This creative solution, which makes use of Intellect's exclusive eMACH.ai architecture and Gen AI capabilities, is the first no touch lost run extraction technique in the world. In addition to having an amazing accuracy rate of over 95% across a range of document formats, including handwritten notes, Excel files, pictures, and PDFs, the system stands out for its ability to handle data from lost runs rapidly.

The importance of this discovery was emphasized by IntellectAI's Insurance Business Head, Sandeep Haridas. He said, "We have resolved an issue that the industry has faced since producing the first loss run output." It is capable of accurately extracting and summarising loss run information from a variety of document types, including those with complex content like headerless sheets and borderless tables. Additionally, it can recognize and comprehend intrinsic hierarchies without the need for human intervention in the extraction process. The time and money savings that this technology provides to insurers, agents, brokers, wholesalers, and MGAs are highlighted by Haridas.

The difficulty with loss runs is that they have different formats and structures depending on the carrier, which makes it harder for AI models to correctly read and extract data. Insurance professionals have historically had to weigh the trade-off between speed of extraction and accuracy of loss run data. Due to the frequent need for human intervention, risk analysis and quote provision were held significantly, which could have an impact on deal results.

Deepak Dastrala, IntellectAI's CTO, highlighted the wider ramifications of this advancement. He said, "From a technological standpoint, what we are doing precisely demonstrates how LLMs can be used to significantly improve the underwriting process without compromising the accuracy and trustworthiness of the extracted data."

In addition to resolving a long-standing problem for the industry, IntellectAI's use of Gen AI technology shows promise for an instant return on investment for customers, which represents a major advancement in the insurance underwriting procedure.