It is said that “Las Vegas is the only place where money really talks, it says Goodbye!”
Well, fifteen years ago, I almost lost everything, and it was not even in Vegas. The reckless actions of a business partner devastated years of work. I pursued damage compensation, but was never compensated.
So, I went back to law school, and realized that the law was designed so that compensation is highly uncertain and hence unfair when damages exist but are difficult to quantify. Though there are a handful of extremely over-compensated damages, the vast majority are under-compensated.
The difficulty of non-quantifiable damages extends to the insurance field. As an example, in an auto accident, the material damages are easy to quantify, but what about the pain and suffering? How does one quantify the loss of engagement in family life?
The last two years have seen accelerated traction for us, with several collaborations, the most recent partnership being with Great American Insurance Group. Today we are a multidisciplinary team of lawyers trained in data science. We build an iterative path from good law, to relevant data, and to accurate prediction. Essentially, we add science to the art of claim adjustment.
Our value proposition to insurance carriers combines improved efficiency (measured through a reduced loss ratio) and better customer service (through consistent and fair compensation). Both being key to sustain long-term profitability.
For example, when a P&C insurance carrier implements our solutions in their claims management, they can reduce their loss up to fourteen percent only by avoiding nuclear verdicts, and by at least one to two percent on all other claims; this is achieved through efficient trade-offs between settlement and litigation and optimized payouts in both resolutions. On top of that, we have estimated a reduced legal expenditure of six percent.
I will now share selected screenshots of our software. For those who are interested in a full demo, we can talk later.
Optimalex’s flagship solution, AGATHA, is capable of reducing uncertainty in damages of several use cases: including personal bodily injury in motor vehicle accidents, slips, trips, and falls, general liability, and workers’ compensation.
AGATHA, can accurately predict the outcome of a case and quantify damages whether litigated or settled. The process is simple: users document claims with information mostly available in their systems on the jurisdiction, on the parties, on the injuries, and then input them into our SOC 2 certified platform.
Imagine this: an insurance company receives notice that an auto accident is at risk of going to trial. The adjuster is initially confident that this claim will be as ordinary as they come. Initial reserve and settlement offer are set accordingly.
In the first scenario, AGATHA predicts a damage award of $187,000 if we go on trial, with a win rate of 57%, and 6% recovery rate. It is clear that settling the claim at this value would be fair for all parties. This claim is flagged by AGATHA as needing prompt settlement.
The second simulation involves different judges and lawyers. The new combination of circumstances for the accident includes a traffic sign violation from the defendant and additional serious injuries on the plaintiff. AGATHA reveals this incident can potentially cost ten times more than the previous one (up to $1.7 million!) with a win rate of 70%, and 72% recovery rate. The initial reserve will likely fall short of the potential award if this incident goes to trial. AGATHA flags this case as needing a more generous settlement.
AGATHA is also user friendly and intuitive with many features to improve workflow. For example: The user can view all the simulations they did over the lifecycle of the case and decide which one to use as their base case.
They can also access statistics and pie charts to compare compensation benchmarks with top 100 similar cases. Users also have the option to effortlessly share a case. Most importantly, they can close a case, which automatically saves the results and improves the algorithms for future estimates.
I would like to thank InsureTech Connect and State Farm for sponsoring this event. Please let me know your questions.