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This paper investigates Small-Medium Banks’ (SMBs) business plans in accordance with the structure of Additional Funds Needed (AFN) model. The Key Profitability Variables (KPVs) are the size and structure of deposits, loans, and their interest rates. This study employs a Genetic Algorithm (GA) problem with hard constraints, to point out the limits to changes in the structure of deposits and loans and the effects of those changes on the P&L of a banking institution. After examining 10,000 iterations with Evolver, an innovative optimization software that uses GA, OptQuest, and linear programming, the alternations, have been narrowed down to 3700 which satisfy both, a) constraints and b) maximization of profits. Having also the distributions, this paper concludes that it is a useful methodology that must be further exploited by applying risk weights, mainly for credit risk, to the structural components of the Balance Sheet, and to other competitive institutions. Keywords: banking institutions, genetic algorithms, additional funds needed, operational research

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