This session focuses on how an AWS customer created a data lake and used machine learning services to analyze and search massive amounts of historical unstructured data. The Municipal Securities Rulemaking Board modernized their analytics platform by using a combination of machine learning natural language services, free-text search capabilities, and optimized storage services to extract information from stores of data without labor-, cost-, and time-intensive processes. The result astonished Board of Directors, who saw the potential of leveraging the cloud to generate tremendous and transformative value for the municipal securities market.

The Department of Veterans Affairs (VA) Office of Inspector General (OIG) conducts oversight of VA programs and services, which is a monumental undertaking in the context of VA’s 2019 budget of $201.1 billion; VA’s status as the second-largest federal employer, with more than 380,000 employees serving an estimated 19.6 million veterans; and the complexity of VA programs and services, which includes operating the country’s largest integrated healthcare system. Since 2018, the VA OIG has partnered with Booz Allen Hamilton to establish and sustain a Predictive Data Analytics and Modeling Program to more proactively detect and mitigate the risk of fraud, waste, and abuse across VA programs and services. This presentation will draw on a case study involving VA’s $12.4 billion educational benefits programs for veterans to showcase the OIG’s successes and lessons learned for leveraging subject matter expertise and data-derived insights to generate leads and self-service tools that meaningfully enhance oversight activities. To that end, we will share VA OIG’s insights regarding how to: (a) stand-up productive, cross-discipline teams; (b) select the most effective analytic methods and techniques for common use cases; and (c) drive adoption from leadership to the front line.

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