Use Cases
Use case 1: Taking a case to trial
Use Case: Supporting the Informed Decision to go to Trial
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Client: A specialized nationwide medical malpractice insurance company
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Solution: Agatha’s predictive analytics for litigation risk assessment
Challenge:
For complex, high-stakes malpractice claims, the decision to settle or proceed to trial can have enormous financial consequences. The company’s leadership team, including its board, is often faced with situations where traditional judgment could benefit from an AI, data-backed, assessment. This is particularly the case when evaluating whether a plaintiff might win or whether the company might get hit with an excess verdict.
Agatha in Action:
The company implemented Agatha’s predictive analytics to support its claims and litigation strategy teams with data-driven insights. Two key features directly inform high-level trial decisions:
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Indemnity Probability Prediction
For any given case, the platform estimates the probability of a plaintiff verdict, using a combination of jurisdictional data, plaintiff attorney track records, expert witness histories, case narratives, and other contextual factors. This allows decision-makers to understand the likelihood of liability in objective, probabilistic terms with a new level of precision. -
Nuclear or Excess Loss Estimate
Even in cases where a defense verdict is plausible, carriers must consider worst-case outcomes. The system estimates the chance of a verdict exceeding the policy limit, flagging those rare but catastrophic scenarios that justify settlement despite low overall risk. These estimates factor in venue, severity cues, and past nuclear outcomes in similar contexts.
Result:
In a recent high-profile claim, the team chose to take a case to trial, based on a favorable indemnity probability estimate and a low probability for an excess verdict. The estimates helped persuade the board that the company could proceed to trial with a strong defense, rather than pay a high-demand settlement. The jury ultimately returned a defense verdict, avoiding both indemnity and reputational exposure.
Impact:
The predictive system has become a trusted component of board-level decision-making. It helps shift the conversation from “What do we feel about this case?” to “What does the data tell us in this case?” leading to more confident, transparent, and defensible trial strategies.
What Agatha users had to say about it:
“Using the nuclear loss report helped us move our CEO and the chair of the claims committee from granting us settlement authority to granting us trial authority”
“Using similar claims and nuclear loss reports is certainly useful when the defence counsel is close to a 50-50 split”
“The County variable is very helpful as well as we may not have a ton of experience in each venue”
Use case 2: Reaching a fair settlement value
Use Case: Reaching a fair Settlement Value Early-on and Proactively
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Client: Ophthalmic Mutual Insurance Company
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Solution: Agatha’s predictive analytics for claim valuation and strategy
Challenge:
In many complex malpractice cases, the claims team recognizes that a settlement is desirable. But they often wait for a demand from the plaintiff before formulating an offer and hopefully arriving at the fair number. This happens because justifying a high settlement value to both the board and the insured physician can be politically and emotionally challenging. Boards are reluctant to authorize large payouts without clear justification, and insureds are often hesitant to settle cases when they believe they did nothing wrong. The usual consequences are longer claims resolution cycle, higher legal fees or LAE, and eventually an aggravated indemnity to settle.
Agatha in Action:
To address these challenges, the insurer deployed Agatha’s predictive analytics to support early, proactive, facts-based settlement planning. Two features are central to the process:
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Similar Claims
The platform surfaces a curated set of prior claims that closely resemble the current case accounting for fact patterns, injuries, jurisdiction, plaintiffs, and defense dynamics. These precedents allow the claims team to demonstrate that the proposed settlement falls within a rational, data-backed range and is consistent with past outcomes. -
Indemnity Estimate
Based on historical data, both market and internal data, and advanced predictive algorithms, the system provides an indemnity range that accounts for venue, injury severity, allegation, demographics, plaintiff/defense counsel patterns, and historical jury behavior. This estimate becomes a defensible anchor for the recommended settlement number, offering a quantitative benchmark to guide negotiations and internal approvals.
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Result:
In one recent ophthalmology case involving a catastrophic injury, the claims team faced pressure from both the board and the insured to reject a pre-trial settlement demand. By presenting a matched set of similar past cases, alongside Agatha’s indemnity estimate, the team secured board settlement authority and obtained the physician’s consent. The case was settled within predicted range, avoiding trial risk and preserving relationships.
Impact:
The platform empowers claims professionals with the data needed to justify difficult settlement decisions. It transforms what used to be a subjective negotiation into a transparent, evidence-based process, facilitating internal agreements, protecting the insured, and reducing the risk of runaway verdicts.
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What our users had to say about it:
“Sometimes, you just feel that a case looks bad, and Agatha confirms everything: the severity, the liability, etc.! Having access to Agatha allows us to obtain earlier-on settlement consent from the insured and settlement authority from the CEO and the chair of the claims committee; this significantly mitigates the loss”. (Randy Morris Claims Specialist)
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