OPTIMAL CONTROL IN BANKING MATHEMATICAL MODELS TO MAXIMIZE PROFIT.
In the banking sector, fund management and lending are two primary activities that significantly impact profitability. Banks must balance risk and profitability, often involving strategic decisions in resource allocation. This thesis explores the application of optimal control in a mathematical b...
Saved in:
Main Author: | |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/84122 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | In the banking sector, fund management and lending are two primary activities that significantly
impact profitability. Banks must balance risk and profitability, often involving
strategic decisions in resource allocation. This thesis explores the application of optimal
control in a mathematical banking model to maximize profit. The model is based on a
system of differential equations that describe the dynamics of deposits, loans, and bank
equity. The methodology employed includes the application of Pontryagin’s Maximum
Principle (PMP) and the Forward-Backward Sweep method to determine the optimal
strategy for setting deposit and loan interest rates. PMP is applied to obtain optimal
conditions and to define the control policies that the bank should implement, with the
controls being the deposit interest rate and loan interest rate. Numerical simulations
are conducted to test the effectiveness of this approach in practical scenarios. There
are control value constraints that must be adhered to in order to maintain the stability
of deposit rates, loans, and equity. Additionally, constraints arise from Bank Indonesia
regulations, requiring adjustments to the control value limits. Numerically, the profit
rate shows an increase ranging from 11.88% to 16.67% over time compared to before
control was implemented. Additionally, sensitivity analysis identifies key parameters
that influence the model’s performance, with important implications for strategic banking
decision-making. |
---|