A Lexicographic Bi-Objective Chance-Constrained Model for Asset-Liability Management with Endogenous Reliability: Theory and Application to Banque Misr (Statistics, Optimization & Information Computing, 2026)
Banks in emerging markets face persistent commercial and regulatory challenges. Profits must be maximized while ensuring solvency against economic volatility. Traditional Asset-Liability Management (ALM) models typically address this problem by treating reliability targets as constant, static parameters. A generalized Lexicographic Bi-Objective Chance-Constrained Programming model is introduced to endogenize these regulatory reliability levels as decision variables. The framework uses a hierarchical optimization system that prioritizes Capital Adequacy Surplus over Loan Returns. Historical financial data from Banque Misr (2011–2021) supplied the empirical baseline. Dynamic calibration demonstrated superior performance compared to standard static compliance. Setting the strategic floor to 80% yields a maximized Capital Surplus of EGP 247.3 million and drives Loan Returns to a peak of EGP 28.1 million. Because the solver strictly anchors both reliability objectives at this exact boundary, the maximum possible Capital Surplus is secured alongside peak Loan Returns. The practical value of this endogenous framework becomes evident when measured against a rigid 90% static benchmark. Escaping that static rule releases EGP 2.43 million in Capital Surplus and generates an additional EGP 6.44 million in yield, preventing a 22.96% contraction in Loan Returns.