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White Paper #2: Project for American Nuclear Power Helped Prevent Meltdown
White Paper #3: Risk Costs Analysis for Florida Association of Self Insureds (FASI)
White Paper #4: Medical Association White Paper
WHITE PAPER #1: Laidlaw Reduced Reserves by Millions
By Alan B. Cantor
How RiskMap® Analyses of Driver Training Drove Operational Changes
VP Corporate Risk Manager for Laidlaw Jeff Cassell was preparing to call his actuary for their quarterly appointment. Mr. Cassell was ready to report that he now had some new insights about operational losses. And he was preparing to discuss these projected losses in a new and more informed manner with his actuary.
BACKGROUND: Laidlaw operated over 50,000 school buses for districts in the US and Canada. As Mr. Cassell surveyed his domain, gaining control of risk meant safely picking up and delivering students to school and then returning them home again safely. It also meant that sporting events, field trips and other extra-curricular program participants were transported successfully as planned, without schedule glitches or unfortunate occurrences.
Laidlaw’s risk management department did a very good and efficient job compiling incident reports, processing claims and creating policies and procedures to support driver safety training; nevertheless, Mr. Cassell felt he had no control over, or understanding of, the loss costs. The risk management group generated data for their actuaries’ loss projections, but had no basis to provide either meaningful insight nor display any convincing control over operational behavior. He had huge concerns every time the actuary was due to re-calculate the loss forecasts, knowing that increases in the loss cost directly reduced the company’s earnings. Millions of dollars of reserves could be added to Laidlaw’s balance sheet when the actuaries’ trend and loss projections were delivered.
All of this changed after Mr. Cassell participated in a National RIMS Conference, where he attended one of Alan Cantor’s presentations on Quantitative Analysis of Risk. Mr. Cantor, a Wharton operations research and finance MBA, presented to the risk professionals several case study examples, which reflected methodologies on how they could gain much better control over their cost of risk. He portrayed how, if they were to continuously evaluate their risks in a more systematic and intensive manner utilizing advanced quantitative analytical tools, they could achieve superior results. When applied properly with the appropriate expertise, the resulting analyses offered insights to better understand the true cost of their organization’s operational risks.
Cantor’s analysis provided the risk managers with the knowledge and data to better work with their actuaries and underwriters, to achieve dramatically improved results. They were now able to better understand the key risk drivers in their operational behavior.
THE PROCESS: Mr. Cassell was intrigued. He began envisioning ways to implement changes at Laidlaw that would drive down their enterprise risk cost with Cantor’s processes and guidance.
Mr. Cantor was initially engaged to help systematically assess, quantify and gauge training effectiveness for the driver safety courses that were prepared for various school districts. Cantor’s proprietary analytical tool for auditable deep dives for actionable insights into masses of data (“RiskMap®”), established baseline metrics. Through successive monthly analyses, the risk management professionals were able to document the impact of new training methods and protocols in dollars. This significantly facilitated and expedited the flow of Best Practices throughout the organization. Cassell said, “Laidlaw now understood the dynamics that affected the loss costs.” He then convinced the actuaries that the reduced loss costs resulted from their carefully crafted and continuously refined driver-safety intervention programs. The changes were systemic, ongoing and statistically verifiable through RiskMap® built-in audit trails. With Cantor’s help, Laidlaw’s risk management department was able to document the cause-and-effect relationship between driver-safety programs and the dual objectives of greater control over risk and reduced loss cost.
Over time, the benefits were manifold. Data systems were reviewed. New methodologies were introduced. Optimal data flows were mapped. New protocols to continuously validate the data were implemented. These new analytical processes facilitated Cassell’s ability to better understand, document and demonstrate the cost effectiveness of his department’s initiatives.
Top management and the Board recognized the improvements and approved an increase of 5-fold to Laidlaw’s SIR, by millions! Insurance underwriters, who experienced the positive changes in enterprise risk culture, acknowledged this new paradigm, and changed how they competed for Laidlaw’s business. Because of the new form of continuous risk analysis introduced by Cantor, Mr. Cassell was able to successfully negotiate a controlled multi-year release of millions of dollars in reserves.
Moreover, because of the empowerment of the risk management department that followed these successes, according to Mr. Cassell, “We were no longer at the mercy of the actuary.” The relationship transformed into a partnership that validated the changes that flowed from the RiskMap® analyses.
WHITE PAPER #2: Successful Risk Modeling Protected the
Nuclear Power Industry Against A Financial Meltdown
In March, 1979 an accident occurred in Middletown, Pennsylvania, at the Three Mile Island nuclear power complex.
The crisis and its clean up lasted fourteen years. As an analyst, Alan Cantor modelled the risk for the American Electric Power Institute and Nuclear Mutual Ltd, an association-owned captive insurance company that covered the Three Mile Island facilities. It was his financial statistical modelling that facilitated the successful placement of the risk at Lloyds. Little did he realize how soon after the reinsurance was arranged that the catastrophic loss was resolved without resulting in a financial meltdown for the electric utility industry.
The $71 million Three Mile Island loss was fully comprehended by the model and managed effectively by the insurance placement. Over time the underwriters were profitable. And the complex placement was spread across multiple names and entities – the average exposure was manageable without threatening their financial health. The acceptance and viability of the risk transfer/risk financing system was assured by model. The syndicates were confident because the risk modeler had captured every conceivable aspect of the risk.
With full authority from the CEOs of General Electric and Westinghouse, Cantor, a newly minted Wharton MBA, had carte blanche access to deconstruct the architectural and engineering drawings of the nuclear power plants. Cantor developed four decision trees based on the reactor designs and input from interviews with the plants’ Chief Engineers. For each component and system in their plants, Cantor factored the probabilities of failure and the potential severities. Next, he utilized historical incident data provided by the Nuclear Regulatory Authority, which data he was told had never before been requested or analyzed. Finally he programmed a Monte Carlo-based simulation model to reflect the data from the Nuclear Regulatory Authority and the probabilistic decision-tree analyses. The simulation model projected cost and geographic potentialities.
Once Cantor’s model was completed, multiple scenarios were run for the London managing agent as he pursued negotiations with Lloyds to fill the slips for fully funding the risk. The unique mathematical model was so robust it was utilized unchanged through successive renewals over many years.
WHITE PAPER #3: Accelerate Control of Risk Management Costs (FASI Analysis)
By Alan B. Cantor
Risk Analysis Services LLC (RAS) has performed a unique analysis on Florida’s workers’ compensation system, including separately reviewing self-insured entities. Using proven methodologies and data-sets not previously analyzed, we conclude that the 2015 NCCI rate reduction for workers’ compensation rates in Florida has created an ideally timed opportunity to exert greater control of the costs of a self-insurance fund.
We obtained data from the US Bureau of Labor Statistics, the Florida Division of Workers Compensation, and Florida Self-Insurers Guaranty Association. First, we extracted total workers compensation claims data for 2005 – 2012, including total annual paid costs and total annual numbers of claims. Second, we received FL WC data for the 398 FL employers who are self-insured for WC. Third, we performed parallel analyses for each population of self-insured, commercially insured and all employers, respectively. We then compared the results.
Trends for self-insureds and all paid WC benefits/costs were significantly divergent. For the period 2008-2012, Total Average Costs for commercially insured was five times higher than the workers’ comp average cost per claim for self-insureds. The Average Cost per Claim for Self-Insureds is 20% of the cost for commercially insureds. In addition, while the total number of claims for the self-insured employers averaged 28% of the total frequency, self-insured employers accounted for only 8% of the Total Paid Cost of all Florida workers’ compensation.
This analysis of the Workers’s Compensation experience for a leading state shows that there is a dramatic impact in the management and cost of Worker’s Comp depending upon whether the risk is Self-Insured, or handled in the commercial insurance market-place. This strongly suggests that there is a demonstrable inefficiency and negative cost impact when Workers’ Compensation is managed in the commercial insurance marketplace vs. Self-Insurance (whether it is direct Self-Insurance or possibly through some individual or group Captive). There is sufficient logic to suggest that associations, if properly managed, can achieve comparably favorable results.
Rigorous, objective and systematic risk data analysis has been shown to yield actionable intelligence which can inform enhanced decision-making: improving management, reducing costs and increasing profits.
The analysis above was prepared for the Florida Association of Self-Insurance (FASI) whose members are statutory participants in the Florida Insurance Guaranty Association (FIGA) for their Winter Conference held January 29, 2015. Responses to this research and analysis included requests for comparable studies for their commercial auto liability. This evidences the fact that this type of analysis had broad application.
In spite of the currently softening workers’ compensation commercial insurance market, companies will benefit from undertaking a study of becoming self-insured in workers’ compensation.
WHITE PAPER #4: Medical Association with 25,000 Members’ Malpractice Coverage
By Alan B. Cantor
When market conditions and participants change are you prepared and nimble enough to improve your position?
Imagine a state medical association with 25 years and tens of thousands of physicians’ medical malpractice claims experience. Instead of a slow Thanksgiving week with a list of renewal notices, the association risk manager received a notice of cancellation. Their malpractice carrier was terminating the association’s account. Twenty-five thousand physicians in the State of New York needed a new malpractice carrier urgently.
As December 31 coverage termination date approached, Alan Cantor, the analyst for the Medical Association’s broker, poured over reams of data. He researched and validated the quality of the data to assure its integrity prior to analysis, including consulting with defense attorneys for selected cases. He performed loss development analyses, based on multiple subsets of the data and for the overall aggregate data: numbers of procedures by type, cases by specialty and subspecialties, comorbidities and combination-claims with multiple surgeons and anesthesiologist.
Cantor’s work was so scrupulously organized that a reader of the final report could trace each thread of the analyses from Validated Source Data (Loss and Exposure) to Loss Development, to Loss Forecasting (Regression-Trend Analysis) to projected losses and cost, including projected cash flows and discounted future cash flows.
The selected projected results were based on those component analyses with the highest correlations and lowest volatilities. Future losses were projected ahead five years. When the projections results were compared to the actual results 6, 7 and 8 years later, Cantor’s projections were ½ of 1 percent off the actuals.
The systematic analysis offered by Risk Analysis Services LLC features the same level of modeling that can be applied to improve your cost of risk, risk transfer and management today.
Author’s Note: The author wishes to express his appreciation to fellow Wharton Alum Lou Polur, Sihle Insurance Group, Clearwater Florida, for his collaborative assistance with these article.
