Artificial intelligence is a branch of computer science that works like humans in building computers. These systems combine reading, studying, responding, and self-correction to complete tasks. Machine learning develops AI methods that use techniques that apply the analytical study of lived experiences to make predictions on new data.
What is AI in Insurance?
Insurance AI is the effective implementation of advanced technology once insurers have identified where it fits into the digital insurance continuum. However, AI can be used for insurance advice, underwriting claims processing, fraud prevention, risk management and direct marketing.
Advances in customer behavior and technology have opened the door for AI to create value in the insurance market, reduce costs, increase efficiency, and achieve higher customer satisfaction and trust.
Read More: Computer Vision Applications in Healthcare
5 Key Applications of AI in Insurance
1. Better customer experience
Matt Adams, partner at PwC based in New York, says the biggest area of AI success in insurance is creating a better customer experience (CX). Businesses are adopting AI more and more to personalise goods for both consumers and corporate clients, maintain more constant client connections to increase customer loyalty and upselling, and analyse more data from more sources (including social media) to make better predictions.
2. Chatbots
According to the National Association of Insurance Commissioners (NAIC), numerous insurers have already made investments in chatbots and other virtual helpers. These chatbots offer digital services and are capable of having conversations that sound natural with people.
The goal is to answer questions, route calls, reduce human traffic to only high-level requests, and be available 24/7 for advice, billing information, and general inquiries and transactions. Among the pioneers of chatbots in insurance are insurers such as Geico, Allstate and Lincoln Financial. And today, many large companies use them. Chatbots are now also used to resolve cybersecurity password issues and provide copies of policies and other basic documentation. This saves enormous manpower.
3. Handling of Claims
A startup called Lemonade combines machine learning with chatbot technology at various stages of the claims handling process. ML models estimate the severity of damage; Estimate repair costs from historical data, sensors and images; and resolve the primary arguments. Lemonade boasts that its chatbots, Jim and Maya, can get a policy for users within 90 seconds and settle a claim in three minutes.
Read More: Top 10 Use Cases of AI in the Banking Sector
4. Agent interaction
Liberty Mutual has developed a way for its AI applications to connect with Amazon Alexa to take care of a wide range of tasks. This includes answering customer queries, providing fast insurance estimates and connecting consumers with the nearest agent who can meet their needs. The company also uses this AI technology to provide advice on managing risk.
5. On-demand insurance
Consumers these days want immediate services. They no longer have to call a 1-800 number, contact a local agent, make an appointment, drive to see the agent, wait for the paperwork to be prepared, and then sign all the documentation. Instead, they want to do it online or on their smartphones.
Benefits of AI in Insurance
Risk management
Cognitive networks can be used to detect fraudulent trends and reduce the number of false claims. According to the FBI, non-health insurance fraud in the United States costs more than $40 billion each year, costing families between $400 and $700 in extra premiums. Machine learning can be used to improve the risk and financial models of insurance businesses, possibly leading to more profitable markets.
Marketing & Sales
Machine learning can be used to price insurance plans more effectively and relevantly and offer beneficial products to clients. Insurers can price their policies based on individual needs and lifestyle, ensuring that customers only pay for the cover they need. This makes insurance more attractive to a wider spectrum of clients, some of whom may have obtained insurance in the first place.
Operative decisions
Chatbots based on deep neural networks can be created to understand and respond to more user inquiries via email, chatting and phone calls. These chatbots help insurers save a lot of time and money, which they can use for other corporate profitability.
How can insurers advance the use of AI?
The four guidelines below will help insurers overcome obstacles and achieve faster ROI using AI:
- Focus on the data. Collecting the right data, cleaning it, and authenticating and making it accessible are all critical steps in adopting AI quickly and reliably.
- Integrate capabilities. Bring together AI, analytics and automation to help with resource allocation, data authentication and use, governance and scaling solutions.
- Consider the long term. When you start building important capabilities like AI upskilling today, you'll surely reap the benefits for years to come.
- Make AI accountable. Apply a responsible AI toolkit to limit the risks of AI and make it more understandable.
The future impact of AI in insurance
Consumer insurance experiences can be transformed from frustrating and bureaucratic to fast, on-demand and progressively seamless through AI. Customized insurance plans increase customer base at low cost.
If insurers apply the power of AI to the huge amount of data available to them, we will see increasingly adaptive insurance, for example, pay-as-you-go insurance on request and incidents, organically adjusting rates based on consumer welfare, and so on. Are you looking for artificial intelligence development services who can automate your insurance business? We will see insurance being increasingly designed in such a way that backup plans utilize AI technologies to better understand what their customers want.
