Program Overview

Financial Services Analytics (FSAN) Ph.D. Program

The Financial Services Analytics (FSAN) doctoral program at the University of Delaware is a unique, interdisciplinary STEM-designated program that combines fundamental data science theories and models with data-driven decision-making tools applicable to the financial services industry and other technology industries. This joint effort between the Alfred Lerner College of Business and Economics and the College of Engineering develops students into leaders in research and practice in the area of financial services analytics.

Program Highlights

• Facilities: State-of-the-art facilities, including the JPMorganChase Innovation Center, the Geltzeiler Trading Center, and the Harker Interdisciplinary Science and Engineering Laboratory, are designed to foster collaboration among students, faculty, and industry.
• Financial Support: Top candidates are provided with financial support, including tuition and a competitive stipend, through a significant grant from JPMorganChase.
• Student Experience: The small student cohort offers ample opportunities for close interaction with thought-leading faculty from multiple disciplines, including business, engineering, and computer science.

Program Requirements

To be granted a doctorate in FSAN, students must successfully complete all FSAN coursework with a 3.0 cumulative GPA. Most students complete all degree requirements within 4 to 6 years.

Courses

Courses include:

• **FSAN 815/ELEG 815 Analytics I: Statistical Learning***
• FSAN 820 Foundation of Optimization
• FSAN 830 Business Process Management Innovation
• CISC 683 Introduction to Data Mining
• FINC 841/FSAN 841 Financial Services Markets*
• FINC 842/FSAN 842 Financial Services Risk Analytics**
• FSAN 850 Financial Services Analytics Seminar (6 credits)
• FSAN 860 Current Research Topics (0-9 credits)
• FSAN 969 Doctoral Dissertation (9 credits)

Examinations and Dissertation

A qualifying exam and research paper are required at the end of the first year. A dissertation proposal and oral defense must be completed by the start of the third year. The dissertation requirement includes the approval of both the written dissertation and oral defense.

A Look Into the Program

FSAN students work closely with their supervisors to identify cutting-edge research topics related to modern data science theory, algorithms, and applications in banking and the financial and tech industries. Sample dissertation topics include:

• Bayesian causal inference
• Predictive analytics
• Bank systemic risk
• Malware detection and classification
• Credit card fraud detection
• NLP & chat-bots
• Link recommendation
• Text-based industry classification
• Loan process optimization
• Customer targeting
• Active learning on graphs

Career Opportunities

The program generates excellent internship opportunities and industry and academic job prospects. Corporate-sponsored internships offer students the opportunity to apply analytics tools to real-world challenges. FSAN graduates are employed as data scientists in major banks, fintech companies, and technology companies.

Where Our Students Intern

• JPMorganChase
• Barclays
• Sallie Mae
• Amazon
• LinkedIn
• HP

Where Our Graduates Work

• Academic Institutions:
  • Chinese University of Hong Kong (Shenzhen)
  • Shanghai University of Finance & Economics
  • University of Delaware
  • Virginia Tech
• Banking and Financial Services:
  • JPMorganChase
  • Bank of America
  • Barclays
  • Sallie Mae
  • USAA
• Industry:
  • Amazon
  • LinkedIn
  • McKesson
  • Meta
  • Microsoft

Admissions Information

The program accepts students every other year, in even-numbered years. The application deadline for the next cohort is May 15, 2026. Students seeking financial aid should submit their applications by January 15, 2026. Highly-qualified students may receive research scholarships as well as a generous stipend to cover all educational expenses.