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Case Study: AI in Commercial Insurance

Transforming Insurance Loss Run Risk Assessment


Accurate risk assessment is vital to the success of any commercial insurance provider. Unlocking the detailed data contained in lengthy and complex insurance Loss Runs for various properties and policyholders is a critical pathway to understanding risk and pricing. A leading insurance company was grappling with the challenge of extracting, analyzing, and managing critical data from loss-run documents. Despite investing in various software solutions, the company struggled to find a platform that could handle the complexities and scale of its data analysis needs accurately.

Using Docugami’s AI-powered Document Engineering, the company was able to significantly reduce the time and effort of loss-run data extraction compared to manual processes. 

The Challenge

Loss run documents contain vital information that can help insurance providers assess the potential risks associated with a potential customer, and set appropriate coverages and prices based on a deep understanding of risk. Unfortunately, loss-run documents are long, complex, and variable, making it extremely difficult for companies to identify and extract the needed data in an accurate and efficient manner. 

Manual data entry and processing were time-consuming and error-prone, leading to delays in policy issuance and inaccuracies in risk assessment. The company had tried a number of software approaches, but they all fell short due to the complexity of loss-run documents. The inability to harness the full potential of loss-run data in a timely manner left the company reliant on partial data and exposed to unnecessary risk. 

Discovering Docugami

The breakthrough came when the company tested Docugami’s AI-powered Document Engineering platform. Using multiple forms of AI, Docugami was able to understand the structure of the company’s diverse sets of loss-run documents, despite the wide diversity of document styles, structures, editing, and ways of organizing the underlying data. Docugami was able to detect the structural similarities across huge document sets, then identify, extract, and organize the critical information across hundreds or even thousands of individual loss-run documents. 

Transparency and training yield breakthrough results

Docugami was able to export the key data into highly organized and transparent reports, with citations for every extracted item directly back to the specific location in the individual loss run document from which it was generated. Unlike other Generative AI tools, Docugami’s full transparency gives frontline insurance analysts the ability to query, verify, and update individual data points quickly and easily. The company’s unique instance of Docugami actually “learns” every time a member of the team updates a generated data point, improving system accuracy with this feedback. This learning is specific to this insurance company only – learning based on their Loss Run documents is never shared with another Docugami customer.

Achievement unlocked: tapping loss run data 

Utilizing Docugami, the company was able to reduce the time required to generate insights from loss run documents significantly, while also reflecting their own individual data needs. Given the inherent complexity of loss run documents, some human intervention was still required to achieve maximum accuracy and fine-tune the software to their preferences, but the learning curve was swift, with no disruption to ongoing operations. Data extraction and analysis from Loss Run documents became faster and more accurate, enabling the company to gain deeper insights into risk profiles and tailor policies to meet the unique needs of its diverse clientele.

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