What can the Chief Data Officers do to accelerate AI adoption in Government? | Pioneers of a More Data Driven Union

How is AI being applied to maximize the Oversight community’s impact with limited resources? | Pioneers of a More Data Driven Union

How is AI being applied to improve $700B worth of grantmaking? | Pioneers of a More Data Driven Union

What is AI and how is it used in industry and government? | Pioneers of a More Data Driven Union

Assessing Second Opinion Effects on Return to Work

Elder Research was tasked to evaluate the effectiveness of second opinions to encourage federal employees on long term disability to go back to work. 

Regulatory Analytics and the Regulatory Information Value Chain

How the OPEN Government Data Act Empowers Data-Driven Government

Improving Unemployment Insurance Claim Fraud Detection

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

Optimizing Federal Workers Compensation Claims Approval

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

Interview with Data Scientist Dave Saranchak About Statistical Data Modeling Techniques for National Security Clients

Join IBM data science evangelist James Kobielus and Dave Saranchak, a data scientist with Elder Research, to discover how Dave develops and applies statistical data modeling techniques for national security clients.

Reducing Contract and Claims Fraud, Waste, and Abuse

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

Prioritizing Building Lease Renewal Risk

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.

Improving Claims Approval Speed and Accuracy

Elder Research combined state-of-the-art text analytics with traditional statistical techniques to create a solution for ranking disability claims for approval. The results were more accurate and consistent than any single doctor’s decision and allowed 20% of the claims to be approved immediately.