In anticipation of his upcoming conference co-presentation, Words that Matter: Application of Text Analytics at the U.S. Commodity Futures Trading Commission, at Predictive Analytics World for Government, October 17-20, 2016, we asked Miguel Castillo, Assistant Inspector General for Audit at U.S. Commodity Futures Trading Commission, a few questions about his work in predictive analytics.
Q: How would you characterize your agency’s current and/or planned use of predictive analytics? What is one specific way in which predictive analytics actively drives decisions in your agency?
A: The agency recognizes that data and technology is critical to transform the CFTC into a 21st century regulator that can efficiently and cost-effectively surveil the derivatives markets. In its Strategic Plan, Goal 1 for IT is to deliver services aligned with core mission functions of the CFTC. Its priority is to meet business needs first by empowering users with self-service technology platforms for data analysis, then by enterprise-focused automation services.
The extensive research and analytical backgrounds of its senior economists also ensures that analyses reflect the forefront of economic knowledge and econometric techniques. Staff expertise is grounded in a solid knowledge of market institutions and practices and experience communicating the results of quantitative analysis.
So while the agency is building its infrastructure, collecting market data, and hiring competent economists, there is an opportunity to introduce predictive sciences into the mix.
Q: Can you describe the challenges you face or have already overcome in establishing a data-driven environment in your agency?
A: One challenge is changing the business culture to balance data access with information security. We are testing an MOU to meet this challenge.
Q: Can you discuss any near term goals you have for improving your agency’s use of predictive analytics?
A: Collaborate, collaborate, and collaborate on projects that use analytics to determine use cases for “predictive analytics.” I think it’s a matter of time before the agency fully learns from the experience of using data to its advantage.
Q: Can you describe a successful result from the employment of predictive analytics in your agency, i.e., cost avoidance, funds recovered, improved efficiency, etc.
A: Our audit text mining experiment used a simple mathematical approach using historical reports to understand how to better plan audits.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World for Government.
A: Not only will we discuss our audit planning text mining experiment but also another effort related the agency’s rule-making.
Don’t miss Miguel’s conference co-presentation, Words that Matter: Application of Text Analytics at the U.S. Commodity Futures Trading Commission, on Tuesday, October 18, 2016, from 10:30 to 11:20 am at Predictive Analytics World for Government. Click here to register to attend. USE CODE PATIMES16 for 10% off current prices (excludes workshops).
By: Sean Robinson, Program Chair, Predictive Analytics World for Government