Empowering Philippine Banks with Real‑Time SME Risk Assessment and Digital Innovation
Philippine banks play a critical role in fuelling small‑business growth, yet lending to small and medium enterprises (SMEs) remains far below what policymakers envisioned. Recent data from the Bangko Sentral ng Pilipinas (BSP) show that total loans to micro, small and medium enterprises stood at ₱540.92 billion in mid‑2025—an increase of nearly 11 % from a year earlier but representing only 4.59 % of the banking sector’s ₱11.78‑trillion lending portfolio. This is well below the 10 % quota established under the Magna Carta for MSMEs, which requires banks to allocate 8 % of their loan book to micro and small enterprises and 2 % to medium‑sized businesses. While the quota includes micro enterprises, CreditBPO’s focus is on SME, commercial and corporate borrowers, yet the broader under‑lending environment still constrains growth. Facing penalties for non‑compliance, many banks still opt to under‑lend due to perceived risks—such as lack of collateral, unstable cash flows and thin credit histories—forcing many entrepreneurs to rely on informal lenders at high interest rates.
Why Traditional Credit Evaluation Falls Short
Banks’ reluctance to extend credit is often rooted in outdated risk‑assessment processes. Manual reviews of audited financial statements capture only a snapshot of a borrower’s financial position; they do not reflect real‑time cash‑flow volatility or early signs of distress. Static credit scores may overlook SMEs’ growth potential or resilience in turbulent markets, leading to overly conservative lending decisions and slow turnaround times. As a result, many credit committees hesitate to approve loans, even when demand exists, prolonging the financial inclusion gap.
AI‑Driven Credit Risk Assessment for SME Lending
To close this gap, a growing number of financial institutions, fintech platforms and non‑bank lenders are deploying AI‑based credit assessment tools that analyse alternative data—such as receivables and transaction histories—to deliver faster, more accurate risk profiles. These digital solutions depart from purely traditional metrics and have already helped hundreds of Philippine SMEs secure financing since 2020. By embracing innovative approaches such as AI‑based credit assessment, SMEs can overcome traditional barriers like lack of collateral and limited credit history and democratises access to finance. Such platforms demonstrate how digital lending can empower entrepreneurs who might otherwise be excluded by conventional banking criteria.
This shift mirrors global trends: AI‑driven credit risk models are transforming SME lending by providing real‑time, personalised credit solutions and significantly reducing loan processing times. Leading digital banks and fintechs across Asia use predictive analytics to continuously monitor borrower health, enabling them to approve or adjust credit limits more dynamically. Beyond credit decisions, AI is being used throughout the banking value chain—from automating loan approvals and enhancing fraud detection to refining risk modelling.
Industry research underscores the urgency of this shift. A 2025 BFSI Digital Transformation Survey found that 70 % of banks plan to adopt AI‑based credit‑scoring platforms, blending traditional documents like AFS with real‑time analytics. Meanwhile, a Deloitte study on emerging markets noted that cross‑checking audited financial statements against peer data can increase the accuracy of predicting potential loan defaults by 27 %. These insights highlight how AI and benchmarking work hand‑in‑hand to strengthen credit evaluations.
Preparing for Digital Assets and Wholesale CBDCs
Looking ahead, Philippine banks must also prepare for the next wave of innovation: digital assets and central‑bank digital currencies (CBDCs). The BSP recently completed testing of Project Agila, a wholesale CBDC pilot that allows financial institutions to transfer large‑value funds beyond regular banking hours using distributed ledger technology. BSP Governor Eli Remolona noted that wholesale CBDCs could enhance liquidity management, reduce settlement risks and strengthen financial stability. By leveraging open‑source DLT and infrastructure from partners like Oracle, Project Agila aims to provide 24/7 interbank payments and cross‑border settlement. Experts emphasise that such systems could improve liquidity management, enable cheaper cross‑border transactions and boost the competitiveness of local banks, but they also warn that adoption will require robust infrastructure, education and coordination across the financial ecosystem.
How CreditBPO Enhances Real‑Time SME Credit Assessment
CreditBPO’s Financial Condition Rating & Benchmarking solution is designed to help banks bridge the gap between traditional credit evaluation and modern, data‑driven lending. Instead of relying solely on year‑old financial statements, the platform ingests audited, in‑house and projected financial statements, along with interim data and macro‑economic indicators, to provide a continuous view of a borrower’s financial condition rather than a one‑time snapshot. This approach preserves the primacy of AFS while supplementing them with up‑to‑date insights, enabling credit committees to:
- Identify early warning signs—such as declining receivables quality or supplier defaults—before they result in defaults or delayed payments.
- Benchmark SME performance against peers in the same industry, adjusting credit limits or pricing accordingly.
- Reduce manual workload by automating data collection and analysis, freeing bankers to focus on relationship building.
Moreover, CreditBPO is developing capabilities to integrate with emerging digital‑asset infrastructures, ensuring that banks can adapt their risk models as tokenised assets and wholesale CBDCs become part of the lending landscape.
A Blueprint for Banks
To thrive in this evolving environment, banks should consider the following actions:
1. Modernize data pipelines: Integrate real‑time transaction and receivables data into credit assessment workflows to gain a holistic view of SME health.
2. Adopt predictive analytics: Use AI‑driven models to forecast cash‑flow gaps, detect anomalies and recommend proactive interventions.
3. Collaborate with fintech platforms: Partner with alternative financing providers and data‑driven platforms to access richer datasets and extend financing options to SMEs.
4. Strengthen digital infrastructure: Prepare for wholesale CBDCs by upgrading payment systems and ensuring interoperability with DLT networks.
5. Invest in talent and risk governance: Train staff on AI, data analytics and digital asset management, and establish ethical guidelines to mitigate bias and ensure explainable decision‑making.
Conclusion and Call to Action
Philippine banks stand at a crossroads: continue with legacy processes that under‑serve SMEs or embrace data‑driven tools that unlock new lending opportunities. By adopting real‑time risk assessment and preparing for digital‑asset integration, banks can expand access to credit, comply with regulatory quotas and remain competitive in a rapidly changing financial landscape.
Interested in transforming your SME, commercial or corporate lending strategy? Our CreditBPO Rating Report evaluates borrowers using audited, in‑house and projected financial statements and benchmarks them against industry peers to deliver objective risk scores and actionable insights. Read more in the accompanying article on CreditBPO’s blog and book a discovery call to see how our Financial Condition Rating & Benchmarking solution can help your institution deliver faster, smarter and more inclusive credit decisions.
👉 Book a discovery call: https://calendly.com/lia_creditbpo/client-discovery-call
