Blog
Celebrating 10 Years of Symphony: Leading the Way in Fintech
Symphony turns 10! Discover how we’re transforming the financial industry through trust, passion, and cutting-edge technology.
November 27, 2024
Underwriting and Claims Text Analytics
- Samuel Leavitt
- Case Studies
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Revenue generation based on pricing decisions and loss mitigation from not underwriting a company who later is hit by a huge lawsuit.
Challenge
At the start of the decision-making process, underwriters are generally provided with only two main data sources: the client-provided information in the application form and previous claims led against the applicant’s insurance policy. From there, they may use Google search, social media, and online news sites to locate any red flags that would impact the final evaluation.
Because the research methodology is manual and ad-hoc, there is a strong likelihood for unknown risks in the portfolio.
Solution
The insurance company applies the Insight Platform’s NLP datasets to automate the risk monitoring process.
With the ability to customize and quickly execute models, the Insights Platform captures news from a wide array of cloud-based documents, whether it is news on private or public companies, SEC filings, or earnings call transcripts.
The platform then scans the content for the insurance company’s specific view of risk. If there is a news story about the applicant in the context of that risk, the underwriter can factor that information into his or her decision.
The build-out process may involve several stages in order to reach an automation process that is an improvement on the existing process. After the Insights Platform team creates the initial model, the insurance company will assess the data results to determine which areas need fine tuning. The team then adjusts the model. There may be several iterations before finally arriving on a custom solution that automates risk detection according to the specific way the insurance company views risk.
Outcome
The underwriter can now log onto the platform dashboard, select the relevant company, and see the number of mentions around the associated risk topic over a period of time.
- For example, the underwriter may see that a pharmaceutical client had 35 mentions around the risk topic cannabis over the past year.
- Based on that information, they can decide whether to not underwrite the policy or adjust the pricing because of the risks associated with the account.
Interested in learning more?
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