How alt data is helping law firms get justice for their customers
AI, and ML are helping legal teams gain an information advantage over opposing counsel, putting certain aspects of ‘discovery’ on autopilot, and enabling firms to increase their caseload capacity.
In this article we will discuss:
- The value AI applications are bringing to the legal process
- Alt data driving in-house legal analysis software
The value AI applications are bringing to the legal process
A legal team working on building a case for a client requires a lot of research regarding the specific case at hand, as well as the legal jusrisdiction, and context in which said case pertains to. This may take the form of:
- Previous verdicts
- Historical data regarding past cases
- Background/digital presence of the litigating parties, among others
This is a labour-intensive endeavor, and as such data-driven algorithms are helping litigation, and defense teams:
- Automate the data collection process
- Put ‘discovery’ on autopilot enabling teams to discover information they may have never otherwise known about
- Make building a case more cost, and time-efficient
- Helping firms increase the caseload they can handle without the need for hiring a large number of interns or junior lawyers to do intensive research projects
Law firms using AI, and ML thus stand to gain an information advantage over their competitors which can make or break the desired outcome of a client’s case. Some firms prefer to use third-party software such as:
- LegalMation: Using a live feed of open source data collection this platform helps professionals automate routine litigation tasks. This includes things like jurisdiction-specific discovery requests, and pleadings.
- Judicata: A data-driven automated briefing insights generator that empowers litigation teams to more broadly analyze their arguments, against cold hard facts.
But sometimes, nothing beats, a customized, in-house data-driven legal analysis software.
Alt data driving in-house legal analysis software
Many times third-party AI software, much like the ones just mentioned, are very efficient for legal research. That is great, and firms using them will have a leg up. But one has to remember that these companies have a Software as as Service (SaaS) model, meaning it is likely that other, competing firms are using them as well.
This is where in-house legal analysis tools come in handy. When you are the sole user/proprietor of tailored software, your comparative advantage grows. When you are collecting, and feeding said algorithms alternative data sets customized to your needs, your information advantage explodes.
Here are some examples of unique ways in which alt data can be leveraged to your law firm or corporate legal team’s advantage:
Building a corporate digital profile
In a case where you are representing one company versus another, especially when dealing with defamation or libel cases, you will want to have a clear picture of who you are dealing with beyond what is presented to you. Data collected from search engines, business/social profiles, and news sites can more accurately help you paint that picture. For example, you may come across a group of early-stage companies who experienced predatory or patent-infringing behavior by one of the litigating parties, effectively strengthening your ‘motion to dismiss’. Or you may come across a news story of a similar case whose verdict, and arguments can help you win a case on your client’s behalf based on legal precedent.
Finding dirty laundry
The uncomfortable truth is that finding a piece of information that paints a rival in a negative light, or their actions as a behavioral pattern may be all you need in order to have a case dismissed. For example, a company may have put out false advertising in the past, having thought that they did a good clean-up job but there may still be ‘digital residue’ of their previous misconduct. By searching for earlier online paid campaigns by said entity, you may come across enough materials to have the other side back down or ease both sides into a more amicable settlement agreement instead of heading directly for litigation.
Discovering ‘chemical X’
‘Chemical X’ refers to the unknown ‘secret ingredient’ that can help a chemist concoct a cure, it means finding the ‘mysterious’ component that has the capacity to help you hit that home run you have been searching for. You can’t know what you don’t know, which is where crawling the entire open-source web for data comes into play. Data collection allows you to define certain keywords such as names of :
- Corporate interests
- Key players in a specific case
Allowing you to discover information that your legal opponent does not have access to so that you can build a case with a unique angle. Yes, you may have to submit this during ‘discovery’ or maybe it just comes to light during your routine, real-time crawling efforts meaning you only need to submit this information to courts once it surfaces as ‘new evidence’ or ‘contextual circumstance’.
A good example of this may be a group of people, who are filing a class action suit against an enterprise that you are representing. By scanning the web, you may come across a social group or some other kind of correlation between the people involved, proving that they premeditated their activities, and were acting to entrap your client.
The bottom line
Data-driven algorithms are serving those in the industry who are looking to become more efficient, increase their caseloads, as well as research capacity without necessarily having to hire large quantities of junior employees in order to facilitate those needs. But these systems are widely available, minimizing the competitive advantages that they offer.
On the other hand, in-house legal analysis software powered by tailored alternative data is where legal entities and corporations can really gain information superiority over their peers and competing entities. Discovering crucial pieces of information will be what ultimately enables them to build clad iron cases, solid defenses, and the ability to drive two reluctant parties into amicable mediation.