Top 5 AI Use Cases in Insurance

Insurance companies are using AI systems for a wide variety of purposes, from risk assessment to fraud detection to underwriting. The goal of each of these AI use cases in insurance is the same: To improve accuracy and efficiency, and to deliver a better customer experience.

1. Risk Assessment

Risk assessment is the process of assessing the risk associated with offering insurance. For medical malpractice coverage, the goal of risk assessment is to determine the likelihood of a physician facing a medical malpractice claim.

The Role of AI in Predicting Insurance Risk

Medical malpractice insurance allows physicians to transfer the financial risks of medical malpractice claims to an insurance company. Insurers must understand the likelihood and severity of potential malpractice events before issuing a policy. AI tools give insurers the ability to analyze vast amounts of data for a more comprehensive risk assessment.

AI & Improved Accuracy in Risk Assessment

AI-enhanced risk analysis processes can gather more data points that go into risk assessment, reduce mistakes caused by human error, and identify details or patterns that humans might overlook. That results in more accurate, more comprehensive  risk assessments.

2. Chatbots in the Insurance Industry

Chatbots are AI programs that are designed to simulate real-life human conversations through text. They’re now common in the insurance industry, especially for customer service.

Enhancing Customer Experience with AI-Enabled Chatbots

AI-enabled chatbots allow customers to easily contact their insurer for help with common requests, such as billing questions or copies of policy documents. Chatbots enhance the customer experience by minimizing the need for traditional support lines, which may have high call volumes and long wait times.

Case Study: Chatbots in Insurance

Some insurers are publicizing major successes from their use of chatbots. For example, a property and casualty insurer says its chatbots can help customers secure a home or auto policy in as little as 90 seconds. The technology also shows promise for many other types of insurance, including  medical professional liability coverage.

3. Fraud Detection & Prevention

Insurance fraud is a big business in the United States: The Coalition Against Insurance Fraud estimates the total cost of insurance fraud at $308.6 billion per year, which drives up premiums for honest consumers. Fighting fraud is a key use case for AI. 

The Use of AI to Prevent Insurance Fraud

Insurers are turning to AI tools to pinpoint fraud attempts. If an AI tool is trained with data of previous insurance fraud, it can flag suspicious requests for coverage or suspicious claims for further review.

AI in Detecting Fraudulent Claims

Two common types of insurance fraud are submitting false claims and inflating real claims. With artificial intelligence, insurance companies can detect claims fraud, for example, by automatically validating data provided by a customer against third-party data.

4. Claims Processing & AI

Claims processing is the process of investigating customer’s claims and issuing payment per the policy terms. Insurers are increasingly using AI tools to accelerate claims processing times and pay settlements faster.

AI in Underwriting & Pricing

Underwriting is the process of deciding whether or not to offer coverage, and if accepted, how much the policy will cost. Insurers use information they gathered during the risk assessment to make underwriting decisions. Increasingly, AI is playing a role in the underwriting process.

How AI is Revolutionizing Underwriting in Insurance

Companies like Indigo are using AI systems to underwrite medical malpractice policies faster and more accurately. AI tools are able to analyze large amounts of data to accelerate policy approvals and identify appropriate coverage terms.

AI’s Role in Dynamic Pricing in the Insurance Sector

Dynamic pricing adjusts premiums based on real-time data about each consumer’s individual risk profile. With AI, it’s possible to accurately price a physician’s risk of facing a medical malpractice claim, based on thousands of data points. That rewards good physicians with larger potential premium savings.

We're written an entire blog about the benefits of AI underwriting for customers of medical malpractice insurance.

5. The Future of AI in the Insurance Industry

AI has the potential to significantly transform the insurance industry for the benefit of both insurance companies and their customers.

Exploring the Future Potential of AI in Insurance

As AI continues to advance, insurance companies will likely find more ways to use it to streamline their operations. For example, in the future, many functions could be fully automated, allowing customers to get coverage and file claims through self-service systems.

Limitations & Challenges of AI in Insurance

Like any emerging technology, there are still some challenges with artificial intelligence. Insurers must be aware of the technical limitations of their chosen systems,  keep ethical concerns such as data privacy and job redundancy in mind. Ultimately, ensuring that changes create value and enhance the overall customer experience will be crucial to sustainability.

What Are the Benefits for You?

There are many benefits of AI in insurance, from faster policy approvals to more personalized pricing. Indigo uses a proprietary AI-powered process to help physicians get the medical malpractice coverage they need quickly.

Request your customized quote today.

Disclaimer: This article is provided for informational purposes only. This article is not intended to provide, and should not be relied on for, legal advice. Consult your legal counsel for advice with respect to any particular legal matter referenced in this article and otherwise.