The insurance industry is rapidly emerging as a sector that benefits considerably from the intelligent analysis of data, also known as Text Mining, Text Analytics, or Natural Language Processing. On a daily basis, insurers gather huge volumes of text from multiple channels, including their websites, email, social media networks, agents, and customer care centers. The collected information includes policies, expert and medical reports, claims, and other customer-related data. Through proven methods, text mining technology allows companies to detect natural language text patterns (which are generally missed by conventional approaches) in a timely and accurate way, thus leading to improved decision making.

SCOR Global Life’s R&D Centers initially developed their own text mining solution to meet the needs of a major client in China. Its experts used specific techniques to automate the extraction of information from the client’s critical illness claims reports, which were previously handled manually. The first step involved transforming text into numbers through natural language processing, adapted to the specificities of the Chinese language. Machine-learning processes were then applied, enabling the client to classify and identify the main causes of critical illness claims.