Elder Research automated fraud detection for a national Workers’ Compensation Insurance Program to optimize investigations and forensic analysis

Elder Research built an end-to-end text mining and document classification solution in the client’s AWS cloud to extract CPA Findings from audit reports.

Elder Research built an automated fraud detection solution for NY DOL Unemployment Insurance Integrity Center of Excellence with annual savings of $1.4M

Department of Labor OIG wanted to detect fraud in Office of Workers’ Compensation Program data. The goals were to highlight abnormalities in the claims data that could be used for future audits and to create visualization tools to allow auditors to easily explore potentially fraudulent claims.

Elder Research developed an automated risk assessment framework to triage Worker’s Compensation claims, prioritizing high risk cases for manual review.

Elder Research developed an automated data pipeline and a data visualization tool used to explore document preparer network relationships. Forty percent of the cases being investigated were automated, reducing case investigation from 20 minutes per case to less than a minute per case.

Elder Research validated the methodologies used by RightShip to develop Qi, a new model to enhance maritime safety by predicting the ship casualty risk.

The goal for this project was to identify and quantify fraud, waste, and abuse indicators for a Medicare and Medicaid Dental Insurance client so that they could rank potentially fraudulent providers and target them for appropriate interventions.

Elder Research designed and deployed an automated fraud detection system credited with saving over $67 million in service provider and warranty fraud.

Elder Research developed and deployed a custom solution to identify and prioritize questionable contracts and healthcare claims for fraud investigation.

Elder Research developed a risk scoring model to optimize management of long-term care claims and identify those most likely to benefit from outreach.

Elder Research created a risk model to help the USPS-OIG prioritize facility lease review to focus on facilities with the highest risk or financial impact.

Elder Research developed a provider risk scoring model for a major dental insurance provider that enabled targeted intervention with low quality providers and reduced per patient cost by nearly 25 percent.

Elder Research was hired to improve the performance of the client’s world-class credit card default risk model using modern machine learning techniques.