The Use of Nonlinear Programming in Banking Risk Management: A Statistical Study

Abstract

This research aims to identify the most important non-linear models (quadratic programming) that can be used in standard modelling, which can be applied to a selected case study (in banking risk management). This is achieved by integrating regional planning with banking risk management to form a future development relationship. Through integration, Banks can play this role by using information about regional development to assess risks better. For example, good infrastructure planning can positively impact the reduction of credit risks in a certain area, thus financing regional projects. Banks can play a role in funding regional development projects, thereby achieving economic returns, improving the financial situation, and subsequently, sustainable development. Banks can support projects that promote development, such as environmental projects that reduce environmental and financial risks, etc. Overall, the relationship between regional planning and banking risk management lies in balancing sustainable regional development and effectively managing financial risks to achieve economic and social stability, taking into account cyclical, incidental, and sudden changes affecting the working system and the objectives set for it. The linkage between regional planning and banking risk management is significant as they intersect in several aspects, such as resource distribution and infrastructure at the regional level, to achieve balanced and sustainable development across all facets and approaches of regional planning. Regional planning cannot be complete and achieve its objectives and investments in all fields without a stable banking and financial system free from risks, which is used in developing analytical models capable of dealing with banking risk management using ready-made statistical programs such as SPSS, Solver, Eviews, etc.