The legal sector is still in its infancy when it comes to big data and analytics. Lawyers and law experts are trying to figure it out, and consternation continues to shadow some corners because not everyone can quite understand what analytics is and how it can improve the personal injury law industry.
Are they still legal experts if they use a computer? Many lawyers have a misconception that their brain is trained, their judgement is invaluable, and their personal experience is their best weapon. This misconception comes because they mistake analytics for AI. Using analytics implies utilizing data to supplement the knowledge, judgement, and experience in the decision-making process and evaluating the situations from a new perspective.
But even if many personal injury lawyers find it hard to believe their clients are ahead of them in using big data, potential clients are looking for law companies that are using it to provide them with better service. The firms that bill their clients on an hourly rate tend to experience internal tension because they believe that analytics would disturb their profitability. However, they can still earn money and be efficient because their clients are pushing their incentives.
Therefore, they should be willing to integrate technology into their processes and do alternative fee agreements to use big data to accelerate cases. Instead of building revenue by the amount of time they spend with a client, they can do it by solving cases effectively and fast. It is becoming clear that big data is of value to the legal profession.
How can personal injury companies use analytics?
When a prospective client approaches a law company that handles personal injury cases, it’s challenging to calculate their case’s value. Experienced lawyers can become proficient at predicting the outcome and duration, but that comes after many bad guesses that cost them money. Data analytics is popular in many industries for monitoring customer behavior and helps companies make informed decisions. Law companies can use analytics to learn more about certain categories of cases and predict outcomes.
Analytics can help them predict payouts
Clients always want to know how much they would receive for a personal injury claim. Lawyers lacking extensive knowledge engage in a guessing game, which isn’t always working to their advantage. But if they use predictive analytics, they can determine how much each case pays out, considering factors as the number of previous cases filled with the same judge. The technology allows them to offer fact-based information and helps them decide if the case is worth legal action.
Big data is also useful in court when the lawyer can provide research to back their statements. When the risk of recurrence for a malpractice case is high, for example, they can convince the judge to be more generous in rewarding the client. Analytics can also help personal injury lawyers to learn more about a specific judge to tailor their arguments.
Big data can help lawyers chose cases
Law firms decide which cases they take on a daily basis. Even within the framework of personal injury law, they get calls from people looking for representation. When the companies have data on the category of cases that usually win, they focus on these, refusing the ones that are tough gold.
Analytics are also useful after taking a case because it helps them comb through past cases and track information that can serve them to solve present cases. This piece of information can help personal injury lawyers build a case because they can review past judgements and form arguments. With analytics tools at hand, they can easily scan data before making a decision that impacts the case, boosting the chances to win when they go to court.
Big data helps law firms find the human connection
Juries and judges are humans and citizens, and therefore they have outside interests. By using analytics, personal injury lawyers can learn more about the residents of the community their clients are part of and form arguments that appeal to the juries’ human connection with the clients. With the help of big data technology, the law team can discover that many people in a particular town have lost their jobs recently, making the argument for lost wages more touching.
Juries are instructed to disregard emotions and make decisions based on facts, but it doesn’t mean that they always respect it. Even if they use only a small amount of their personal judgement when voting, a personal injury lawyer can use the information analytics provided to them to point out facts important for them. For the above example, they can give specific amounts for medical bills, lost wages, and suffering and pain to help the jury resonate with the client and base their decision on their feelings.
The impact of predictive modelling on personal injury cases
Predictive modelling is a technology that evolved together with big data analytics. For the personal injury law industry, it’s a tool that is slowly gaining popularity, so it’s likely to become part of most claims shortly.
Predictive modelling handles the less obvious or even hidden claim outcomes. A personal injury expert’s decision becomes increasingly opaque when they use this technology. Most times, hidden predictors can make a case less predictable, which isn’t always bad. When a claim includes a hidden factor, the lawyer can convince the insurer to make a higher-cost compensation offer to protect themselves from more extensive damage they would experience in a suit. On the other hand, insurers can also use this technology to identify hidden factors that can point to fraud and respond accordingly.
As big data becomes more commonly used in personal injury cases, some lawyers may be concerned that some personal information about their clients is divulged in the court and, therefore, impact the outcome. In this area, many aspects still require clarification on how deep a search can dive and the limit for unveiling information to public discussion.
Big data and predictive modelling is happening, and personal injury lawyers need to find a way to integrate them into their work.
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