Empower insurance experts to make the right decisions
What if you could spend less time poring over volumes of insurance product, actuarial and client information, and more on delivering better risk assessments and driving client outcomes? Using natural language processing (NLP), IBM Watson® Discovery helps your underwriters, claims processors, customer service agents, and actuaries find answers and insights from insurance documents, customer and public data faster. That means faster business results, satisfied customers and happier employees.
What's your potential ROI?
IBM Watson Discovery with NLP technology can help improve productivity and lower costs of previous tools.
How it’s used
Better evaluate insurance risk
Analyze volumes of insurance documents at once to accelerate risk reviews, reduce manual error and increase productivity. Insurance underwriting experts can delegate time-consuming, manual tasks to AI and get risk-informed, data-driven insurance policy recommendations in near real-time. Not only can this approach reduce the duration of the underwriting lifecycle, but it can also improve customer experiences.
Claims management processing
Settle claims faster
Experts in insurance claims can use AI solutions to adjust, appraise, examine and investigate claims faster by drawing insights from multiple natural-language information sources. This results in faster claims resolution and settlements, delighting customers.
Risk and fraud management
Spot patterns and detect fraud
Use AI to help improve fraud detection by noting potential markers of fraudulent claims. Risk managers, auditors and actuaries can use hidden trends and patterns in information to help prevent loss before making payouts to claimants.
Empower agents with faster answers
With AI technology, customer service representatives and insurance agents can analyze current and previous customer service situations from databases and documents to identify resolution patterns and gain faster resolution times.
Meiji Yasuda Life Insurance Co.
Using AI tools to analyze unstructured data, the insurer has seen a 90% reduction in work involving text data reading and analysis, and has eliminated nearly 1,500 hours of work annually.