Narrow Results

The main purpose of this paper is to model bank spread behavior under capital regulation and deposit insurance. Comparative static results show that an increase in the capital-to-deposits ratio or the deposit insurance decreases the bank's interest margin or spread. It is also shown that an increase in the equity that implies its opportunity cost of the coupon rate on the fixed leg decreases the margin. Previous research on market-based evaluations of bank equity has modeled the bank as a narrowing banking firm with risky assets and insured liabilities. The equity of the bank is viewed as a call option on its risky assets. No attempt was made to explicitly analyze a synergy between lending and deposit-taking, and, in our view, the equity of the bank is viewed as a swap option on coupon bonds. Synergy banking, particularly in the return to retail banking, is important in distinguishing banks from other lenders such as finance companies and mutual fund institutions. These other lenders call for the breaking up of banks into separate lending and deposit-taking operations, respectively. Our findings provide an insight for synergy banking operations concerning regulated bank spread behavior in the return to retail banking.

This chapter aims to investigate how banks build their dynamic capabilities and deal with corollary rigidities in the era of digital open innovation. Our analysis of two in-depth case studies stresses the challenges that banks face in the era of digitalization. It indicates that banks are transforming themselves deeply in terms of organizational structure, internal processes and interactions, and individual competences; human resistance to change and core rigidities being the most challenging issues to solve. Our results show that people-centered managerial practices — rather than purely technology-centered ones — seem to be highly promising to develop dynamic capabilities within banks. To succeed in developing their innovative capabilities banks have to find the right balance between the external constraints due to the specificity of their activities and the desire and need to innovate in order to satisfy their interconnected clients. To achieve this delicate equilibrium and proceed to the appropriate structural and organizational changes, awareness and collective mindset from banks’ executive management appear certainly as one if not the first determining factor to succeed.

This study examines the effectiveness of the Naïve Bayes Rule relative to that of five other popular algorithms in constructing scorecards that correctly discriminate between good-risk and bad-risk credit applicants. Scorecard performance is assessed on a real-world data sample by both the percentage of correctly classified cases and the more relevant criterion of bad rate among accepts. Naive Bayes is found to produce the worst-performing scorecard under both measures used.