HOW CAN AI REDUCE COST & RISK IN THE INSURANCE INDUSTRY?

2019.10.30

Joshua Kwah

PERSPECTIVES

 

Data lies at the heart of the insurance industry, which requires high-quality information to serve customers, process claims, and make predictions. In the past, ensuring information is accurate has required tiresome manual processes to cross-reference documents and crunch numbers, but with AI, automated solutions can significantly reduce the amount of work necessary to execute common pieces of an insurance company’s workflow.

Here are five common use cases for AI in insurance:

Automated claim processing

Processing insurance claims is among the most common, crucial, and time-consuming tasks of any insurer. Typically made up of several manual tasks, such as referencing correspondence and routing claim files, the time it takes to process an insurance claim often frustrates clients waiting for their determination. AI drastically improves claims processing through automation, using virtual assistant software to quickly extract and upload information into a claims handling system.

New business underwriting

Finding new clients and uncovering new business opportunities is essential to growing an insurance company. AI greatly enhances the process of new business underwriting, extracting insights from multiple data sources to automatically determine new product offerings.


Fraud reduction

Insurers can lose significant amounts of money through fraudulent claims. Insurance fraud cost companies 1.2b pounds in the UK in 2018 as reported by KPMG. AI can reduce this risk through predictive models that can automatically identify potential fraud, extracting data from historical records to better estimate repair and write-off costs.

Risk management

Proper risk management allows insurers to weather storms and reduce the likelihood of things going wrong. Machine learning algorithms can greatly assist in risk management-related tasks, using tools such as automated document scanning to gather information directly from forms. This data is then fed into a larger data set that can assist in better long-term decision-making.

Customer support

24/7 customer service capabilities to handle general queries, make recommendations, and facilitate transactions Is essential to providing high-quality customer communication. AI can greatly reduce the need to rely upon human operators to handle all customer service queries large and small through natural language semantic search engine capabilities. AI-equipped chatbots can return pre-programmed answers to frequently asked questions, giving customers access to the information they desire most, as well as route them to a live agent should an inquiry require additional assistance.

A modern, truly intelligent insurance operation benefits from as much AI assistance as possible. Tasks that tend to require higher cognition, such as natural language processing, can add significant value for both clients and companies, and rules-based automation solutions can trim significant amounts of time off of tiresome, repetitive tasks. Once applied, insurers can quickly see tremendous internal and external benefits of using AI, generating long-term wins that only get better with time.

AI as an augment to insurance service providers

Artificial intelligence (AI) can not only greatly reduce the amount of human brainpower required to execute routine complex tasks but augment the human workforce in providing better and personalised service to customers. By training applications and machine learning algorithms with relevant data, AI can learn patterns, draw conclusions, and highlight opportunities that can be used to streamline multiple business’ workflows and drive greater productivity.

 

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