Mathematical Programming Approaches to Net Interest Income Optimization in Bank Balance Sheets

This thesis proposes the construction of an optimization model in the field of Asset & Liability Management (ALM), developed following an internship at company 'Prometeia', with the aim of integrating profitability and regulatory constraints in bank balance sheets. Within a context defined by Basel III standards, the work constructs a mathematical optimization framework capable of describing the interactions between asset and liability exposures, capital requirements, liquidity indicators, and operating limits. The resulting model is formulated as a nonlinear programming problem, with the possibility of reducing specific configurations to a linear program solvable with classical methods. The numerical implementation, developed in Python, allows the problem to be simulated with different, more or less restrictive, constraints and the impact of each constraint on the solution space and financial planning decisions to be assessed. The results show how integrating capital, liquidity, and balance sheet structure constraints produces significant trade-offs in determining the optimal allocation. The thesis's contribution therefore consists in defining an operational model that, in addition to its theoretical value, can concretely support strategic decisions regarding bank balance sheet management.