Quaker Analytics Exposure Recognition System
CASE STUDY
One of our clients, a large self-insured trucking company, faced a familiar yet challenging scenario: a low-speed, low-impact collision, where soon after a spinal surgery was claimed, alleged to be necessary by the plaintiff, and eventually performed. While at first glance, this might appear as a minor accident, patterns of claim escalation - particularly spinal surgeries following minor incidents - continue to be common in areas like New York City. Often, these cases seem driven by legal strategies designed to amplify the value of a claim, burdening insurers with inflated settlement demands. For insurers and self-insureds, early detection of these patterns is essential to avoid unmanageable costs and prolonged litigation.
This is a Serious Injury Report prepared by one of our customers. The accident type will likely seem very familiar, as will the progression of the alleged injury severity. After reviewing this, we’ll discuss how Quaker tools can improve results on cases like this.
This case demanded the need for proactive identification and intervention, a capability Quaker Analytics addresses through our exposure recognition system. The models within this system are designed to recognize when a claimant has hired an attorney who has a track record of referring clients to doctors who perform seemingly unnecessary spinal surgeries. They can also detect an attorney’s frequency of cases that result in spinal surgeries. Essentially, these models empower claims managers to recognize early indicators of high-risk claims, equipping them with the tools needed to strategically settle and reserve with confidence.
Quaker Analytics Exposure Recognition System
Several years ago, when Quaker Analytics first introduced its exposure recognition system, the head of claims and risk management at a major trucking company asked a critical question: Could these models forecast a claimant’s likelihood of spinal surgery - particularly in regions notorious for high-value claims? Our models were designed for precisely this purpose. They bring visibility to potential escalation points, giving clients the upper hand by identifying patterns of high-risk claims early in the process.
Here’s how the system’s insight supports the claims process:
Early Detection of Claim Escalation: The models rapidly analyze data to identify the likelihood of high-cost medical interventions, such as surgery. In cases like this one, where a plaintiff’s attorney files a claim shortly after the incident, an alert is triggered. This alert enables a proactive approach, reducing the insurer’s financial and time burden associated with escalating injury severity allegations.
Guiding Strategic Reserves and Estimations: Early identification allows carriers to set accurate reserves from the start. For this client, Quaker Analytics provided an alert indicating potential escalation, ensuring that reserves aligned with the claim’s true risk level. Additionally, it prompted an evaluation of potential legal expenses if the case proceeded to litigation, including the necessity of medical and biomechanical experts.
Enhanced SIU Strategy: With suspicious claims, early intervention is essential. Quaker’s model doesn’t just predict high costs; it also supports Special Investigation Units (SIUs) by flagging cases for potential surveillance. This level of insight was invaluable to our client, who could validate suspicions of claim inflation and take steps to monitor the claimant’s condition and interactions.
Opportunity for Strategic Settlement Offers: Given the early alert of potential surgery, the carrier could make a substantial offer before the procedure took place. In cases where surgeries may be medically unnecessary but increase claim costs, this proactive settlement can discourage excessive medical interventions and bring quicker, and potentially more cost-effective resolutions.
How Quaker’s Models Made the Difference
In this case, the accident was reported by the plaintiff’s lawyer just five days after it occurred, eliminating the chance of a pro se settlement. However, with the Quaker Analytics exposure recognition models alerting the carrier to the potential for surgical escalation, the client was able to make swift and strategic decisions. They not only reserved the case appropriately but also initiated a rigorous SIU investigation plan to determine the claim’s legitimacy. Furthermore, they used this opportunity to educate policyholders and drivers on the importance of prompt reporting, reinforcing a crucial component of risk management.
By catching these red flags early, Quaker Analytics allowed the carrier to consider a settlement strategy that would deter unnecessary surgery, ultimately saving resources and improving the likelihood of a favorable outcome.
A Game-Changer for Commercial Auto Claims Management
Spinal surgery claims following minor incidents can be particularly costly and challenging to defend, and Quaker Analytics is helping to change that. In an industry where each misstep can cost millions, the insights delivered by Quaker’s exposure recognition models are transforming how claims managers approach volatile cases. Even with a highly skilled and experienced claims management team, things happen. Such as missed or incomplete claim file reviews, file reassignment delaying review, or a simple unintended missed indicator of potential high severity. Ultimately, the cost of just one missed exposure can be a significant financial hit to any company. Insurers and self-insured companies alike benefit from our data-driven insights, which replace guesswork with reliable indicators of potential claim costs and escalation.
Recent industry research supports the approach Quaker Analytics takes. A study published in the International Journal of Scientific Research and Management found that early recognition and intervention in claim escalation can significantly reduce litigation rates. Furthermore, predictive models like Quaker’s have demonstrated a significant impact on reserving accuracy, a crucial factor in underwriting and financial planning.
The Future of Data-Driven Claims Management
For insurers and self-insureds facing the challenges of managing commercial auto claims, Quaker Analytics’ exposure recognition system offers a considerable advantage. With tools that detect patterns and anticipate costly claim trajectories, insurers can act decisively to manage costs, reduce litigation, and improve outcomes. This case highlights not only the power of predictive insights, but also how early strategic intervention transforms high-risk claims into manageable cases.
As we continue to refine and expand these capabilities, our focus remains on empowering our clients to respond to claims that could otherwise spiral into costly, prolonged battles. In cases like these, Quaker Analytics isn’t just a technology - it’s a strategy for sustainable claims management that keeps our clients steps ahead.