The insurance industry is one of the economy’s oldest and most essential sectors. It provides financial protection and compensation for losses, damages, or risks in exchange for a premium. However, it is also one of the most complex and challenging sectors, facing various issues, such as rising costs, changing customer expectations, increasing competition, and evolving regulations.
To overcome these issues and seize new opportunities, this industry is undergoing a digital transformation, leveraging the power of artificial intelligence (AI). This article will explore how AI works in insurance and use cases and the future of artificial intelligence in insurance in the coming years.
How AI Insurance Works?
Artificial intelligence in insurance works by using various AI technologies, such as machine learning (ML), natural language processing (NLP), computer vision, and chatbots, to perform different tasks and functions in the insurance value chain, such as
Data collection and analysis
AI can help insurers collect and analyze large and complex data sets, such as customer profiles, behavior, preferences, feedback, claims history, risk factors, market trends, and regulations, and discover patterns, trends, and insights to inform their decision-making and actions.
Risk assessment and pricing
Besides, with its support, insurers may assess and price an insurance applicant’s or policyholder’s risk and eligibility and determine an insurance policy’s premium, coverage, and terms based on data and algorithms. It can also predict the likelihood and severity of claims and optimize their pricing and profitability.
Content creation and communication
Using natural language generation (NLG) techniques, AI can help insurers create and communicate content, such as product descriptions, policy documents, marketing materials, or customer messages. Not stopping at that, insurers may understand and communicate with customers using natural language understanding (NLU) and speech recognition methods.
Product and service delivery
The company may need artificial intelligence in insurance to deliver its products and services using automation and chatbot techniques, such as policy issuance, claims submission, verification, and settlement. Besides, based on customer data and preferences, they may also provide personalized and relevant products and services, such as recommendations, offers, rewards, or solutions.
Fraud detection and prevention
Using ML and anomaly detection techniques to identify and flag suspicious or fraudulent activities, the company can detect and prevent fraud, such as false or exaggerated claims, and provide evidence and support for investigation and litigation.
Use case of artificial intelligence in insurance
There are many use cases of artificial intelligence in insurance across various types and domains of insurance. Here are some examples of how well-known companies and brands use AI to enhance and automate their insurance activities and outcomes.
Underwriting
The first use case is evaluating and pricing the risk and eligibility of an insurance applicant or policyholder. Underwriting can help insurers to determine the premium, coverage, and terms of an insurance policy.
It uses ML, NLP, and computer vision to analyze large and complex data sets, such as medical records, credit scores, social media, or images, and discover patterns, trends, and insights that inform their underwriting decisions and actions. Besides, we can predict the likelihood and severity of claims and optimize their pricing and profitability.
For example, Lemonade, a digital insurance company, uses AI to underwrite and issue policies in minutes and adjust and pay claims in seconds using its chatbot Maya and anti-fraud algorithm Jim.
Encouraging safer driving habits
Encouraging safer driving habits is providing incentives and rewards for drivers who drive safely and responsibly, such as lower premiums, discounts, or cash back. It can help insurers to reduce the frequency and cost of claims and to increase customer loyalty and retention.
With AI, insurers promote safer driving habits by using telematics, sensors, and cameras to monitor and measure the driving behavior and performance of drivers, such as speed, acceleration, braking, cornering, or distance, and to provide feedback, tips, and recommendations to improve their driving skills and habits. Moreover, artificial intelligence in insurance creates and delivers personalized and relevant incentives and rewards to drivers based on their driving data and preferences.
For example, Progressive, a car insurance company, uses AI to offer its Snapshot program, which tracks and scores drivers’ driving habits and adjusts their premiums accordingly.
Claims processing
This step can verify and settle the claims of policyholders who have suffered a loss, damage, or risk and are entitled to compensation or reimbursement from their insurers. Claims processing can help insurers provide customer service, satisfaction, and trust and manage their cash flow and reserves.
In this case, insurers can improve their claims processing process by using NLP, computer vision, and chatbots to automate and streamline the claims submission, verification, and settlement process and provide faster and more accurate claims resolution and payment. Artificial intelligence in insurance can also detect and prevent fraud by using ML and anomaly detection to identify and flag suspicious or fraudulent claims and provide evidence and support for investigation and litigation.
For example, Tractable, an AI company, uses AI to assess vehicle damage and estimate repair costs, using computer vision and deep learning to speed up the claims process for insurers and customers.
Selecting health benefits & plans
Choosing the best health insurance plan for oneself or employees based on various factors, such as coverage, cost, network, and preferences, is what this feature can do. It can help individuals and employers to optimize their health and wellness and to reduce their medical expenses and risks.
Artificial intelligence in insurance can help individuals and employers select health benefits plans using ML and NLP to analyze their health data and needs and provide personalized and relevant recommendations and comparisons of different health insurance plans. With this, businesses could monitor and manage their health benefits plans by using chatbots and sensors to provide feedback, reminders, and alerts on their health status and usage of their health insurance benefits.
For example, Lumity, a health benefits platform, uses AI to help employers and employees select and manage their health benefits plans using data-driven algorithms and user-friendly interfaces.
Personalized insurance policies
This use case can help customize and tailor to each customer’s needs and preferences rather than based on generic or standardized criteria. They can help customers to get the best coverage and value for their money and to increase their satisfaction and loyalty. With this, insurers can create and offer personalized insurance policies using ML and NLP to analyze customer data and behavior and develop and deliver personalized and relevant products and offers, such as recommendations, discounts, or rewards.
AI can also help customers choose and manage their customized insurance policies by using chatbots and sensors to provide feedback, tips, and alerts on their insurance needs and usage of their benefits. For example, Metromile, a pay-per-mile car insurance company, uses AI to offer personalized insurance policies using telematics and sensors to track and charge customers based on their driving mileage and behavior.
Assessing vehicle damage
Assessing vehicle damage means figuring out how much damage an accident, crash, or other event did to a car and how much it will cost to fix. Checking the damage to a car can help the insurance company and the customer speed up and ease the claims process while lowering the risk of fraud and mistakes. AI can help customers and insurance companies figure out how badly damaged a car is by using computer vision and deep learning to look at pictures and videos of the damaged car and quickly and accurately guess how much it will cost to fix. Chatbots and automation can also help insurance and customers check and settle claims by making the process of filing, verifying, and paying claims faster and easier. Tractable, an AI business, uses computer vision and deep learning to speed up the claims process for customers and insurance. For example, AI is used to evaluate damage to vehicles and guess how much it will cost to fix them.
Determining property risks
Figuring out property risks means looking at and guessing a property’s possible losses and risks, like fire, flood, theft, or abuse. Picking property risks can help customers and insurers set prices for and protect their property insurance plans and stop or lessen losses and damages. AI can help customers and insurance determine a property’s risks by using computer vision and geographic analysis to look at satellite and overhead pictures of the property and its surroundings. This gives accurate and thorough information about the property’s features, conditions, and risks.
In addition, AI can help customers and insurance keep an eye on and handle the risks that come with their property. It can do this by using sensors and alerts to give real-time and predictive information about the property’s state and events and proactive and preventative actions and solutions. To give you an example, Cape Analytics, an AI company, uses computer vision and geographic analysis to look at property pictures and data and give insurance and customers property information and risk scores.
Customer service
Before, during, and after a customer buys or uses a product or service, customer service helps and supports them. Customer service can help insurance and customers build trust, happiness, and lasting relationships, which will keep customers coming back and loyal.
AI can help insurance and customers improve their customer service by using natural language processing and robots to help customers with questions, fix problems, give information, and make purchases 24 hours a day, seven days a week. AI can also help insurance and customers improve customer service by using machine learning and sentiment analysis to understand and respond to customer comments, feelings, and levels of happiness, as well as to offer personalized solutions and suggestions that are relevant to the customer.
For instance, Lemonade, a digital insurance business, uses AI to improve and enhance customer service. Its robot, Maya, helps customers right away and in a nice way, and its anti-fraud program, Jim ensures that claims are handled quickly and fairly, leading to faster payment and settlement of claims.
The future of AI in insurance
The insurance business is already being changed by AI, and it will continue to do so as AI tools get better, easier to use, and cheaper. Many chances and problems will come up for customers and insurers in the future of AI in insurance, such as
New products and services
AI will help insurers come up with and offer new products and services that are more creative, flexible, and adaptable to the needs and wants of customers as they change. For example, on-demand, pay-as-you-go, or peer-to-peer insurance are some examples of these new goods and services. AI will also make it easier for people to get and use new goods and services that are easier to use, more flexible, and cheaper. These will offer more value and benefits, like smart contracts, blockchain, and robo-advisors.
New markets and customers
With AI, insurers will be able to reach and serve new customers and markets that they haven’t been able to reach or serve before. These could be low-income, rural, or remote customers, as well as new areas, industries, or segments, like the sharing economy, gig economy, or green economy. People will also be able to get and use insurance goods and services that aren’t available, cheap, or right for them right now, like internet insurance, microinsurance, and parametric insurance.
New risks and regulations
AI will also create and expose new threats and regulations currently unknown, unmanaged, or unregulated, such as ethical, social, or legal implications, data quality and security issues, human oversight and intervention needs, and customer trust and acceptance concerns. AI will also require insurers and customers to adapt and comply with new risks and regulations that are constantly evolving, complex, and diverse, such as privacy, transparency, accountability, or liability.
Read more: Artificial Intelligence in Marketing: Run your Business in the Best Way
AI is an intriguing and developing technology that presents opportunities and challenges to the insurance sector and society. To remain ahead of the competition and satisfy the evolving demands and expectations of the market and society, insurers and consumers must embrace and exploit AI and continue to learn and experiment with it.
AI is the future of insurance, and it is already here. Yet, remember that it is not a substitute for human insurers but rather a supplement and tool that may assist them in improving and automating their insurance operations and results. This is not a one-size-fits-all solution but a tailored and adaptive solution that addresses various insurance objectives, circumstances, and scenarios. AI in insurance is not a static and fixed technology but rather a dynamic and developing technology that can learn and improve with input and supervision from human insurers over time.
