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EFFICIENCY AND BENCHMARKING IN BANKING: REGULATORY & MANAGERIAL PERSPECTIVES

2018-2019

EnIESEG School of Management ( IÉSEG )

Class code :

1819-IÉSEG-M1S1-IBE-MA-EI36UE

INTERNATIONAL BUSINESS


Level Year Period Language of instruction 
Master1S1EnEnglish
Academic responsibilityK.KERSTENS
Lecturer(s)Kristiaan KERSTENS


Prerequisites

Micro-economics (mainly production theory).
A basic course in mathematical (e.g., linear) programming is a plus (but not needed).
Maximum 35 students allowed.

Learning outcomes

Efficiency assessment and benchmarking are crucial in management given the context of world-wide competition. OR and economic methods for evaluating efficiency are becoming basic tools for performance improvement. These methods have also been applied to banks and the results received a strong interest from bank managers.
This course serves 3 purposes:
(i) to develop an intuitive understanding of the concepts of production process and different notions of efficiency in production,
(ii) their meaning in the banking industry,
(iii) the application of the basic measurement tools and the managerial interpretation of its results within the same sector as well as in portfolio analysis.

At the end of the course, the student should be able to:
- understand production processes
- understand the various notions of static efficiency
- interpret efficiency measures
- understand the scope for applications in banking and other industries.

Course description

The topics treated in the course include the following:
- Service production and the need for performance criteria
- Efficiency in financial services (what do banks and bank branches "produce"?)
- Frontier technologies for benchmarking
- Sources of efficiency: A regulatory perspective (e.g., failure prediction, mergers)
- U.S. Case studies: Efficiency in commercial banks, credit unions, within a holding bank, among others
- European Case studies: Efficiency in a Greek, a Cypriote and some UK banks


Class type

Class structure

Type of courseNumbers of hoursComments
Independent work
Research8,00  
Independent study
Estimated personal workload8,00   Case studies reading & Report per student
Face to face
Interactive class16,00  
Total student workload32,00  

Teaching methods

  • E-learning
  • Research


Assessment

Lectures, case studies and student report.

Teaching is based on:
- lecture notes,
- articles with case studies and optional reading list, and
- class discussion.

Student presentations are based on an article (to be chosen among the references) describing a case study.

Each student must write a small report (2 to 4 pages at most) taking a personal position in favour or against the use of frontier benchmarking tools in either regulation or management. Students whose name starts with A-G (H-Z) must take a favourable (unfavourable) position. Whether or not the imposed position coincides with the personal conviction, what counts is the development of a series of coherent arguments legitimating why one stance could be defended above the other. Obviously, their arguments are conditional on the current understanding of these tools as developed in the course and the articles provided.

Participation in discussions, answer to case study questions and simple report: 40%
Final exam (open book): multiple choice and open-ended questions: 60%

Type of controlDurationNumberPercentage break-down
Continuous assessment
Participation0,00010,00
Oral presentation0,00015,00
Others
Written Report0,00115,00
Final Exam
Written exam2,00160,00
TOTAL     100,00

Recommended reading

  • * Articles to select a case: -

    Precise list varies from year to year

  • Athanassopoulos, A., D. Giokas (2000) The Use of Data Envelopment Analysis in Banking Institutions: Evidence from the Commercial Bank of Greece, Interfaces, 30(2), 81-95. -

  • Fried, H.O., C.A.K. Lovell, P. Vanden Eeckaut (1995) Service Productivity in U.S Credit Unions, in: Patrick T. Harker (ed) The Service Productivity and Quality Challenge, Boston, Kluwer, 365 390. -

  • Golany, B., J.E. Storbeck (1999) A Data Envelopment Analysis of the Operational Efficiency of Bank Branches, Interfaces, 29(3), 14-26. -

  • Hartman, T.E., J.E. Storbeck, P. Byrnes (2001) Allocative Efficiency in Branch Banking, European Journal of Operational Research, 134(2), 232-242. -

  • Kantor, J., S. Maital (1999) Measuring Efficiency by Product Group: Integrating DEA with Activity-Based Accounting in a Large Mideast Bank, Interfaces, 29(3), 27-36. -

  • Norman, M., B. Stoker (1991) Data Envelopment Analysis: The Assessment of Performance, New York, Wiley. Only sections 8.6 and 8.8. -

  • Sherman, D., G. Ladino (1995) Managing Bank Productivity Using Data Envelopment Analysis (DEA), Interfaces, 25(2), 60-73. -

  • Zenios, C.V., S.A. Zenios, K. Agathocleous, A.C. Soteriou (1999) Benchmarks of the Efficiency of Bank Branches, Interfaces, 29(3), 37-51. -

  • * Lidi, J. (1991) US Bankcorp seeks savings via branch-analysis system, American Banker, 156(195), 3. -

  • * Norton, R. (1994) Which Offices or Stores Really Perform Best? A New Tool Tells, Fortune, 136(9), 26. -


Internet resources



 
* This information is non-binding and can be subject to change
 
 
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