Financial Information Rating System (Firms) As A Risk-Based Financial Allocation Model For Cooperative And MSMEs Financial Mitigation

Achmad Murdiono; Fadia Zen; Subagyo; Deni Bagas Pradana

doi:10.63922/ijbqr.v4i03.5234

Achmad Murdiono Universitas Negeri Malang, Malang, Indonesia
Fadia Zen Universitas Negeri Malang, Indonesia
Subagyo Universitas Negeri Malang, Indonesia
Deni Bagas Pradana Universitas Negeri Malang, Indonesia

DOI: https://doi.org/10.63922/ijbqr.v4i03.5234

Keywords: Financial Information Rating System, Early Warning System, Financial Distress, MSMEs

Abstract

Micro, Small and Medium Enterprises (MSMEs) have a strategic contribution to the national economy, but are still vulnerable to financial distress due to weak financial governance, limited financial planning, and low risk mitigation capacity. This study aims to develop and describe Financial Information Rating System (FIRMS) as Integrated Financial Rating and Early Warning System to support risk-based financial allocation and mitigation of MSME bankruptcy. The study uses a descriptive-development approach by integrating repayment indicators. capacity, cash flow quality, liquidity, financial planning, human resources quality, and financial governance into the risk rating system. Data were obtained through observation, interviews, documentation, and expert validation. The results of the study indicate that FIRMS is capable of producing objective financial ratings, identifying potential financial distress early and provide risk-based financing recommendations. FIRMS contributes to strengthening the financial resilience of MSMEs and supporting a more sustainable, inclusive, and adaptive financing system,

References

Ajzen, I. (2011). The theory of planned behavior : Reactions and reflections . Psychology & Health , 26(9), 1113–1127.
Altman , E.I., Iwanicz-Drozdowska , M., Laitinen , E.K., & Suvas , A. (2017). financial distress prediction in an international context : A review and empirical analysis of Altman's Z- score model . Journal of International Financial Management and Accounting , 28(2), 131–171.
Basel Committee on Banking Supervision . (2020). Principles for the Management of Credit Risk . Bank for International Settlements .
Breiman , L. (2001). Random forests . Machine Learning , 45(1), 5–32.
Hafeez , M., Khan, M.A., Ahmed, A., & Shah, S.A. (2022). Financial distress prediction using machine learning approaches : Evidence from emerging economies . Journal of Risk and Financial Management , 15(8), 1–19.
Hopkin , P. (2018). Fundamentals of Risk Management : Understanding , Evaluating and Implementing Effective Risk Management . Kogan Page .
Hristov , I., & Appolloni , A. (2022). Performance measurements systems and sustainability performance : The role of accountability and strategic alignment . Business Strategy and the Environment , 31(4), 1460–1478.
Hristov , I., & Chirico , A. (2019). The roles of sustainability key performance indicators in implementing sustainable strategies . Sustainability , 11(20), 5742.
Huston , SJ (2010). Measuring financial literacy . Journal of Consumer Affairs , 44(2), 296–316.
Huynh , T., & Uebelmesser , S. (2024). Early warning systems and financial distress prediction : Evidence from machine learning models . International Review of Financial Analysis , 91, 103051.
Ministry of Cooperatives and SMEs of the Republic of Indonesia. (2024). Development of Indonesian MSME data in 2024. Ministry of Cooperatives and SMEs of the Republic of Indonesia.
Lusardi , A., & Mitchell, O. S. (2014). The economics importance of financial literacy : Theory and evidence . Journal of Economics Literature , 52(1), 5–44.
Payne , A., Frow , P., & Eggert , A. (2017). The customer value proposition : Evolution , development , and application in marketing . Journal of the Academy of Marketing Science , 45(4), 467–489.
Ramirez, E., & Lim, S. (2021). Financial capability and SME sustainability : Evidence from developing economics . Small Enterprise Research , 28(3), 215–230.
Ramirez, H., & Lim, T.S. (2021). Performance of SMEs : Literature synthesis of contingency models . Problems and Perspectives in Management , 19(3), 276–287.