How Machine Learning and AI are Transforming the Insurance Industry

The insurance sector has been sitting on a treasure trove of big data. Machine Learning and AI is able to utilise this data to help the industry make better decisions. For instance, artificial intelligence in insurance improves efficiency in claims processing, underwriting, risk evaluation and fraud detection.

During the pandemic, companies realized that their AI/ML applications, including natural language processing, made it easier to figure out the exposure within their insurance portfolios for sudden events like COVID-19, by standardizing documents.

Areas for transformation

The global AI market is estimated to grow at a CAGR of 42.2% to $733.7 billion by 2027. Some of the ways in which AI and machine learning are transforming the insurance industry are :

Intelligent underwriting

The underwriting process in insurance which is an integral part of the insurance process was traditionally dependent on humans. With AI, the process of underwriting has become easier, quicker and more accurate.
Intelligent underwriting algorithms can analyze customer information to create reliable customer profiles and detect risk more efficiently.

Improved claims management

Settling a claim involves processing large volumes of data and interacting with the claimant, insurance agent, underwriters, brokers, financial institutions. AI/ML applications can automate routine data checks as well as interactions, streamline processes right from data scanning and processing to verifying policy details and identifying gaps or errors.

For example, Japanese insurance company Tokio Marine incorporated an AI-based claims document system to upload handwritten notices onto its cloud-based system. This AI-based system was able to reduce input time by 50%, cut human error by 80% and fast-tracked claims payments for the company.

Fraud detection using machine learning

In the United States alone, insurance fraud (non-health insurance) costs the industry over $40 billion in losses each year (Fbi.gov stats). Insurance fraud detection using AI can be an efficient way to identify these scams.

Deep anomaly detection is a popular ML application to detect fraud. Insurance companies can significantly reduce risks and costs when potential frauds are flagged if there is any deviation from typical claims.

To cite an example, one of Turkey’s largest insurers, Anadolu Sigorta, had a team of 50 people to check every claim using a set of loose rules and their own personal experience. The results were compared to the results of a predictive analytics software tool which speeded up the process and reduced errors. After the change, Anadolu Sigorta insurer saw a 210% ROI within a year of switching to the AI solution.

Read more about the 6 Ways Machine Learning and AI are Transforming the Insurance Industry

Originally published at https://www.simplesolve.com on April 1, 2021.