, the company dedicated to transforming how professionals work, today announced that – a leading insurance risk and commercial law firm based in the UK and Ireland – is using to capture data from its documents to analyse and make accurate predictions around claims outcomes.
As a firm that handles nearly 70,000 cases per year on behalf of insurance companies, BLM has long embraced different forms of technology that make the firm more efficient. iManage Extract, powered by the RAVN AI engine, provides an ideal way for the firm to pull data from its documents for use in analytics around claim costs and likely outcomes. By automating the extraction of key information, the firm will develop structured reports to provide better advice for its clients.
“We were looking to build models that could make accurate claims predictions but most of our data is held in unstructured form in documents scattered around our business,” said Abby Ewen, IT Director, BLM. “iManage RAVN Extract is able to quickly and accurately capture the specific pieces of data from the raw documents within our document estate. Extract will significantly improve our efficiencies and help reduce the claims processing time.”
During an initial proof of concept, BLM was impressed with iManage Extract’s performance and the value the extracted data provided and it plans to find new ways to leverage iManage Extract within the firm moving forward. “The RAVN AI engine helps us develop a sophisticated data analysis platform,” added Ewen. “We work with a large number of insurance companies and it’s essential we use technologies that innovate.”
“By using AI to automatically read, extract and interpret critical business information from large volumes of documents and unstructured data, iManage RAVN Extract helps organisations get more value out of their data,” said Nick Thomson, General Manager, iManage RAVN. “Innovative firms like BLM are increasingly recognising the benefits of unlocking information stored in their documents to deliver increased value to clients.”