What is Legal Analytics?
The process of incorporating data into decision making on topics affecting law-firms and lawyers, like matter-forecasting, legal- strategy, and resource-management is called legal analytics. It provides a competitive advantage by providing transparency and insight into in-house counsel members, departments, and decision-makers. The road map of evolution of Legal Tech is shown below.
Why data science is important to legal-sector?
(1) The world is becoming increasingly quantified. All businesses are becoming data-driven. As data stores in our sector grow, so will the latent value within it, to harness which data-scientists will be needed.
(2) Some corporate legal firms have already created formal roles for “legal data scientists” and started work with legal and risk teams to invest in data-strategies and new techniques to harness value from data. In fact, the 2018 Gartner State of the Legal Function Survey showed that 14% of legal departments have already hired a non-lawyer to serve as a dedicated “legal data scientist”. Other law firms will find themselves in a precarious position if they do not follow the suit, missing out on opportunities to improve the client experience, to mitigate risk, and to maximize the profits.
What are the types of data analyzed in legal analytics?
Data in the legal sector generally falls into three categories:
(1)Individual data
It is data is related to existing and potential clients’ online activities on law firm's website. This data is sourced from places like Google Analytics, email campaigns, click-stream analysis, cookies etc.
(2)Internal law firm data
Internal data comes from your law firm’s daily activities like billing rates and time tracking. Industry data comes from third-party research groups to determine legal industry trends, such as with the Legal Trends Report2.
(3)Legal industry data
In the past, it took tremendous labor to gain any meaningful insight from the vast amounts of legal data available. But with the advent of technologies like ML,AI, and NLP; lawyers now have the tools available to take data-driven approaches when formulating case strategy, forecasting case outcomes, and even obtaining new clients.
What are the latest technological trends in law?
According to a research by reputed firm Gartner1, following five major trends are observed in legal industry post COVID pandemic.
(1) By 2025, legal departments will increase their spend on legal technology threefold.
(2) By 2024, legal departments will replace 20% of generalist lawyers with non-lawyer staff.
(3) By 2024, legal departments will have automated 50% of legal work related to major corporate transactions.
(4) By 2025, corporate legal departments will capture only 30% of the potential benefit of their contract life cycle management investments.
(5) By 2025, at least 25% of spending on corporate legal applications will go to nonspecialist technology providers.
What are some applications of data-science in legal sector?
(1) Due diligence:
Due Diligence is the confirmation of facts and figures and a thorough assessment of a legal situation. The process can also be very time-consuming and tedious. Lawyers need to conduct a comprehensive investigation for meaningful results. As such, lawyers are also prone to mistakes and inaccuracy when doing spot checks. Litigators perform due diligence with the help of AI tools to uncover background information. E.g. Kira Systems13 founded by ex M&A lawyer has made a solution that is capable of performing a more accurate due-diligence contract-review by searching, highlighting, and extracting relevant content for analysis. The company claims that its system can complete the task up to 40 percent faster when using it for the first time, and up to 90 percent for those with more experience. Other companies making similar solutions are: Leverton14,eBrevia15,JP Morgan16, LawGeex18, LegalRobot19 ,CaseText20 etc.
(1) Leverton's solution is capable of reading contracts at high speeds in 20 languages.
(2) eBrevia's solution can analyze more than 50 documents in less than a minute with 10 percent more accuracy than a manual review process.
(3) J P Morgan's program ‘COIN’ extracts 150 attributes from 12,000 commercial credit agreements and contracts in only a few seconds. This is equivalent to 36,000 hours of legal work by its lawyers and loan officers.
(4) LawGeex claims that with their tool, law firms can cut costs by 90% and reduce contract-review and approval time by 80%. It lists Deloitte and Sears as clients.
(5) CaseText claims to allow lawyers to forecast an opposing counsel’s arguments by finding opinions that were previously used by lawyers.
(2-A) Descriptive Analytics
Lawyers often have to go through vast amount of past case histories, court verdicts, legal precedents etc in limited time. ML based classification algorithms can easily analyze this huge data and summarize important actionable points quickly.
(2-B) Predictive Analytics
One proof-of-concept, investigated by at FastDataScience10 was the possibility of using ML to identify criminal cases that are likely to lead to a successful prosecution.
Likelihood of a successful prosecution in criminal cases depends on a number of factors: witnesses, witness statements, ages of witnesses, type of court, type of crime and many other factors. If outcome can be predicted using ML with high probability than the strategy for whether to fight or go for arbitration can be decided. A firm Lexmachina11 which claims to predict case outcomes using Law-Firms can use predictive analytics for three main use-cases.
(A)For forecasting how long a case will last to the likelihood of winning, predictive analytics can help attorneys provide trends analysis, correlations, and irregularities to build a case, devise litigation strategies, and evaluate suspects.
(B)Departments can also use predictive legal analytics in their hiring process to help them assess potential candidates and create the best team composition.
(C)Predictive data analytics can help lawyers cover all their needs—from deciding if they need external counsel, consultants, partners, or freelancers for projects.
Some well known tools in this space are Premonition5-a, Brainspace5-b, LexMachina5-c
Following are three main research examples of successful algorithmic prediction of outcome of court cases.
(3) Legal Research:
Identifying appropriate precedents or statutes could give a lawyer the edge in court. But conducting smart legal research that’s thorough and accurate is laborious and time-consuming process. Legal analytics tools can help a lawyer find relevant cases in any practice area without manual labour. Earlier also the information was available digitally but through expensive platforms only.
Today, however, numerous excellent free tools available online—making free legal research a viable option for law firms. E.g.,
(a) Fastcase3-a: For an online law library
(b) CourtListener3-b: For legal opinions
(c) Caselaw Access Project3-c: For book-published case law
(d) FindLaw3-d: For searchable Supreme Court decisions
(e)Legal-Info-Institute3-e:US-law-Online&legal encyclopedia
(f) Casetext and ROSS3-f: For AI assistance
(g) Justia3-g: For the latest summaries sent straight to you
If it is required to refer primary source directly then refer:
(a) US Office of the Law Revision Counsel4-a
(b) Bound Volumes of the Supreme Court4-b
(c)Rulings from regulatory and administrative agencies4-c
(d) Financial Crimes Enforcement Network4-d
(e) Equal Employment Opportunity Commission4-e
Reliable Legal Blogs are other great sources
(a) American Bar Association's Annual list5-a
(b) LexBlog5-b
Finally a great resource is Google Scholar4-f
To fetch relevant data from all these comprehensive sources ML techniques like web-scraping are required. Finally to find actionable insights from this huge data big data analytics and NLP are required. The fact that >80% of this data is unstructured makes the task challenging.
(4) Document Automation And Management:
Legal profession involves huge amount of paperwork. Hence document-automation can greatly help in it. It can help in creating a high volume of documents in a short period of time while being compliant and maintaining a consistent brand. It allows a firm to automate document creation using intelligent templates and provides a centralized process of producing all legal documents thus optimizing the way lawyers work. Document management ensures that the document is easily accessible, well organized, and secured for future access, edits, and sharing.Tools which offer both automation and management of documents are really handy e.g., Clio Manage24, PerfectNDA25
(5) Intellectual Property:
The process for securing patents, copyrights and trademarks can be long and arduous and involves looking into thousands, of results. This takes long time if done manually. On the other side, patent-filing is a time-sensitive process which must be done as quickly as possible. Manual way of handling it is self-defeating.
However, now some companies are emerging that provide solutions which take at least part of the load in above process.
E.g. TrademarkNow26 is a company whose IP solution returns search results in less than 15 seconds (ranked according to relevance) which manually would take weeks. ANAQUA Studio27, is specifically designed for drafting patents and prosecution and claims that it saves 4-20 hours of lawyer's time.TurboPatent from SmartShell28 reported 500-800% improvement in productivity for their para-legal staff.
(6) Electronic Billing:
Managing legal expenditure is one of the automatable tasks that the majority of companies handle manually using spreadsheets. With AI, companies can reduce paper costs, decrease human-made errors, and achieve more accurate insights about their legal spending. Here is a list of AI-powered electronic billing vendors: Brightflag29, Smokeball30
(7) Fasten Courtroom Procedure:
Here big data analytics can help greatly. Most important problem of legal system in many countries like India is the huge backlog of cases which results in delay of years before verdict comes. The main reason is humongous amount of data which courts and lawyers have to deal with.ML based solutions can help to correctly collect, store, catalog, and organize all the data so that it can be useful at the right time. This will enable the access of references from anywhere and answer the questions asked in the courtroom with clarity and evidence.
(8) Evidence Mining:
With use of internet becoming ubiquitous cyber-crimes are increasing. E.g. credit-card frauds, online payment frauds. To detect and prevent such frauds banks use ML and AI powered solutions. Still, many cases go into dispute and lawyers on both prosecution and defense side must hire data-scientists to make sense of available evidence and and make proper argument. Even in conventional crimes examining finger print, genomic sequence, photographs from the police database of millions of criminal used to be time-consuming but with AI and ML based techniques, often it can be done in minutes. This results in quicker detection and higher conviction rate.
(9) Increased Client Base:
Use of AI, ML and automation leads to two big benefits which gives a law-firm ability to handle more clients.
(A) Improved Productivity:
Legal work is highly monotonous and cumbersome. AI can improve productivity to a great degree by automating tedious day-to-day tasks which don’t really require any expert input, thus enhancing the efficiency and accuracy of legal procedures. Lawyers in the UK are all familiar with online resources such as LexisNexis12, which use NLP to assist in information retrieval.
(B)Better profitability:
AI analytics can have a positive impact on almost every aspect of a legal firm, including accounting, advertising and client procurement. Machines can rapidly detect patterns across massive amounts of data in order to establish certain connections and trends, and even inconsistencies. Spotting such patterns in advance can enable legal firms to delegate assignments in a way that ensures exemplary legal services and run more profitably and efficiently.
(10) Contract Management:
current AI applications in legal contracts can be classified as follows:
(1)Retrospective analysis of previously signed legal documents – In large-organizations which sign many documents every day, NLP platforms are being applied to extract metadata.
(2)Information extraction from legal contracts.
In future, AI can perform well in following two potential cases:
(1)Cases where a quantitative factor (like term of an agreement or a share percentage) needs to be changed.Current AI is very capable in identifying and suggesting change in such factors.
(2)Cases where changes in contractual language such as rephrasing some sentences is required. This is a more complex task requiring knowledge of legal jargon. This is highly nascent and Current NLP platforms find such tasks very difficult.
A good practical example of this use is NLP based platform Klarity9.
The benefits of AI based contract management are shown below
(11) E-discovery:
This refers to use of electronic methods for preserving, collecting, reviewing, and exchanging case-related information. With e-Discovery analytics software available during litigation and investigations, the process is now a whole lot easier. Instead of having to go through a large volume of documents, lawyers can filter documents by date range or specific keywords. This eliminates the need to manually comb through huge data. A great product for this is logikcull4-g.
(12) Legal marketing analytics:
Legal marketing analytics can help lawyers to understand their ideal client, and where their practice stands compared to competitors, so they can devise a more effective marketing strategy that resonates with their target audience. In addition, legal analytics software can analyze where your prospective clients are coming from, so you will know the best marketing channels and networking platforms to spend your marketing hours and budget on. E.g., with use of CRM platform, a law-firm can organize, nurture, and evaluate potential new clients as well as existing ones for targeted, customized campaigns.
Some well known tools in this space are Clio Grow6-a, Lawlytics6-b
(13) Derive Business Insights:
Professions of doctor, lawyer, teacher etc. also must be done like a business to survive in today's competition. So running a law firm now involves:
(a) Monitoring the right success metrics,
(b) Looking at key KPIs related to client acquisition, like the cost of acquiring a new client, the number of new prospects by source, and the estimated average value of each new case.
(c) Better understand productivity KPIs like the number of billable hours, the utilization rate and realization rate for your firm and for each attorney.
(d) Using a data-driven-approach to guide your decision making. E.g., If analysis finds that certain months of the year tend to be slower for a firm, as those slow months are approaching, the can dedicate more time to bringing in more business to prepare for the anticipated decrease in cash flow. A great tool in this space is Clio Manage7.
Challenges Hindering Legal Tech Adoption
1. Lack of understanding
The foremost challenge for the legal tech market is that many legal professionals do not have an in-depth understanding of what technologies to use and when, so as to derive better and effective outcomes. Also, they are living with the fear that the growing relationship between law and emerging technology will result in a higher rate of unemployment in the industry.
It has been found that 36% of lawyers are unaware of the set of technology used in law firms for better purposes.
2. Organizational issues
The emergence of technology in the legal sector has brought a 180 degree transformation in its business model. It has completely changed the way they attract new clients, process, and earn money. Because of this, various law firms are also facing several organizational challenges like acceptance of technology and software for daily tasks, ease of determining the scope of varied types of legal technology, practice as per the yet not proven business model, and more.
Over 34% of organizations do not look ahead to enter the Legal Tech market because of organizational problems.
3. Financial barriers
Last but not least, the expenses associated with considering technology in the future of law such as legal software development cost is also impeding attorneys from getting inclined to this idea.
30% of the organizations are overlooking the impact of technology on law industry because of financial issues.
However, legal sector is adopting the technology as the 2019 Global Legal Department Bench-marking Report31 shows (fig. below).
Following diagram nicely summarizes various areas in legal sector where AI based solutions are already developed and important companies operating in those field.
What is future outlook & predictions for LegalTech adoption?
Are there any examples of Indian Firms in Legal Analytics?
Yes! There are at five notable start-ups operating in LegalTech space.
(1) SpotDraft 32
(2) CaseMine 33
(3) NearLaw
(4) Pensieve 34
(5) PracticeLeague 35
REFERENCES
(1)https://www.gartner.com/smarterwithgartner/5-legal-technology-trends-changing-in-house-legal-departments
(2)https://www.clio.com/resources/legal-trends/
(3)https://www.clio.com/blog/best-free-legal-research-tools/
(3-a): https://www.fastcase.com/
(3-b): https://www.courtlistener.com/
(3-c) https://case.law/
(3-d) https://lp.findlaw.com/
(3-e) https://www.law.cornell.edu/
(3-f) https://casetext.com/
(3-g) https://www.justia.com/
(4-a) http://uscode.house.gov/
(4-b) http://www.supremecourt.gov/opinions/boundvolumes.aspx
(4-c) https://www.socialsecurity.gov/OP_Home/rulings/rulfind1.html
(4-d) https://www.fincen.gov/resources/statutes-regulations/administrative-rulings
(4-e) http://www.eeoc.gov/federal/digest/index.cfm
(4-f) https://scholar.google.com/schhp?hl=en
(4-g) https://www.clio.com/app-directory/logikcull/
(5-a) https://premonition.ai/
(5-b) https://www.brainspace.com/
(5-c) https://lexmachina.com/
(6-a) https://www.clio.com/grow/
(6-b) https://www.lawlytics.com/
(7) https://www.clio.com/features/law-firm-insights/
(8) https://emerj.com/ai-sector-overviews/ai-in-law-legal-practice-current-applications/#:~:text=Based%20on%20our%20assessment%20of%20the%20companies%20and,be%20used%20for%20trends%20and%20patterns.%20More%20items
(9) http://klaritylaw.com/
(10) https://fastdatascience.com/impact-ai-law-legal-industry/
(11) https://lexmachina.com/
(12) https://www.lexisnexis.com
(13) https://www.kirasystems.com/
(14)https://leverton.ai/
(15)https://ebrevia.com/#overview
(16)https://www.bloomberg.com/news/articles/2017-02-28/jpmorgan-marshals-an-army-of-developers-to-automate-high-finance
(17)https://thoughtriver.com/
(18)https://www.lawgeex.com/
(19)https://www.legalrobot.com/
(20)https://casetext.com/
(21)http://www.jstor.org/stable/4099370?seq=1#page_scan_tab_contents
(22)http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174698
(23)https://peerj.com/articles/cs-93/
(24)https://www.clio.com/manage/
(25)https://www.neotalogic.com/solution/perfectnda/
(26)https://www.trademarknow.com/
(27)http://www.anaqua.com/corporate/products/anaqua-studio
(28)http://turbopatent.com/automating-the-patent-process-a-case-study/
(29)https://brightflag.com/product
(30)https://www.smokeball.com/
(31)https://www.acc.com/sites/default/files/2019-06/ACC_Benchmark_062019.pdf
(32)https://analyticsindiamag.com/meet-spotdraft-ai-based-contract-management-platform-manages-cumbersome-paperwork/
(33)https://analyticsindiamag.com/story-casemine-ncr-based-startup-thats-disrupting-indian-legal-system-using-ai/
(34)https://analyticsindiamag.com/mumbai-startups-proprietary-legal-research-platform-is-driving-the-next-generation-of-legal-tech/
(35)http://www.practiceleague.com/law-firm/practice-management.html
