Artificial intelligence (AI) and lawyers make for a difficult combination. The use of AI in the finance, marketing and medical sectors is growing exponentially. By contrast, the legal sector is being left behind, and this is happening despite the more than adequate opportunities available. We will take you through three potentially valuable use cases. Each use case has evident added value and we have used it at our customers over the past year.
Quality information counts
Virtually all legal work stands or falls on the quality of the information that the lawyers can use to base their arguments on. Problems in legal practice can often be traced back to incorrect or incomplete information, with the result that the lawyers are unable to analyse the information effectively. The outcome is that legal advice is accompanies by a lot of assumptions, ifs and buts, poor communication and high legal costs for the work done. Work that is in fact superfluous or could have been done much more quickly.
Ever increasing information, distributed across the organisation
Businesses have to deal with an exponentially increasing volume of data and information. Lawyers are not always in a position to gain ready access to it. The relevant information is distributed across several source files: hard disks, emails, Sharepoint, a legal database, contract management systems, virtual data rooms (VDRs) and financial data systems. The data sources are silos without a central overview or central access. Worse, it is often the case that, when it comes down to it, the quality of the information leaves a lot to be desired. Information is poorly structured and updated, and mutual links and an overview are lacking. For these reasons alone, the options provided by data analysis software deserve greater attention from the legal sphere.
Data analysis software helps
Where lawyers do make use of data analysis software, they usually employ it for e-discovery or forensic or competition law research. Slowly but surely it is also being put to use in operational legal areas. A sound basis for operational legal use is a data analysis platform like ZyLAB. On a platform of this kind lawyers are able to gather, cluster and mine data. This is significant, as it means that document research is quicker and provides greater insight. Data analysis of this kind is also termed Technology Assisted Review (TAR). Legadex is developing new fields of application at high speed and is devising problems to “educate” the software, as it were.
Example of the options: 3 use cases
1. M&A preparation and due diligence
Efficiency in the preparatory phase
Valuable time is often lost during the preparatory phase of a company acquisition on the quest for all the relevant information and on evaluating it. Data analysis provides the option of rapidly and efficiently collating all the information from different sources within the business by means of algorithms and clever ‘queries’. So as to cluster and index this information and to make its content intelligible. This takes place through smart reporting and summarising functions. It means that a large part of the manual work is obviated and the time for preparing the deal is cut short.
Large strides have now been made in:
- auto-classification of documents into the VDR folder structure,
- automated selection and review of documentation for relevance and materiality,
- increased speed in indexing and naming M&A documentation.
The data room, in which aspects such as finance, insurance and pension have not yet been completely classified automatically, is still under rapid development. This is because the underlying criteria are insufficiently recognisable for the software. We are gradually developing these components further, in collaboration with other market players, with the aim of taking the M&A information process to a higher level of automation and intelligibility.
Vendor due diligence
In preparing an M&A, being able to find and analyse relevant documents is important, apart from providing the documentation. Here once again data analysis can be of service. In the first instance to the vendor and the business being sold. And in the second to all the consultants involved, such as lawyers, accountants, corporate finance specialists, tax experts and bankers. By contrast with a traditional VDR, a data analysis platform offers the option of ‘playing’ comprehensively with the information, in order to generate reports and answer specific queries. Consider for example automated generation of summaries of contractual parties and contract termination dates, or of a good overview of guarantees issued.
By highlighting particular words automatically, lawyers can speed up analysis. One example is highlighting words like ‘terminate’ or ‘assign’ in an investigation into whether legal relationships can be transferred. Once the data have been structured and analysed on the data analysis platform, they can be transferred to the traditional VDR - and then presented to bidders. In this way, the selling party can conduct its vendor due diligence to the best advantage. It is then streets ahead in the Q&A process with the information and knowledge on offer.
Transfer of loan and real estate portfolios
A data-analysis platform can also be useful in transferring extensive loan and property portfolios, particularly in the banking and real estate sectors. Entities in these sectors are able to adjust their data analysis software to:
- collate information on loans and property from different ICT systems,
- subsequently combine this information into coherent dossiers,
- present the documentation contained in a clear context,
- and render it fully searchable for legal or financial due diligence.
This means that the entities can conduct largely automated searches for example into the general banking conditions that apply or established security rights. Another possibility is to link loan agreements to the appropriate mortgage deeds. Document categories, for example loan agreements, can be efficiently analysed in clusters. This leads to a rapid acceleration of the vendor due diligence for those involved, such as lawyers.
2. Contract review
The use of data analysis for reviewing contracts is now increasingly standard. Businesses often struggle to gain an overview of and insight into important conditions in contracts. Especially when the numbers are large and the reporting functions in the ICT systems being used fall short. The range of data analysis software, especially from the English-speaking world, also focusses increasingly on contract review. This is where the fastest results can be achieved. Systems like Kira, Seal and eBrevia are good examples, or a more widely applicable system like ZyLAB.
Some of these systems offer detailed search functions, by means of which outcomes to many frequently asked questions in the review can quickly be gained. Businesses can use the outcomes of the contract review for operational questions or as part of due diligence, for a single transaction or for specific projects. With a view to Brexit for example, an interesting question could be to ask which contracts of a particular business English law applies to. Or which guarantees issued by another party are still in force.
3. Automated redaction or blacklining
Privacy and data protection rules are becoming increasingly stringent. When sharing information with other parties, lawyers are usually for this reason required to render personal data in documents anonymous. Consider here details such as name, date of birth, address, account numbers and signature, faith and political leanings. Anonymising is done by ‘blacklining’ or ‘redacting’. Redaction of commercially sensitive or confidential information can also be necessary in M&A processes, as a result of contract conditions or where information falls under professional confidentiality.
Lawyers still often redact this sort of information with a black pen on hard copy, which they then scan in once more. In other cases they may well use software in which the black pen is replaced by a digital pen. But everything is still inspected with the human eye. This is an extremely time-consuming and costly process given a large number of documents. Data analysis software can speed this up enormously.
Firstly because the documentation is classified and easily searchable. But more importantly, using data analysis software, lawyers can search for sensitive personal data on the basis of input criteria. They can then have it redacted automatically. The amount of information that can be automatically redacted depends largely on the type of information. If for example a lawyer wishes to redact the names of persons, and is able to supply a correct list of the names, then automated redaction delivers good results. By way of support, lawyers can also work with so-called ‘text mining lists’. The data analysis software then generates its own list of personal names, for example from names that the software has encountered in the documentation. A lawyer can check a list of this kind, alter it where necessary, and then use it for automated redaction. Completely automated document redaction is currently rare, but the time gained from partially automated redaction is considerable: from 50% to as much as 90%.