How RiskMap® Analyses of Driver Training Drove Operational Changes

Author: Alan B. Cantor
Founder & Chief Analytics Officer, Risk Analysis Services LLC

Clarity Where There Once Was Confusion

When Laidlaw’s Vice President of Corporate Risk Management, Jeff Cassell, prepared for quarterly discussions with actuaries, he faced a familiar challenge: there was no shortage of data, but there was limited insight.

Laidlaw operated more than 50,000 school buses. Incident reports, claims histories, and driver training records were meticulously maintained. Yet despite the volume of information available, it remained difficult to clearly explain why loss costs were changing — or how specific driver training initiatives were influencing those outcomes.

Each actuarial review carried the potential for significant reserve increases, directly affecting earnings. What the risk team needed was not more data, but a clearer understanding of the dynamics driving loss behavior.

A Different Kind of Insight: Quantitative Risk Analysis

At a national RIMS Conference, Mr. Cassell attended a presentation I delivered on quantitative risk analysis and its application to operational risk. The discussion focused on moving beyond descriptive reporting to understanding how operational decisions influence loss outcomes over time.

Risk professionals excel at collecting data. Far fewer have the tools needed to quantitatively evaluate how operational changes affect loss costs. That gap is precisely one of the things that RiskMap® analyses were designed to address.
(Note: This is one of the things that RiskMap® can deliver.)

RiskMap® is not a reporting system or dashboard. It is a proprietary analytical framework used to perform deep, auditable analysis of large and complex data sets — enabling risk behaviors to be measured, tested, and explained with statistical rigor.

Video Discussion: Independent Perspective on the Laidlaw Analyses

In the video below, Neil Gordon interviews insurance advisor Lou Polur, who discusses how analyses performed with the help of RiskMap® provided deeper insight into Laidlaw’s driver training initiatives and their impact on loss behavior and loss costs.

The discussion offers an independent, practitioner-level perspective on how quantitative risk analysis supported clearer understanding, improved communication with actuaries, and more confident risk retention decisions.

What We Did — The Analytical Process

When Laidlaw engaged Risk Analysis Services, the objective was straightforward in concept and demanding in execution:

Quantify how driver safety training initiatives influenced loss behavior and loss costs.

To achieve this, we:

• Established objective baseline metrics using historical loss and driver training data
• Performed systematic, recurring analyses to evaluate how changes in training protocols affected loss outcomes
• Applied RiskMap®’s audit-ready analytical methods so that all conclusions could be traced, reviewed, and defended

This approach relied on statistical evidence rather than assumptions or anecdotal observations. Impacts were measured in real dollars, allowing management to clearly distinguish which operational changes were producing measurable results.

Outcome: From Reactive to Proactive Risk Management

Once RiskMap® analyses were applied to Laidlaw’s data:

• The risk team could explain and demonstrate the causes of loss trends rather than speculate about them
• Training-related best practices were identified and communicated with far greater confidence
• Discussions with actuaries and underwriters shifted from debate to collaboration, supported by defensible data

As Mr. Cassell later noted, Laidlaw gained a much clearer understanding of the dynamics driving its loss costs.

Senior management recognized the value of this improved insight and approved a five-fold increase in the company’s Self-Insured Retention (SIR) — representing millions of dollars in retained risk supported by analysis rather than uncertainty.

Organizational Impact Beyond the Numbers

The impact extended well beyond a single engagement:

• Existing data systems were evaluated and strengthened
• New methodologies for ongoing risk evaluation were introduced
• Data flows were refined to support continuous, repeatable analysis

Risk management evolved from a reactive function to a strategic contributor — one capable of influencing operational decisions and financial outcomes with confidence.

A Quick Word on Data

If data were a school bus, RiskMap® analysis would be the route map that identifies operational risks and blind spots in advance.

In risk management, insight outperforms instinct — especially when conclusions are supported by defensible data.

Related Case Studies by Alan Cantor

• Successful Risk Modelling Protected the Nuclear Power Industry Against a Financial Meltdown
• Medical Association With 25,000 Members Secured Malpractice Coverage Through Advanced Risk Analysis