BLM selects iManage RAVN Extract to complete “data triangle”
BLM’s IT director Abby Ewen tells Legal IT Insider how the RAVN tool is being used to predict outcomes as part of a three-pronged approach to analysing the firm’s data.
BLM has selected iManage RAVN Extract to help capture unstructured data from its documents and emails which, working together with its data analytics team and in partnership with the London School of Economics (LSE), will form the basis of predictions around costs and claims outcomes.
BLM handles nearly 70,000 cases per year on behalf of insurance companies and currently much if not most of its data is held in unstructured form in documents stored across the business.
What sealed the selection of the RAVN tool was a proof of concept in which RAVN was able to locate an accident report form that was located in an attachment containing multiple documents within an email box containing 7,000 emails.
Speaking to Legal IT Insider, BLM’s IT director Abby Ewen says: “The fact that the tool could pick through thousands of emails and attachments and within a big PDF and locate the form and extract the information we needed and put it in a database impressed us both in terms of that specific task but also what that means for what that means for what we can do with it in the future.”
BLM in February 2018 signed a two-year research and development partnership with the LSE, and its data analytics team led by head of analytics Andrew Dunkley will work with three LSE professors to develop new litigation risk management offerings for BLM customers.
Ewen adds: “We have all kinds of use cases in mind and we are forming a triangle between RAVN, our data analytics team and our partnership with LSE: we’re using RAVN to extract the data which the LSE team can then use to inform their thinking. We have loads of data including structured data that comes out of our case management system and this is a way to amalgamate all our data and to then build complex algorithms from which we can make predictions and build tools.”
While there is disillusionment across the legal industry at the lack of maturity of extract technology, many firms are looking for a magic bullet that doesn’t exist. Ewen says: “We often don’t have the right capability to know how to use this kind of technology and many people struggle to make it work. What is a shame is that many expect these kinds of tools to work out of the box, and when they don’t the tools get the blame.”
The RAVN purchase comes as Ewen looks to leverage the firm’s existing tech stack and she says: “I keep saying that I don’t want to buy any more technology. We have so much, we just need to find better ways of using it. It’s about finding clever people who can solve a well-articulated business problem using the tools you’ve got. RAVN is another piece of the AI process puzzle.
“We’re using Intapp; HighQ; Ravn and some opensource stuff but mostly my focus is using the things we’ve already got in new and different ways. You don’t get AI in a box – you need the business input because the business needs to be defining the question you need to answer. What is the client problem you’re trying to solve? It has to be defined. What’s the most specific problem they have? Then we use Intapp to provide an external facing environment for our clients to put their data into and the output is through the HighQ Collaborate portal. It’s understanding about integration and creating a solution.”
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