past, insurance underwriters’ reliance on information supplied by their potential clients has contributed to inaccurate risk assessment. Machine Learning and specifically, NLP can scan a customer’s social profile to gather information, find trends & patterns and provide a better indication of the customer’s exposure.

AI can self-operate the entire process of analyzing risks and help companies create predictive risk models. The accuracy of data analysis is greatly enhanced by AI as compared to data analysis performed by humans. AI has the ability to predict each customer’s risk, and thus provide customers with the precise amount of insurance required. This will also safeguard companies from risky customers. The accuracy of the risk assessments drives the pricing models and is the differentiator when it comes to competitive products.

The underwriting course involves many manual tasks that slow down the process and introduce the likelihood of human error. The underwriter spends a lot of time on the manual tasks instead of focusing on tasks of higher value such as portfolio management, analytics and creative solution services. With the advent of AI algorithms, the increased data accuracy leads to better developed products. Some of these manual tasks have the potential to be automated via a combination of AI technologies. The automation will significantly improve the productivity of the insurer's underwriting process, giving room to underwriters for dealing with higher-value decision making tasks. This will lead to significant customer benefits that include improved customer engagement via self-servicing models and customized or personalized policy pricing as per the customer’s need.

AI has certainly expedited the process and propelled insurers to focus more towards predictive pricing models and underwriters towards portfolio management.

Fraud Detection:

AI can play a significant role in automatic fraud detection for insurance companies. The insurance data is growing at an exponential rate and real-time identification of fraud in the initial stages of the process is extremely vital to avoid huge losses. Many companies run Machine Learning algorithms on historical data to identify anomalies, abnormal sequences, fraudulent patterns and trends which indicate fake traits that may go unnoticed by the human eye.

In addition to the algorithms, insurance fraud advisors carry out research and analysis to continuously inform the machine of certain behavioral and identity patterns to make the AI system more adaptable to latest fraud-trends, besides intelligently reduce and avoid false alarms. This repository of patterns and trends ensures higher accuracy with quicker fraud identification. With the human element added to the machine, the overall AI system becomes more mature to ensure efficient coverage of the risk ecosystem.

AI and Machine Learning are being used to automate numerous routine processes in the insurance domain. Futurists believe that AI and Machine Learning will completely change the face of the fast-growing industry. Digital labor can leapfrog the current technology gap and traditional insurance companies must reinvent to survive.

Do you agree with us that AI is the way forward for insurance companies? Let us know your thoughts at info@mindtree.com.

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