Automate due diligence tasks using Artificial Intelligence

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Organisations are often required to provide due diligence checks and recommendations on their contracts but face the challenge of doing this manually to tight deadlines whilst ensuring accuracy. Firms are now looking to Artificial intelligence to improve this process.
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Traditionally, organisations have to manually perform due diligence tasks, sometimes involving the manual categorisation of portfolios into product types and supporting document sets, followed by manual review of each set. This process can be extremely laborious and in order to meet deadlines some firms have to extend working hours or draft in supplementary resources. The process can also cause a risk in the accuracy of the extracted information. When the situation later invariably changes (a counterparty or judge requires additional information from the data set), the whole task has to be done all over again.

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The RAVN Extract for Due Diligence Solution

RAVN Extract, an application built on the RAVN ACE platform, can be applied to overcome these challenges. Documents and contracts, including scanned PDFs, are uploaded to RAVN Extract. The machine then automatically clusters the content into separate document classes (e.g. facility agreements, commercial mortgages, structured finance contracts, etc.) before extracting the relevant set of data points for each document class into a desired output e.g. third party system or excel spreadsheet.

RAVN Extract has the ability to compare negotiated agreements either against a body of agreements to establish machine-learned standards or with the original template, if available, or, Zones where the content changes between contracts are automatically detected and these elements are then extracted for analysis and compared with automatically or manually established rule sets. Deviations can then be prioritised, assigned a corresponding risk factor and flagged, via workflow, to the appropriate personnel for action. You are in total control of priority levels and workflow.

Contract Risk Analytics
Contractual risks can be quantified and aggregated according to contract type, contract negotiator or any other specified or extracted Key Performance Indicator (KPI). They can be reported (both pre- and post- signature) in a simple dashboard, with visual analysis tools as standard. Because Contract Risk Analytics quantifies contract value and risk across contract types, it could open up the opportunity to offset risk to insurers or niche risk trading mechanisms for particular business or product lines; and in so doing, free up investment capital for other business uses.

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Not only can RAVN Extract eradicate human error when performing due diligence tasks but staff who used to carry out manual data extraction can now be re-deployed to more productive and rewarding tasks, leading to improved morale as well as increasing efficiencies within the organisation.

In a recent example, RAVN Extract was able to replace 800 hours of manual due diligence work with 40 hours, including configuration, processing and output of the data; an overall reduction of 95% of the time for the data processing phase of the engagement. Sampling of the extracted data also showed an improvement in accuracy over manual methods. It also allowed the entire portfolio to be processed, adopting a consistent process and eliminating the need for temporary resources, leading potentially to better overall interpretation and advice.

Organisations offering due diligence services enhanced by RAVN Extract now have a superior competitive advantage when bidding for work that has traditionally taken a long time to perform manually.

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What is RAVN Extract?

RAVN Extract is built on top of the RAVN Applied Cognitive Engine (ACE). RAVN ACE brings together different technologies from the fields on Information Processing and AI (Artificial Intelligence) in a coherent, enterprise-ready solution stack. Beyond the foundations of a powerful document search engine, the Applied Cognitive Engine focuses on extracting and distilling the information within documents.

Clients chose to work with RAVN as our ‘Applied‘ Cognitive Engine is thoroughly applied to the business. We listen to the firm’s issues and create a robot that specifically handles those issues within that domain. Our technology can be deployed as standalone solutions or some organisations chose to combine our products to compliment each other, ensuring all needs are met.

There are various payment options – the technology can be delivered as a service, pay per document model or enterprise license.

Watch our Case Study on BLP’s use of RAVN ACE

See how RAVN ACE has benefited Berwin Leighton Paisner in terms of increasing efficiencies, mitigating risk, cutting costs as well as increasing staff morale.


Need more information?

Read our Extract for Due Diligence Brochure


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    As a trusted adviser and negotiation partner, we wanted to have first hand experience of a leading AI technology so we can advise on how it will change the workplace over the coming years to ensure we’re offering the most appropriate advice to our clients. 
    Ole Møller, Vice President at Djøf
    This technology will bring us a flexible environment that is dedicated to our firm so we can ensure we can look after our clients as efficiently as possible. We chose to collaborate with RAVN as we recognised them as a leading AI provider and wanted their product to be part of the firm’s portfolio. 
    Santiago Gómez Sancha, ICT Director at Uría Menéndez
    For our lawyers, time is very precious and we needed a fast, reliable and accurate search engine that was easily integrated into our existing systems. The team at RAVN proved they could tick all the boxes we required. 
    Flavio Romerio, Partner at Homburger
    The software will read, interpret and extract key provisions from a client’s property lease agreements. This approach is a great supplement to manually laborious processes, and a stand-alone device in relation to certain standardized agreements and will mitigate risk from human errors and inconsistencies. SVW is happy to continue the collaboration with RAVN to further improve the SVW real estate robot. 
    Peter Van Dam, Knowledge and IT Manager at Simonsen Vogt Wiig
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    César Mejias, IT Director at Garrigues
    RAVN's platform has allowed us to implement our vision of providing integrated, secure and effective access to our knowledge resources. 
    Robin Hall, Head of Knowledge Management at Howard Kennedy
    RAVN is one of a number of innovative solutions that the business is implementing as part of IT's 2020 vision aligned to improve efficiencies and productivity benefits across the firm
    Clive Knott, IT Director at Howard Kennedy
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    Ovais Naqvi, Managing Director – Head of Market Engagement at Abraaj
    It's likely to save us tens of millions of pounds in lost revenue.
    Horia Selegean, Head of Revenue & Margin Assurance at BT
    Sky are committed to using the latest innovations to ensure our customers receive the best possible viewing experience. RAVN’s AI component has allowed us to successfully automate the EPG review process which has dramatically reduced the review time as well as ensuring we maintain robust and compliant information">
    Angus Gairdner, Head of Content Planning Operations at Sky
    By adopting this innovative platform we are able to quickly focus on the high value and high risk contracts within large data sets, simply categorise and divide up tasks and ultimately provide a more responsive service to our clients. We are now looking to roll out the RAVN solution to live client matters within the firm
    Lucy Dillon, Chief Knowledge Officer at Reed Smith
    The RAVN solution effortlessly made all of our operational content, valuable precedent and knowledge content discoverable within the firm’s chosen collaboration and Search platform, Microsoft SharePoint. As such, the disruption for users was negligible, yet the benefits from efficient search, preview and expertise location across a geographically distributed organisation have been significant.
    Jeremy Rooth, Director of Business Transformation & Knowledge Management