
How ML and AI Can Transform the Insurance Industry
CIO Review APAC | Wednesday, July 05, 2023

AI algorithms can flag potentially fraudulent claims for human review, allowing an insurance company to act much faster than humans alone.
FREMONT, CA: Because it is scattered across disparate systems, the insurance industry has been sitting on a largely unused treasure trove of big data. Recently, data management tools that incorporate artificial intelligence have seen accelerated adoption to generate business intelligence. Artificial intelligence has gained traction in claims processing, efficient underwriting, risk assessment, and fraud detection in insurance.
Businesses recognized the value of their artificial intelligence (AI)/machine learning (ML) applications, including natural language processing, during the pandemic. By standardizing previously unstructured documents, it became easier to determine the exposure of insurance portfolios to sudden events such as COVID-19.
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With the global AI market expected to grow at a 42.2 percent compound annual growth rate to $733.7 billion by 2027, AI and machine learning applications in insurance are only likely to increase. According to current trends, the insurance industry expedites AI and machine learning in the following ways.
Prudent underwriting
Insurance underwriting is heavily reliant on data and analytics. It entails risk analysis and pricing, thereby integrating underwriting into the insurance process. Historically, this critical function has been entirely dependent on humans. Underwriting has become more accessible, faster, and more accurate as a result of AI.
Intelligent underwriting algorithms can analyze customer data and create more accurate customer profiles, allowing for more efficient risk detection. Several applications of artificial intelligence in risk analysis include the following:
- For property and vehicle insurers, photo analytics are used to verify the damage.
- Geospatial imagery for property risk analysis and risk comparison systems are powered by deep learning and data science. Insurance companies can both mitigate risk and enhance the pricing mechanism for policies.
- Efficient underwriting will pass the benefit on to customers by charging the appropriate rate for each applicant–this is true personalization.
Enhanced management of claims
While claims management is a necessary component of the insurance industry, it is complicated and time-consuming. A claim requires processing large amounts of data and interaction with various stakeholders, including the claimant, insurance agent, underwriters, brokers, and financial institutions. AI/ML applications can automate routine data checks and interactions, freeing up agents' time to perform other critical tasks.
Claims management software can automate the complete claims action, from data scanning and processing to verifying policy details and identifying gaps or errors.
Another advantage of machine learning applications in claims management is that they provide customers with increased data security. Insurance companies can streamline the claims management process by utilizing these advanced technologies.
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