AI in insurance:
4 solutions insurance companies should implement now

Harry Liimal
April 8th, 2021

ai in insurance

The insurance industry, like many others, is on the verge of a seismic, tech-driven shift. AI in insurance is now enabling companies to unlock and analyze much more data in ways that people alone simply cannot. This provides insurance companies a number of benefits like speeding up customer service, faster claims settlements, pricing policy, better fraud detection or risk management.

Here are four AI solutions for insurance industry that have already proved their impact and insurance companies can and should implement already now:

1. Automating Customer Service

AI-powered chatbots, emailbots and callbots are a perfect way to automate customer service. They are fast, efficient and always available for the customer to get answers or offers.

Chatbots can automate 100% of the chat process. Chatbots can answer 60% of questions automatically, forward 20% of conversations to salespeople if a sales opportunity is signaled and send 20% of complex, non-repetitive questions to the right agents the first time. Emailbots can help to automate email communication and automatically answer frequently asked questions, forward emails to the right agents, prioritise emails and get accurate statistics about the reasons customers contact the business. Call automation bots can transcribe and analyze the call in real-time and forward it to the right specialist or answer questions automatically without any human assistance.

Such machine learning solutions help to automate routine tasks and free employees to focus on higher-value tasks, thus improving customer experience and customer engagement. AI enables self-service queries on policy issuance, endorsements, cancellations and renewals. AI solutions are also able to increase loyalty through effective bundling and cross-selling the right products to the right customers at the right time.

2. Claims Management and Processing

Insurance companies’ efficiency is defined by how fast they can manage to settle claims and how successfully they do it. Imagine 10 claim handlers doing the work of 40 with higher quality, this is what AI can deliver. Machine learning models like speech/voice or text analytics can understand and interpret spoken words to text and connect content to claim. This means insurance companies are able to extract data from documents much easier which means claims are settled much faster.

3. Fraud detection

AI is perfect to detect fraud with insurance claims. Machine learning models are smart which means they can learn and improve over time and encounter signs of fraud or anomalous behaviour that are new to insurers. They can raise flags in such cases and send claims to further review, which helps to improve decision making. For instance, a similar system was recently implemented for tax fraud detection.

4. Risk Management

Building AI on top of the data that insurance companies have access to enables more proactive risk management and more granular underwriting.

Using data with AI gives businesses the confidence that risks can be effectively identified and managed while taking into account companies’ policies and risk culture. Implementing AI does not require companies to turn to completely new processes, but to enhance existing ones and use AI to fill necessary caps. AI can examine thousands of loss reports and understand trends that previously would have taken specialist months.

Specialists are still important and required but AI in insurance can improve and speed up their work due to access to quality information.

This means better risk scores, predicting break-even price, dynamic pricing compared to competitors or predicting payments per month.

To wrap it up

AI in insurance is changing the industry and companies should act now to get the much-needed edge over the competition. To solve previously mentioned challenges MindTitan has developed an easy roadmap solution for insurance companies with the following steps:

  1. Discuss with your team what are the business problems you wish to solve and what are processes you wish to improve.
  2. The next steps are to figure out whether AI is the right solution to solve those business problems and optimize those processes. Contact MindTitan to do a workshop with your company.
  3. Create an AI strategy with MindTitan to understand which AI use cases to tackle and what is the required infrastructure and steps to execute.

ai use cases formulation