Introducing 4WARN’s Tech-Enabled Litigation Risk Score™

By Todd Kozikowski

Originally published in The Demotech Difference Spring 2024

The 4WARN Tech-Enabled Litigation Risk Score™ was created to help organizations improve their strategies by using a detailed and quantified framework to measure both the extent and nature of targeting aimed at them. 4WARN’s framework evaluates litigation risk by analyzing several risk factors, characterizing opportunistic behavior, and benchmarking the efforts focused on initiating contested claims or litigation. Equally important, 4WARN’s index evaluates the complexity of a variety of methodologies utilized by multiple opportunists in an organization’s overall risk assessment.

Once engaged with a company, 4WARN sifts through billions of data points, encompassing search engine data, cached web pages, location intelligence, micro- targeting data, historical SEO and Pay-Per-Click performance, as well as litigation data.

Constructing this comprehensive Risk Score involves various dimensions, such as demographics of the opportunists, network maturity, resourcefulness, past success, micro-targeting tactics aimed at policyholders, and the number of online engagement conversions. Finally, an evaluation of the targeted organization's endpoint vulnerabilities includes a domain audit to provide a precise and holistic understanding of litigation risk intelligence (i.e., how opportunists are using your website against you).

Once engaged with a company, 4WARN sifts through billions of data points, encompassing search engine data, cached web pages, location intelligence, micro-targeting data, historical SEO and Pay-Per-Click performance, as well as litigation data. The ultimate objective is to assist the company by establishing a risk benchmark, and then recognizing, addressing, and strengthening its response to the multiplicity of strategies underlying tech-enabled claim instigation. This results in the development of a quantifiable, objective risk score that prioritizes actionable responses that can then be analyzed comprehensively, thereby enabling a coordinated response across every organizational department, (i.e., claims, counsel, special investigation units, enterprise risk management, underwriting, digital marketing, and actuarial, as well as the chief information security officer and information technology teams). If a company does not have these internal positions, 4WARN can assist in coordinating a response.

A Tech-Enabled Litigation Risk Score should not be static. The successful efforts of your team can favorably impact your Tech-Enabled Litigation Risk Score and lower it.

Risk Prioritization: The Search for the Greatest Vulnerability

All triage involves assessing and sorting so that the most urgent situations are addressed immediately. Developing a risk model to assess tech-enabled litigation requires an understanding of the unprecedented challenges developed to target insurers.

4WARN has prioritized a new model with three core principles in mind:

  1. To build a risk model that reflects the complexities inherent in different types of risk to the targets while ensuring a human element understands and verifies the calculated outcomes — before and after the application of remedies.
  2. To secure a deeper contextual understanding of the opportunists’ digital behavioral engagement tactics, including their continuous modifications and adjustments made in their effort to optimize and maximize their success.
  3. To ultimately develop a probabilistic risk model derived from pertinent risk factors, which enables organizations to develop an action plan to prioritize and address identified risks directly.

Calibration and Sensitivity Testing on Exploitability

4WARN’s primary focus is on analyzing and selecting each risk input for the model. This involved numerous experiments to validate the contribution of each risk and determine its relative predictive ability. 4WARN tested combinations of hypothesized risk factors to ascertain the measurability and contribution of their inclusion. However, it’s crucial to note that correlation doesn’t necessarily imply causation. Therefore, 4WARN utilized machine-learning models to identify which risk factors contributed to assessing each company’s tech- enabled litigation risk.

The approach was further refined by introducing additional variables, including company size, to assess relative risk. Intuitively, smaller, regional carriers targeted by large national law firms with substantial resources were likely to exhibit higher relative risk levels compared to larger national insurance companies, whose resources were more comparable to the opportunists targeting them.

4WARN also identified risk factors that yielded a statistically significant influence on the level of tech- enabled litigation risk, incorporating these findings into the metrics. The outputs of these models were then cross-referenced to predict risk levels with anonymized lawsuits filed by identified opportunists, validating the associated risk factors. This critical process allowed for a more comprehensive breakdown of influencing factors, facilitated calibration, and re-evaluation subsequent to response, while simultaneously ensuring alignment of the Tech-Enabled Litigation Risk Score with the real-world behaviors of the opportunists.

A Model for Response and Accountability

As a result of these efforts, 4WARN can provide organizations with a bespoke assessment of the tech- enabled litigation risk they face, across various markets. However, the reality is more nuanced. This proprietary research involves contextualizing each risk factor in terms of its potential exploitability under multiple scenarios. This necessitated incorporating numerous assumptions, such as “click conversion success” or “network maturity” (referring to the additional magnitude of targeting by an opportunist). Consequently, instead of making definitive assertions about the individual contributions of each component to risk outcomes, 4WARN opted to incorporate weighted probabilistic inputs.

An essential facet of each assumption was ensuring that a risk model’s value lies in rigorous testing coupled with prioritization of actions to effectively mitigate the greatest risks first. This also establishes accountability between 4WARN’s responses, client implementation, and the anticipated change in the tech-enabled litigation risk score.

Interested in how your organization's Tech-Enabled Risk Score™ stacks up?

Empower your strategy with 4WARN's expertise and steer clear of tech-enabled claim instigation risks.

Continuous Surveillance & Calibration

Constant calibration and testing of real-world litigation behaviors and claims instigation tactics are components of maintaining an effective and adaptive risk model. As the legal landscape evolves with the confluence of AI-driven litigation platforms, third-party litigation funding, and the motivation of higher settlements and awards, new tactics emerge, requiring continuous updating of the risk model to ensure its relevance. Likewise, developing a robust and dynamic response plan for organizations should lead to better decision-making, thereby instilling confidence rather than uncertainty in navigating the unknown digital multi-channel tactics by opportunists.

As Joe Petrelli noted in his testimony to the U.S. House Subcommittee on Housing and Insurance’s hearing into the availability and affordability of insurance, tech- enabled claim instigation adds another wave to this industry cycle. The increased level of litigation translates into higher insurance rates for policyholders as insurers adjust premiums; however, there is a significant delay between an accurate assessment of loss and loss adjustment expense levels and an adequate premium. By having an “early detection system” of impending tech-enabled claim instigation effort, aimed at them, organizations can respond to the emerging and omnipresent issue of tech-enabled claim instigation BEFORE it hits the claims department — before it’s too late.
This capability requires awareness of the degree of targeting that a company faces, which in turn requires new methods and processes for detecting and measuring tech-enabled litigation risk. The 4WARN Tech-enabled Litigation Risk Score offers companies a comprehensive, data-driven assessment of the claim instigation threats originating from the digital landscape. Companies will be empowered to make informed decisions and take proactive measures to mitigate risks and protect their interests.

The 4WARN Tech-Enabled Litigation Risk Score provides the first-ever comprehensive index of claims and technological litigation risk by leveraging dozens of digital behavior and search metrics across four dimensions of risk.

DemoTech Difference Publisher’s Note

Joseph Petrelli

Joseph Petrelli

In early 2022, Demotech Inc. performed a financial due diligence of six insurance carrier failures (each of which were Florida- focused property insurance writers). As of that date, none of the 2022 and 2023 legislative revisions had been enacted. Similarly, as of that date, National Association of Insurance Commissioners data and published reports authored by the Florida Office of Insurance Regulation, documented the disparate, disproportionate level of property insurance litigation in Florida versus countrywide. The review of multiple sources of litigated claim counts revealed a hockey stick growth rate in new litigated claims, year over year, at each failed insurance carrier. In the aggregate, the litigated claim count for the failed carriers had increased nearly 800 percent in five calendar years.

As this level of growth in litigated property insurance claims seemed well beyond the capability of efforts such as the door-knocking, TV and radio advertising being utilized by plaintiff firms and public adjusters, Demotech Inc., at my direction, retained Todd Kozikowski, a data technologist with expertise in artificial intelligence, machine learning and search engine optimization, to analyze and assess whether internet-based activity or other technological capacities had been leveraged to accelerate litigation levels.

Previous issues of the Demotech Difference have highlighted Kozikowski’s observations. Research pioneered by Demotech, undertaken by Kozikowski, unearthed tech-enabled claim instigation. Tech-enabled claim instigation is a business model implemented by opportunists to leverage litigation funding (financing), litigation platforms, litigation marketing, and search engine optimization for the purpose of securing contested claims as first notice of loss.

In an effort to create awareness and build a response mechanism to assist targeted entities within and outside the insurance industry, Kozikowski established 4WARN, Inc. Although I have shared, and will continue to share, the history of what led Demotech to undertake our unprecedented research of underlying causes of accerlerating increases in litigated claim frequency, neither Demotech, Inc. nor its owners have an interest in 4WARN, Inc.

Today, we continue to educate recipients of The Demotech Difference on the business model targeting the insurance industry and other sectors of the economy. Kozikowski and 4WARN have developed a procedure to identify, assess, and quantify how the business model of tech-enabled claim instigation impacts each company in any industry.

Since its inception, 4WARN has been communicating with regulators, trade associations, insurance companies, global reinsurers, and, through my testimony, the U.S. House of Representatives Subcommittee on Housing and Insurance, to create awareness of tech-enabled claim instigation. Once the substance of the business model is understood, the questions heard most often are, “What can we do to address this?” and “Am I being targeted?” Having developed responses to the varying degrees of targeting, 4WARN turned its attention to “Am I being targeted?” As the answer is that every carrier is being targeted, directly or indirectly, 4WARN also validated the impact on additional industries including transportation and hospitality — all in an effort to better understand and assess the growing and evolving risk of tech-enabled claim instigation at the individual company level.

From the DemoTech Difference - Spring 2024