Big data, advanced analytics, and data-driven decision making have been both disrupting and enhancing the government’s ability to detect and mitigate fraud, waste, abuse, and risk. From developing data-driven enterprise risk and fraud frameworks to improving racking-and-stacking to enhancing big data pattern discovery to deploying predictive risk models, hear from key fraud and risk analytics champions across the government on how they’ve (A) designed and deployed innovative analytic solutions, (B) catalyzed change and adoption across their agencies, and (C) tackled common pain points and challenges.