Like in every sphere of life, AI is now being widely used in insurance. AI has brought a significant revolution in the insurance industry, especially underwriting, by enhancing accuracy, efficiency, and speed.
“Furthermore, with an AI-driven underwriting process, it is now possible to detect frauds using ML algorithms, personalize pricing based on an individual’s risk profile, reduce overall process time, and analyze vast data in real-time without the need to rely on manual data assessment, actuarial models, historical data, etc. as it for traditional methods. Detection of frauds means that underwriters can now focus on actual cases and improve efficiency,” says Rakesh Goyal, director, Probus.
Improvement In Efficiency
AI underwriting algorithms have the power to leverage a wide range of data sources. This results in data-driven underwriting that improves efficiency and lowers risks for insurance companies. AI algorithms can identify patterns that may not be revealed by human analysis. These algorithms can analyze risk profiles much faster compared to what it would take traditionally and this significantly boosts the efficiency of the underwriting process. This can help lower costs and lead to lower premiums.
For example, let us take the example of a 46-year-old woman who is applying for insurance. Her electronic health records, daily steps, heart rates, and pharmacy records can be instantly analyzed and AI can predict her risk. She may have a chance of diabetes but have a lower risk of heart disease. Using models trained on patient data, her premium could be 10-15 per cent lower than others of the same age.
Providing Coverage To Those Previously Excluded
AI can help in fairer pricing based on individual risk, enhance claim settlement and policy approval speed, and be more accessible to the underserved population through accurate risk assessment. Traditional underwriting methods may exclude certain populations due to limited data.
With AI one can analyse alternate data sources. This could be telematics (for auto insurance), wearable devices (for health insurance), and social media to assess risk more accurately. This could allow insurers to offer coverage to individuals previously excluded. Having said that, the insurers need to ensure that no certain groups are intentionally left out of getting coverage.
