AccScience Publishing / NSCE / Online First / DOI: 10.36922/NSCE026170014
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RESEARCH ARTICLE

Nonlinear dynamics of a discrete-time banking monopoly model with delayed risk effects

Moch. Fandi Ansori1*
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1 Department of Mathematics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia
Received: 20 April 2026 | Revised: 10 June 2026 | Accepted: 23 June 2026 | Published online: 10 July 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Bank lending dynamics are strongly influenced by internal adjustment mechanisms and accumulated risk exposure, both of which can contribute to financial instability if they are not properly managed. In this study, we propose a discrete-time banking monopoly model with delayed risk effects, in which the current lending decision depends on both current profitability and the previous-period loan portfolio. The delayed component is introduced to capture the economic impact of accumulated credit risk, regulatory capital pressure, and expected loss provisioning associated with loan expansion. Using a gradient-based bounded-rationality framework, the model was formulated as a two-dimensional, nonlinear map. We derive the equilibrium points and establish explicit local stability conditions using the Jury criterion. Furthermore, bifurcation analysis shows that the positive equilibrium may lose stability through flip and Neimark–Sacker bifurcations, depending on the interaction between the adjustment speed and the delayed risk intensity. Numerical simulations, including bifurcation diagrams, Lyapunov exponents, isoperiodic diagrams, and basin-of-attraction plots, reveal rich nonlinear phenomena such as periodic oscillations, quasi-periodicity, and chaos. These results show that delayed risk exposure can be an endogenous cause of instability in the lending dynamics. It also outlines the role of prudential adjustment policies in ensuring stability in the banking sector.

Keywords
Banking dynamics
Delayed risk effects
Discrete-time systems
Bifurcation analysis
Chaos
Funding
None.
Conflict of interest
The author declares no competing interests.
References
  1. Gerali A, Neri S, Sessa L, Signoretti FM. Credit and Banking in a DSGE Model of the Euro Area. J Money Credit Bank.2010;42(s1):107-141. https://doi.org/10.1111/j.1538-4616.2010.00331.x
  2. Bosch T, Mukuddem-Petersen J, Petersen MA. Accounting, Cyclicality and Financial Stability: The South African Experience (1990--2007). In: Encyclopedia of Finance Research. Nova Science Publishers; 2012:685-760. Accessed June 25, 2026. https://novapublishers.com/shop/encyclopedia-of-finance-research-2-volume-set/.
  3. Andrieş AM, Ongena S, Sprincean N. Sectoral Credit Allocation and Systemic Risk. J Financ Stab.2025;76:101363. https://doi.org/10.1016/j.jfs.2024.101363
  4. Grilli R, Tedeschi G, Gallegati M. Bank Interlinkages and Macroeconomic Stability. Int Rev Econ Finance.2014;34:72-88. https://doi.org/10.1016/j.iref.2014.07.002
  5. Riccetti L, Russo A, Gallegati M. Financial Regulation and Endogenous Macroeconomic Crises. Macroecon Dyn.2018;22(4):896-930. https://doi.org/10.1017/S1365100516000444
  6. Ferilli GB. The Dual Impact of Digital Lending on European Banks: How Do Fintech Platforms Affect Bank Stability and Loan Portfolio Quality? In: Innovation in Banking and Financial Intermediaries: The Disruptive Role of ESG Policies and Fintech Players. Taylor & Francis; 2025:216-232. https://doi.org/10.4324/9781003539759-13
  7. Mwanjilinji EE, Shakiru TH, Huang FM. The Role of Credit Risk in Shaping the Profitability of the Banking Sector in the World's Largest Economies: Evidence from Panel Quantile Regression. SN Bus Econ.2025;5(11). https://doi.org/10.1007/s43546-025-00964-y
  8. Malovaná S, Hodula M, Bajzik J, Gric Z. Bank Capital, Lending, and Regulation: A Meta-Analysis. J Econ Surv.2024;38(3):823-851. https://doi.org/10.1111/joes.12560
  9. Mujtaba G, Akhtar Y, Ashfaq S, Abbas Jadoon I, Hina SM. The Nexus Between Basel Capital Requirements, Risk-Taking and Profitability: What About Emerging Economies? Econ Res.2022;35(1):230-251. https://doi.org/10.1080/1331677X.2021.1890177
  10. Mueller I, Sfrappini E. Climate Change-Related Regulatory Risks and Bank Lending. J Int Econ.2025;158:104156. https://doi.org/10.1016/j.jinteco.2025.104156
  11. Sagliaschi U, Savona R. Continuous Time Models, Unsecured Debt and Commitment. In: Contributions to Finance and Accounting. Springer Nature; 2021:113-141. https://doi.org/10.1007/978-3-030-77853-8
  12. Vincent A, Sumarti N. Implementation of the Banking Dynamics Model Using a System of Deterministic Differential Equations. Front Appl Math Stat.2025;11:1517447. https://doi.org/10.3389/fams.2025.1517447
  13. Begenau J, Bigio S, Majerovitz J, Vieyra M. A Q-Theory of Banks. Rev Econ Stud.2026;93(1):106-143. https://doi.org/10.1093/restud/rdaf035
  14. Ansori MochF. Dynamic Modeling and Optimal Control of Bank Balance Sheets under Capital Adequacy Constraints. Int J Optim Control.2026;16(1):40-53. https://doi.org/10.36922/IJOCTA025250113
  15. Ansori MochF, Sumarti N, Sidarto KA, Gunadi I, Gümüş FH. Mathematical Model of Bank Balance Sheet with a Macroprudential Instrument and Its Application to Banking Data. Math Methods Appl Sci.2025;48(18):16789-16803. https://doi.org/10.1002/mma.70127
  16. Ansori MochF, Sumarti N, Sidarto KA, Gunadi I. An Algorithm for Simulating the Banking Network System and Its Application for Analyzing Macroprudential Policy. Comput Res Model.2021;13(6):1275-1289. https://doi.org/10.20537/2076-7633-2021-13-6-1275-1289
  17. Tramontana F. Dynamic Models of Financial Markets with Heterogeneous Agents. In: Springer Proceedings in Complexity. Springer; 2016:291-304. https://doi.org/10.1007/978-3-319-33276-5_6
  18. Szidarovszky F, Bischi GI. Games and Dynamics in Economics: Essays in Honor of Akio Matsumoto. Springer Singapore; 2020. https://doi.org/10.1007/978-981-15-3623-6
  19. Neamah ZH, Alawsi AAM, Ali HM, Ali AMA, Al-Baghdadi AF. Novel 3D-Chaotic Financial Model with Mesh Attractor: Complexity Analysis. Math Appl.2025;14(1):105-112. https://doi.org/10.13164/ma.2025.14107
  20. Chen WC. Dynamics and Control of a Financial System with Time-Delayed Feedbacks. Chaos Solitons Fractals.2008;37(4):1198-1207. https://doi.org/10.1016/j.chaos.2006.10.016
  21. Tramontana F, Gardini L, Westerhoff F. Intricate Asset Price Dynamics and One-Dimensional Discontinuous Maps. In: Financial Asset Pricing: Theory, Global Policy and Dynamics. Nova Science Publishers; 2011:191-204.
  22. Chian ACL, Rempel EL, Borotto FA, Rogers C. An Example of Intermittency in Nonlinear Economic Cycles. Appl Econ Lett.2006;13(4):257-263. https://doi.org/10.1080/13504850500394335
  23. Bouali S, Buscarino A, Fortuna L, Frasca M, Gambuzza LV. Emulating Complex Business Cycles by Using an Electronic Analogue. Nonlinear Anal Real World Appl.2012;13(6):2459-2465. https://doi.org/10.1016/j.nonrwa.2012.02.010
  24. Fanti L. The Dynamics of a Banking Duopoly with Capital Regulations. Econ Model.2014;37:340-349. https://doi.org/10.1016/j.econmod.2013.11.010
  25. Brianzoni S, Campisi G, Colasante A. Nonlinear Banking Duopoly Model with Capital Regulation: The Case of Italy. Chaos Solitons Fractals.2022;160:112209. https://doi.org/10.1016/j.chaos.2022.112209
  26. Brianzoni S, Campisi G. Dynamical Analysis of a Banking Duopoly Model with Capital Regulation and Asymmetric Costs. Discrete Contin Dyn Syst Ser B.2021;26(11):5807-5825. https://doi.org/10.3934/dcdsb.2021116
  27. Bacchiocchi E, Bischi GI, Giombini G. Non-Performing Loans, Expectations and Banking Stability: A Dynamic Model. Chaos Solitons Fractals.2022;157:111906. https://doi.org/10.1016/j.chaos.2022.111906
  28. Ansori MochF, Brianzoni S, Campisi G. Bifurcations and Complex Dynamics in a Banking Duopoly Model with Macroprudential Policy. Physica A.2024;641:129730. https://doi.org/10.1016/j.physa.2024.129730
  29. Ansori MochF, Ashar NY, Fata HK. Logistic Map-Based Banking Loan Dynamics with Central Bank Policies. J Appl Nonlinear Dyn.2025;14(3):561-574. https://doi.org/10.5890/JAND.2025.09.006
  30. Gümüş FH, Ansori MochF. Adaptive Dynamics of Bank Lending under Credit Risk: A Discrete-Time Modeling Approach. Konuralp J Math.2026;14(1):87-98.
  31. Stepanova S, Karakchieva V. Improving Loan Loss Provisioning Framework as a Driver of Economic Growth. J Corp Finance Res.2020;14(2):72-82. https://doi.org/10.17323/j.jcfr.2073-0438.14.2.2020.72-82
  32. Pastiranová O, Witzany J. IFRS 9 and Its Behavior in the Cycle: The Evidence on EU Countries. J Int Financ Manag Account.2022;33(1):5-17. https://doi.org/10.1111/jifm.12140
  33. Heid F. The Cyclical Effects of the Basel II Capital Requirements. J Bank Financ.2007;31(12):3885-3900. https://doi.org/10.1016/j.jbankfin.2007.03.004
  34. Reiter M, Zessner-Spitzenberg L. Long-Term Bank Lending and the Transfer of Aggregate Risk. J Econ Dyn Control.2023;151:104651. https://doi.org/10.1016/j.jedc.2023.104651
  35. Alsagr N, Apergis N. Total Climate Change Risk and Banks' Loan Portfolios: Fresh Evidence and Extensions. J Environ Manage.2025;394:127460. https://doi.org/10.1016/j.jenvman.2025.127460
  36. Phukan A, Dehingia K, Sarmah HK, Borah L. Dynamical Analysis of a Time-Delayed Financial System with Synchronization Strategies. Sci Prog.2026;109(1):368504261423737. https://doi.org/10.1177/00368504261423737
  37. Pei L, Sun M. Quasi-Periodic, Phase-Locked and Chaotic Solutions in a Financial System with Two Feedback Delays. J Vib Eng Technol.2025;13(1). https://doi.org/10.1007/s42417-024-01731-3
  38. Dou WW, Fang X, Lo AW, Uhlig H. Macro-Finance Models with Nonlinear Dynamics. Annu Rev Financ Econ.2023;15:407-432. https://doi.org/10.1146/annurev-financial-110921-112053
  39. Agur I. Bank Risk Within and Across Equilibria. J Bank Financ.2014;48:322-333. https://doi.org/10.1016/j.jbankfin.2014.05.012
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