Decision-makers at all levels increasingly must rely on verifiable data, presented in a clear, concise manner to the satisfaction of all stakeholders. In this burgeoning field, sophisticated data management and modeling techniques, in conjunction with strong industry knowledge, are the keys to providing meaningful analytics. The Quantitative Services practice provides thoughtful decision-making tools for management through complex data analysis, claim allocation modeling, and data-extraction services. Experienced staff members are dedicated to providing superior quantitative services with an emphasis on presenting results in a manner most useful to the clients’ needs. Allocation modeling services have been provided to insurers, reinsurers, claims counsel, and others for various types of claims, including asbestos, hazardous waste, lead, chemical, intellectual property, and professional liability.
Counsel for a joint defense group requested data analysis and an expert report that resulted in a favorable summary judgment in an asbestos case where plaintiffs were seeking in excess of $100,000,000. Alan Gray LLC analyzed underlying claimant data, performed an audit of the underlying claims and calculated product exposure points corresponding to the insured’s ownership of the asbestos product.
An account reconciliation on payments made in a chemical exposure case resulted in the collection of $4,000,000 in deductibles from the insured. Alan Gray LLC’s analysis determined that the insured’s data reporting techniques aggregated losses rather than applying per claim deductibles, resulting in a lower assessment of deductible dollars.
Contracted to provide quantitative services in a complex hazardous waste litigation, the staff worked with counsel to develop and employ a decision tree analysis in conjunction with a number of standard allocation modeling runs, to value their settlement options. After factoring in the appropriate coverage discounts, the client was supplied with a working model in which they were able to change the probabilities of success/failure at their discretion. The result was a favorable settlement where the insured paid approximately 10% of their exposed limits, 75% less than originally demanded.
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