Application of Data Envelopment Analysis on Bank Asset and Liability Management

Jacob Muvingi ()
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Jacob Muvingi: University of Kurdistan Hewler

A chapter in Advances in the Theory and Practice of Data Envelopment Analysis, 2025, pp 267-279 from Springer

Abstract: Abstract Data envelopment analysis (DEA) is a method for identifying the best practices among peer decision-making units (DMUs). Bank profitability is a function of a bank’s asset and liability management. The sensitivity of a bank’s assets and liabilities to the movement of interest rates is a key aspect of a bank asset and liability management. The difference between rate-sensitive assets (RSA) and liabilities (RSL) represents a bank’s income gap (IG). The nature of a bank’s IG affects the bank’s interest-bearing income. Banks generally face a decision-making challenge associated with choosing the optimum RSL, RSA, and IG structure. The current study proposed a IG efficiency analysis for a hypothetical banking sector based on three scenarios of a bank’s IG; negative IG, positive IG, and a mixture of positive and negative IG. The semi-oriented radial measure model was used in the study to handle negative IG values. Targets for the outputs in each scenario were provided. Overally it was discovered that of the three scenarios, the negative IG scenario yield a higher number of efficient banks.

Keywords: Data envelopment analysis; Bank asset and liability management; Gap; Semi-oriented radial measure (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-98177-7_18

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DOI: 10.1007/978-3-031-98177-7_18

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