Machine learning: how will AI impact the insurance sector?
05 Jun 2023
The adoption of machine learning and artificial intelligence (AI) has become an essential element in almost all industries, and the insurance industry is no exception. The pandemic has reinforced the use of new technologies, including AI, for a smarter and more efficient future. According to PricewaterhouseCoopers (PwC), AI contribution is expected to grow annually between 20-34% per year across the region, with the UAE experiencing the fastest growth, followed by Saudi Arabia. The insurance sector alone has automated more than half of claims activities, and AI has improved various insurance processes, such as fraud detection and prevention, and routine operations.
AI positively impacts the insurance industry in the following ways:
- Fraud Detection and Prevention: AI can lower the risk of fraud by providing valuable details for better human judgment. AI tools can scan and analyze data to detect any abnormal patterns that might indicate fraudulent activity. This helps insurers identify potential fraud and take appropriate action to prevent it. By leveraging AI, insurers can improve their fraud detection capabilities and reduce losses due to fraudulent claims.
- Claim Processing: AI can help facilitate the process of submitting a claim by allowing policyholders to report a claim through AI tools such as chatbots, saving time and effort. AI can also automate routine tasks in claim processing to speed up the process and reduce errors, improving the overall customer experience.
- Improved Routine Operations: AI can automate routine operations, such as data entry, document processing, and other administrative tasks, saving time and reducing errors. Automating these tasks can increase productivity and operational efficiency as the process includes little to no human intervention.
ML and AI technologies will continue to add value and benefit the industry as new tools emerge to make business conduct easier. By leveraging various AI tools, insurers will save costs and time, and allow for more focus on the development of better product categories.