Managing Legal and Expert Expenses When Plaintiff Demand Exceeds Projected Case Value

One of the pressing challenges for commercial auto claims handlers is determining how to account for legal, expert, surveillance, and other claim expenses when a plaintiff's demand significantly overshoots the case's projected worth. It's not simply a matter of adding up all potential litigation expenses and increasing the offer; it’s about knowing if and when these projections justify moving beyond initial valuations to settle effectively.

Loss Adjustment Expense (LAE) includes all costs related to the defense of a claim, such as attorney fees, expert witness charges, and investigation costs. Typically, many companies approach these expenses as unavoidable add-ons, tracking them separately from indemnity payments, but this can miss the mark for a realistic financial strategy. While some companies avoid factoring total loss costs (indemnity plus LAE) into settlement calculations to prevent artificially inflating settlement benchmarks—especially with a known plaintiff’s lawyer—others adopt a “think net” strategy to better project a case’s total cost. This perspective becomes particularly useful when a case is likely to go to trial, and when the plaintiff's strategy could result in extensive discovery that requires the defense to hire additional experts and/or conduct more discovery than anticipated, including the expense of multiple depositions. Assumptions about evidentiary challenges and their outcomes can also be critical factors in calculating future LAE.

Whether one favors the net-loss perspective or not, a proactive approach is necessary when projecting future LAE in cases heading toward litigation. Quaker Analytics data reveals an alarming trend for companies relying solely on estimates or experience-based judgment: the actual LAE paid can deviate by 22% to as much as 200% from initial projections. These disparities stem from factors like shifting case dynamics, plaintiff’s strategic pivots, and adverse pre-trial rulings - each carrying unique cost implications and complications. As a result, not only is the LAE reserve thrown off, but the overall claim cost can also skyrocket, often exceeding set bodily injury (BI) reserves and leading to steep, unexpected financial impacts.

The LAE Expense Model (LEM) developed at Quaker Analytics offers a data-driven solution to counteract these unpredictabilities, delivering enhanced accuracy in future LAE projection. Rather than relying on intuition or personal judgments, the LEM leverages Quaker’s extensive database of paid LAE figures from similar past cases, factoring in specifics like case type, venue, and plaintiff representation. This approach has shown promising results, particularly in reducing LAE reserve discrepancies, leading to more balanced BI and LAE ratios and helping prevent runaway expenses.

A critical part of optimizing case strategy involves understanding both the historical LAE data and the case-specific dynamics that can influence trial outcomes. Quaker Focus™, Quaker's proprietary focus group tool, can assist claims teams in testing the viability of potential defenses and examining the nuances of case value, guiding an effective settlement strategy. For example, attorneys may find it beneficial to spend additional legal and expert expenses to reach a reasonable demand figure, avoiding the potential for a costly, protracted trial. A strategic, data-informed focus group approach can substantially shift the negotiation landscape, ensuring teams base their valuations on sound predictions rather than best guesses.

By embracing a model-driven approach to LAE projection, that is based on actual historical paid LAE on similar cases, teams can achieve more accurate LAE reserving practices, reducing the risk of substantial LAE reserving variances and adjuster bias, which we discuss below. The combination of historical LAE data, focus group insights through Quaker Focus™, and our LEM tool enables claims managers to approach each case with a more reliable, data-backed strategy that aims to improve case outcomes and cost management.

Finally, Quaker Analytics’ data reveals a correlation between claims handler experience and LAE projections accuracy. In cases managed by less experienced handlers, LAE variance from the projected amounts was often considerably higher or lower than what was actually spent. This led to substantial over or under LAE reserving and the potential for bias, one way or the other, either increasing the settlement offer by too much or not enough. This variance highlights the benefit of having a structured model like LEM that ensures even the less-experienced team members have robust, data-backed resources to inform their decisions.

Bias plays a critical role in future LAE projections, as an adjuster's personal inclinations can unintentionally influence the numbers. For instance, if an adjuster wants to push the case toward trial, they may underestimate the projected LAE to keep the amount added to the settlement offer low. On the other hand, if the adjuster prefers to avoid a prolonged case—perhaps due to difficult negotiations with a particular plaintiff attorney—they might inflate the LAE projection. This higher projection, in turn, allows them to justify adding more to the settlement offer to increase the likelihood of a quick resolution.

For those ready to bring a more predictable and optimized approach to case management, a demonstration of the Quaker Analytics LAE model can provide first-hand insights into how this data-centric model can improve future reserve accuracy and decision-making throughout the litigation process.