Research conducted by Rizqi Adhyka Kusumawati and Arief Darmawan from the Universitas Islam Indonesia (UII) in June 2026 focuses on modernizing the financing risk assessment system at the Bank Pembiayaan Rakyat Syariah (BPRS) UII using Artificial Intelligence (AI) technology.
Background and Issues
BPRS UII faces significant challenges in financing risk management because the customer eligibility assessment process has historically relied heavily on the subjective judgment of credit analysts. This reliance on manual assessment creates risks of bias, inaccuracy, and inefficiency in credit-granting decision-making.
Research Methodology
The study employed a participatory and collaborative approach with the following stages:
- Observation and Needs Gathering: Identifying weaknesses in the existing risk assessment system.
- Application Development: Building a Credit Risk Rating (CRR) application using the Flutter platform and the Dart programming language.
- Assessment System: Combining two assessment models: a logic gate-based model for the retail segment and an AI-based assessment model for data automation.
- Training and Evaluation: Conducting Credit Risk Scoring module training for staff, providing mentorship, and evaluating system effectiveness.
Key Findings
- Assessment Automation: The AI-based CRR application reduces dependence on the subjective judgment of human analysts, making the assessment process more measurable, objective, and consistent.
- Increased Effectiveness: The integration of an AI system enables the bank to perform more comprehensive and rapid data analysis on customer risk profiles.
- Provision of Training Modules: The development of the Credit Risk Scoring module provides technical skill support for BPRS UII staff in operating the new system to strengthen overall risk management.
Practical Implications
The implementation of this application has a tangible impact on BPRS UII's operations:
- Risk Mitigation: Enhancing the bank's ability to identify financing risks at an early stage.
- Operational Efficiency: Accelerating the financing approval process without compromising the accuracy of credit eligibility assessments.
- Standardization: Creating a uniform risk assessment standard within the bank, in accordance with OJK regulations regarding the implementation of risk management in BPRS.
Author Profile:
- Rizqi Adhyka Kusumawati, Arief Darmawan – Faculty of Business and Economics, Universitas Islam Indonesia, Yogyakarta.
Research Source: Kusumawati, R. A., & Darmawan, A. (2026). "Designing an AI-Based Credit Risk Rating and Data Analysis Application to Improve the Effectiveness of Financing Risk Management at BPRS UII".
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