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AI and Data Analytics for the Financial Sector

Jan Scholtes | November 26, 2018

On October 18 of 2018, Legadex and ZyLAB organized a special lunch round-table for the financial sector in the beautiful restaurant “De Veranda” in Amsterdam, the Netherlands. Together with Luc van Daele and Hans-Martijn Roos, we prepared an agenda to discuss how the financial sector can use AI and Data Analytics to address the difficulties in locating, collecting, processing and analyzing large volumes of data for a variety of financial use cases.

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Information management and VDR

Where ZyLAB traditionally assists the financial sector answering information requests, dealing with internal investigations and audits triggered by regulatory agencies, or handling Subject Access Requests and Right to be Forgotten Requests under the GDPR, the round table focused more on helping the business to prepare Virtual Data Rooms and black-line personal or confidential information, especially when dealing with the sale of mortgage and loan portfolios

 The turn-out was great, as was the initial discussion, where participants provided several real-world examples of recent projects that could have used smart technology to do their jobs smarter, better, faster and more efficient!

The financial sector is by far the largest information processing industry, exceeding all others. Volumes continue to surge, complex regulatory and internal requirements create additional challenges for the business. Just to give a few examples: creating new financial products, issuing new loans, selling off a portfolio, financing transactions; all require the collection, analysis and review of enormous amounts of data. During this process, one has to take into account business risks, but also deal with compliance, regulatory, and privacy issues. Information is spread over several IT systems, making it impossible to create coherent and structured files. Often files in such IT systems are incomplete or contain wrong information, making reporting difficult.

This requires at least that all relevant transaction information is available in one platform, providing not only strong search, analytics and review functionality, but also tooling to deal with today’s specific compliance regulatory requirements.

 

Automatic Blacklining under the GDPR

A great example of such smart functionality is automatic blacklining (also called redaction, anonymization or pseudonymisation). Data sets typically contain thousands of documents, each of which contains sensitive personal data in many forms. Under the GDPR, one has the legal obligation to anonymize or pseudonymize data before disclosure. This is tedious, expensive and burdensome work. ZyLAB has developed technology based on text-mining and machine learning to identify such information and automatically anonymize or pseudonymize it, including a reference to the legal grounds for such action. In various projects, Legadex was able to reach quality levels of 97% at a fraction of the normal price and in incredible short time frames, using ZyLAB’s technology. Especially in cases where time is of the essence, such as the creation and opening of a virtual data room, such tooling can make the difference between a deal or no deal!

 

Preparing a Virtual Data Room (VDR)

The preparation of a virtual data room, also includes collecting relevant data from various IT systems, organizing the files, checking for completeness and off-course, preparing for vendor due diligence by detecting potential red flags or problems. This is where eDiscovery technology can make a huge difference. Such tools, used worldwide by the financial sector for litigation, arbitration, answering regulatory requests and internal investigations, have the built-in capability to automatically collect information, make every item completely searchable, enrich, analyze, quickly review and organize electronic information. Using additional AI and data analytics, it is also possible to automatically organize data into relevant folders and use extremely powerful search and visualization tools to identify risks, potential red flags, issues and opportunities in such large data sets.

Creating loan files in a comprehensive and coherent structure (e.g. loan agreements, mortgage deeds, valuation reports, General Conditions) is then an almost automatically process. In various projects, by using ZyLAB’s platform, Legadex could easily identify missing documents, provide clear overviews of information in pie charts and underlying documents including reporting, all together crating “due diligence” readiness and create a sound factual basis for reliance.

Where virtual data rooms can reach the size of hundreds of thousands (and sometimes even millions) of documents, when such a transaction needs financing, such data sets are often “dumped” upon financial institutions as part of the loan documentation. Understanding the risks of such a transaction and making an educated decision whether to finance such a transaction or not is then almost impossible. One can imagine, that the AI and data analytics can be extremely helpful in such a case as well!

 

Post-Closing Portfolio Management

Post-closing, many organization move on with their daily activities and forget about the large investment made in creating such virtual data rooms. So, why not leverage this investment use the data from the virtual data room for ongoing operations of the business (portfolio management, contract management, compliance), because there will be another day, where you decide to sell-off such an investment and redoing all the work again from scratch will cost you greatly!

Are you interested in reading more, you can check out our White Papers, eBooks and other resources as www.zylab.com or read the detailed article in Legadex magazine on how AI allows the financial sector to work smarter, better, faster and more efficient: https://issuu.com/legadex/docs/leg18033_digital_magazine_may2018_0

Written by Jan Scholtes

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