Optimalex has transformed the Ph.D. research of Frank Giaoui, its Founder & CEO, into a predictive analytics solution software that helps reduce legal risk and optimize the damages outcome of a dispute through settlement or litigation.
In this in-depth interview, Frank talks to Jus Mundi about Optimalex’s path, solutions they offer, and challenges the team faced during their decade-long journey of legal research and computer/data science development. Currently, Optimalex’s team includes lawyers, economists, engineers, and business professionals with 100 years of cumulated experience in the USA, France, and other countries.
What is the mission of Optimalex?
Optimalex is a SaaS start-up providing legal predictive analytics solutions. Our solutions support business and individual decision makers to help prevent a dispute or predict its outcome, to quantify damages, and to choose the best route between litigation, ADR, and settlement.
What is the important challenge that Optimalex is trying to address in the legal industry and what is your vision to address this challenge?
- Optimalex addresses 3 fundamental challenges many dispute’s resolutions face: they may be risky, inefficient, and sometimes even unfair.
- Our vision is to share referenced damages schedule that will help:
- reduce risks of disputes with liquidated damages provisions drafted in contracts;
- settle anytime it is more efficient than litigate;
- and maximize return on judicial investment whenever it is necessary to litigate.
- Our vision is to facilitate a shared usage by all stakeholders in the judicial sphere (lawyers, judges, experts, funders, the parties themselves).
- The vision is also to create a common language to ease the dialogue and the decisions among those stakeholders.
- Ultimately, the vision is to reduce uncertainty and increase fairness.
How did Optimalex transition from theory into reality?
- All started with an unfortunate professional experience: I was advising a start-up client to raise funds. We had approached a bunch of VCs, negotiated with a couple, and granted exclusivity to one of them who committed to invest. Eventually, the investor breached our contract and never invested.
- We failed to settle our dispute, my client went bankrupt, we filed a lawsuit and we lost: We did not have the right methods to support and quantify our damages claim.
- The law is made so that damages are awarded easily for reliance or past economic damages – those actual costs incurred – they are easily evidenced and hence compensated.
- However, expectancy damages – the business expected – are difficult to quantify whenever there is no substitute market price. The same can be said of pain and suffering damages in cases of personal bodily injury. They are often considered too speculative or subjective and hence seldomly (should I say randomly?) compensated.
- I decided to embark on a Ph.D. research in order to help improve the law which currently says that damages are a question of facts and each case calls for a “sui generis solution”. The initial idea was to build compensation schedules for damages pretty much mirroring what exists in employment law, in family law or for body injuries in tort law.
- I started with a review of the theory in academic law & economics literature and extensive field interviews with legal practitioners. This produced the first set of hypotheses describing which variables could predict the outcome and the compensatory damages. Then, with the assistance of interns from Columbia Law School (in New York) and Sorbonne Law School (in Paris), I collected and analyzed an initial sample of cases to validate or amend the hypothesis. The fundamental alternative legal theory I offered and published was to say that damages are not only a question of facts but also a question of law. As such they could generally be anticipated to reduce uncertainty.
At what point did you think about translating this academic research into a commercial product?
- It came progressively. We identified the business opportunity to work with data scientists and computer scientists in order:
- To scale up the sample;
- To improve the predictive power of the models; and
- To develop a user-friendly decision support SaaS that would serve parties, lawyers, and funders in a wide range of commercial disputes.
- Our initial entrepreneurial motivation on commercial disputes is based on three strong beliefs:
- Many litigations can be avoided altogether through better contract drafting and efficient settlements;
- When litigations are necessary, judicial decisions can improve in fairness, consistency, and certainty;
- And, AI can support lawyers’ decisions and optimize the outcome – pretty much as it currently supports medical or financial decisions.
- The result is that two good social impacts would eventually emerge:
- First, it would increase affordability for parties and optimize return on their judicial investments;
- And, second, it would reduce the burden on the legal system and focus judges’ and courts’ attention on the most unique cases.
What makes Optimalex unique and allows it to stand out from other case prediction software?
First, the team. The team is a unique blend of very experienced and younger managers; also, a blend of academics and practitioners.
- They are among the most talented people in their respective fields: law, economics, computer science, data science. So, we are truly a multi-disciplinary team.
- Yet, we all share the same passion for research, development, and operational impacts.
Then the technology: Based on our legal expertise, we have used cutting-edge ML and NLP techniques and enhanced them on damages.
- Optimalex’s distinctive technology extracts the most relevant facts and predicts the damages values to support objective settlement or litigation decisions; it actually goes as far as to predict the win rate, the recovery rate, and the grant value.
- Finally, we also differentiate by our transnational roots: Our expertise and database are designed in multiple jurisdictions on Comparative Common law and Civil law with additional references to international commercial law.
Who are your key clients, and what is your value proposition for your clients?
Our clients are lawyers working at law firms, also those working in corporate legal departments, at insurance companies or litigation funders.
Optimalex provides predictive legal analytics solutions focused on damages.
From our solutions, all types of clients can expect smarter, time-efficient, and data-driven decisions.
- Our solutions help law firms:
- Automate discovery and research at every stage of a potential dispute;
- Focus more time on higher-level thinking and expertise;
- Add strategic fees to their hourly billings.
- Our solutions also help parties:
- To optimize their risk management;
- To select jurisdiction and applicable law;
- To win if they litigate and to win if they settle.
- The value of Optimalex Solutions for insurance companies comes:
- When they assist their policy holder and when they are one party themselves;
- From objective information provided to quantify the reserve;
- From optimal settlement proposals.
- Our solutions help litigation/arbitration funders:
- To spot underserved cases;
- To identify and invest in winning cases;
- And also, to invest in cases with quicker returns.
How does Optimalex’s multi-jurisdiction prediction work with international commercial law?
Much like national law-based systems, our algorithms are built using specifically filtered and chosen decisions, under relevant applicable rules by selected jurisdictions.
Of course, international commercial law presents a unique degree of difficulty when it comes to the accessibility of the decisions. This is where our academic and research expertise come in particularly handy to access a sufficient number of decisions and study them while guaranteeing the confidentiality that the litigants were looking for.
Frank Giaoui, is an entrepreneur. He has advised corporations and negotiated contracts for three decades as manager at Bain & Company, vice president at Oliver Wyman and founder at Hera Finance. He was co-founder of Apollo Invest, Medimania and e-Kingfisher ventures. Frank is also an academics. He is Post Doc JSD at Columbia Law School, PhD from La Sorbonne Law School, teaching fellow in law & economics at University of Lorraine, and was visiting professor of corporate finance at Essec, the business school from which he graduated.