Indonesia Credit Reporting Ecosystem: Study on Regulatory Frameworks and Perimeter Between PCR & PCB

Indonesia is an expansive archipelago with a large population of over 270 million (~208 million aged 15 years and older), depicting a potential geographic barrier to coverage of financial services. Currently, 65.4% of Indonesian adults own financial accounts (OJK), and 85.1% of the population make use of financial services. Indonesia’s retail loan market is also projected to reach ~IDR 2,550 Tn by 2027, seeing significant growth in mortgage and vehicle loans. P2P lending also shows significant growth (CAGR +65% FY19–23) and is replacing traditional collateral-based loans, especially for younger age groups who lack the financial history, while credit card services remain stagnant at ~17Mn cards issued. Furthermore, Indonesia’s low household loans to GDP ratio of 16.2% is considerably lower than comparable peers who average above 30%.

These factors reflect a large demand for unsecured loans, but limited accessibility and inclusivity for the general population; unsecured loans are highly dependent on creditworthiness evaluations to mitigate risk of bad loans. This indicates a core issue of whether the country’s financial sector leverages financial data efficiently. Hence, there is a need for refinement of credit worthiness evaluations to support expansive and inclusive lending products—extending loan access to all levels of society while maintaining robust risk management for lenders. Essential to this endeavor is the enhanced collaboration between PCR and PCB, permitting analysis of both traditional and alternative data to develop a comprehensive evaluation of each borrower.

Current market conditions for lending in Indonesia bring into question the resilience and innovative capacity of the PCBs in the country’s financial system, as well as the effectiveness of banking services and the robustness of the supporting framework. To address these issues, a comprehensive understanding of Indonesia’s dual-system (PCR-PCB) model, its primary drivers of adoption, stakeholder boundaries, and mechanisms for data sharing among different industry stakeholders, is necessary. This will further augment efforts to achieve robust financial data analysis for improved risk management, which will foster access to credit and other financial products, financial literacy, and hence financial inclusion.

 Executive Summary 

1. The establishment of SLIK, a Public Credit Registry (PCR) by OJK, has facilitated secure information exchange amongst financial institutions in Indonesia, fostering enhanced risk management and curbing over-borrowing. However, while these strides offer a stepping stone towards financial deepening, SLIK currently focuses on conveying existing credit information with minimal data processing. Contrary to PCBs, which improve data quality through additional data cleansing, consolidation of financial data from institutions not yet covered by SLIK, and data analysis and interpretation. Notably, there’s a shortage in innovations that could incorporate those who lack traditional financial history (thin-file, new-to-bank, underbanked)–a critical element to increasing financial depth.
2. In founding LPIP, containing Private Credit Bureaus (PCBs), OJK is optimistic that LPIP members can introduce innovative credit assessment models that cater to individuals with unconventional financial history. This solution aims beyond financial inclusion; it’s an endeavor to create a robust credit data-centric financial system. Simultaneously, OJK’s establishment of SLIK and the initiation of LPIP sets the stage for a dual-monitoring model—a system gaining traction in many countries looking to develop their credit data infrastructure. To ensure the success of such a model, defining clear boundaries and collaboration avenues between the PCR and PCBs is vital. These definitions should be reflective of the current Indonesian landscape, the country’s aspirations, and more so, the desired outputs of PCR and PCBs as well as the industry stakeholders’ transactional paradigms. The ineffectiveness in the interaction between PCRs and PCBs leads to less comprehensive credit reports for risk assessments and inhibits the continual innovation of credit modeling that can accurately evaluate credit behavior.
3. Our comparative study in the global credit reporting domain has led to the identification of five interaction models: PCR-only, PCR-driven, dual-system, PCB-driven, and PCB-only. We have gleaned valuable insights from global benchmarks, pinning down three potential cooperation modes between PCR, PCB, and other stakeholders: Visible and Non-visible, Segment Based, and Tiered Charging. Implementing this could serve as a crucial step to actualize Indonesia’s ambition to fast-track financial inclusion and financial literacy growth. However, we must evaluate if this dual-monitoring system sits well with the Indonesian population and if the infrastructure is adequately fortified. These are essential queries to address to ensure a smooth transition towards a thoroughly banked economy with better use of credit data in Indonesia.