Ph.D. in Financial Services Analytics (FSAN)
Big data is reshaping the way we live and the way businesses operate. Its impact is especially profound in the financial services industry, where abundant data comes from many sources. Financial services analytics is the science of quantitative models and technologies designed for the financial services industry. It offers improvements in risk management, customer service, customized product offerings and business operation efficiency.
The financial services analytics (FSAN) program at the University of Delaware is the first of its kind, developing fundamental FSAN theories, creating new data-driven decision-making tools and training researchers and professionals. The interdisciplinary program brings data analytics methods and non-traditional data sources to bear on issues important to the financial services industry, which differentiates it from programs in finance or financial engineering.
As a Lerner FSAN student, you’ll:
- Collaborate with thought-leading faculty from multiple disciplines including business, engineering and computer science.
- Work with your advisor to choose your research and dissertation topics.
- Attend conferences and research seminars that provide access to provocative thinkers from industry and academia.
Corporate-sponsored internships offer you the opportunity to apply analytics tools to real-world challenges on teams in wealth management, machine learning, data architecture, investment banking, global finance and business management.
Our state-of-the-art facilities are designed to foster collaboration among students, faculty and industry; these include the JPMorgan Chase Innovation Center, the Geltzeiler Trading Center and the Harker Interdisciplinary Science and Engineering Laboratory.
To be granted a doctorate in FSAN, you must successfully complete all FSAN coursework with a 3.0 cumulative GPA. You have up to five years (if you have a previous master’s degree) or seven years (if you have a bachelor’s degree) to complete all degree requirements.
BUAD 840 – Ethical Issues in Domestic and Global Business Environments
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 Firms and 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)
Electives: Choose 3 courses from:
FSAN 817/ELEG 817 – Large Scale Machine Learning*
MISY 831/FSAN 831 – Enterprise Information Systems
FINC 843/FSAN 843 – Financial Services Regulation*
ACCT 804 – Database Design, Networks and Implementation
ACCT 806 – Systems Analysis, Design and Implementation
ACCT 817 – Information Technologies Audit
ACCT 820 – Financial Statement Analysis
CISC 681 – Artificial Intelligence
CISC 684 – Introduction to Machine Learning
CISC 886 – Multi Agent Systems
ELEG 630 – Information Theory
ELEG 636 – Statistical Signal Processing
ELEG 657 – Search and Data Mining
ELEG 655 – High-Performance Computing with Commodity Hardware
ECON 801 – Microeconomics
ECON 803 – Applied Econometrics I
ECON 810 – Mathematics for Economists
ECON 861 – Industrial Organization and Regulation
FINC 855 – Financial Institutions and Markets
FINC 856 – Financial Engineering and Risk Management
FINC 870 – Theory of Financial Decision Making
FINC 871 – Workshop in Finance: Seminar
MATH 612 – Computational Methods for Equation Solving and Function Minimization
MATH 630 – Probability Theory and Applications
MATH 631 – Introduction to Stochastic Processes
MATH 672 – Vector Spaces
MATH 829 – Topics in Mathematics
APEC 802 – Operations Research Applications
APEC 807 – Math Programming with Economic Applications
STAT 601 – Probability Theory for Operations Research and Statistics
STAT 602 – Mathematical Statistics
STAT 611 – Regression Analysis
STAT 615 – Design and Analysis of Experiments
STAT 617 – Multivariate Methods
STAT 620 – Nonparametric Statistics
STAT 674 – Applied Database Management
STAT 675 – Logistic Regression
Examinations and Dissertation
A qualifying exam and research paper are required at the end of the first year. The candidacy exam must be completed by the end of the third year, upon successful completion of which and at the recommendation of the dissertation committee, you may be admitted to Ph.D. candidacy. The dissertation exam includes the approval of your written dissertation and an oral defense. Full exam and dissertation details can be found on myLerner.
A Look Into the Program
FSAN graduates are researchers and professionals who play key roles in teams that bridge the financial services industry and data and operational sciences. FSAN graduates find employment in positions such as data analyst, data scientist and financial analyst.
– FSAN student Leonardo De La Rosa Angarita
Contact Dr. Bintong Chen
The application deadline for the next cohort (beginning fall semester 2018) is February 1, 2018. We accept students every other year. Highly-qualified students may receive research scholarships to cover all educational expenses.
Learn more about financial services analytics Ph.D. admissions requirements, deadlines, tuition and financial aid available to you.