Data Analytics in Finance Graduate Concentration

For the Data Analytics in Finance Concentration

chair of department: Louis Chan

director of graduate studies: Martin Widdicks (MSF); George Pennacchi (PhD)


department website:

overview of grad college admissions & requirements:

college website:

department office: 340 Wohlers Hall, 1206 S. Sixth Street, Champaign, IL 61820

phone: (217) 244-2239

The Data Analytics in Finance Concentration is open to students enrolled in:

Finance, MS

Financial Engineering, MS

The Data Analytics in Finance Concentration is designed to develop graduates who understand:

  • how to apply data analytics in a variety of financial contexts including investment and policy decisions;
  • critically solve business problems using data-intensive economic and financial information; and,
  • synthesize and effectively communicate data-intensive information, findings, and conclusions to others, including supervisors, peers, and clients. 

This concentration will not only provide a strong technical knowledge of data analytics topics, but also provide students multiple opportunities to apply this knowledge via experiential learning opportunities.

Graduate Degree Programs in Finance


Finance, MS

optional concentrations for the Finance, MS: Accountancy, Business & Public Policy, Corporate Governance & International Business, Data Analytics in Finance, Information Technology & Control

Financial Engineering, MS (administered by Finance and Industrial & Enterprise Systems Engineering)

optional concentration for the Financial Engineering, MS: Data Analytics in Finance

Finance, PhD




Data Analytics in Finance


Business & Public Policy

Real Estate


Candidates will apply to the Department of Finance for admission into the concentration. Students wishing to be admitted to the concentration should consult with their program advisor before applying.

For the Data Analytics in Finance Concentration

Completion of this concentration requires twelve hours of coursework, comprised of

  • FIN 510: Big Data Analytics in Finance (4 credit hours)

And any two of the following graduate courses:

  • FIN 552: Applied Financial Econometrics (4 credit hours)
  • FIN 553: Machine Learning in Finance (4 credit hours)
  • FIN 555: Financial Innovation (4 credit hours)
  • FIN 567: Financial Risk Management (4 credit hours)
  • FIN 580 DA: Data Analytics in Finance (4 credit hours)