1. What is Credit Underwriting

Our second use case focuses on credit underwriting, where secure, real-time data sharing can significantly enhance both user experience and credit risk assessment.

In this context:

• Data Providers (DPs) are institutions that hold a user’s financial data — such as banks, EPF, or other regulated sources.

• Data Consumers (DCs) are institutions that, with the user’s consent, retrieve that data to offer financial services — such as lenders, credit scoring platforms, or fintechs.

It’s also important to note that a single institution can play both roles — for example, a bank may act as a DP when exposing its customer’s data, and as a DC when retrieving data from other institutions to support its own loan underwriting or credit scoring.

Traditionally, loan applicants must manually submit documents such as pay slips and bank statements — an inefficient and often insecure process.

With Open Finance, users can consent to share verified financial data — such as account balances, income flows, and transactions — from multiple DPs to a DC as part of a loan application. This enables real-time data access, supports cashflow-linked lending, automated affordability checks, and helps users build credit readiness for larger future purchases such as homes or vehicles.

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2. The Problem with Current Financial Data Sharing

Today, applying for a loan often requires users to share sensitive financial information, but the process remains insecure, inconsistent, and frustrating. In the absence of standardised, institution-to-institution data sharing, applicants are burdened with manually gathering and submitting documents such as bank statements, payslips, and EPF records. These documents are often shared through insecure channels like email, WhatsApp, or upload portals, increasing the risk of data breaches.

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This section highlights the common pain points in the current user journey:

• Manually retrieving bank statements, salary slips, EPF/SOCSO contribution records, etc.

• Sharing financial documents via PDFs, screenshots, or images

• Submitting through email, chat platforms, or manual upload forms

• Lack of clarity over data ownership and limited traceability

• High operational costs and delays for Data Consumers (DCs), such as lenders and financial institutions

These fragmented and error-prone methods are not only inconvenient but also introduce significant risks, including identity theft, privacy leaks, fraudulent activities, and exposure to phishing attacks. Moreover, the friction in the user experience can lead to high drop-off rates, reduced conversion, and longer turnaround times for loan approvals.

Transforming Loan Underwriting experience with Open Finance Data Integration:

Open Finance fundamentally reimagines this process by enabling secure, consent-driven data access across financial institutions. Instead of manually uploading documents, users can authorise regulated entities to retrieve verified financial data directly from trusted sources through secure APIs.

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This transformation offers several key benefits:

• Frictionless Experience: Borrowers can apply for loans without collecting and uploading documents, reducing abandonment and application fatigue.

• Enhanced Security & Trust: Consent-based data sharing mitigates risks associated with file tampering, phishing, and unauthorised access.

• Faster Underwriting: Lenders receive structured, real-time financial data (e.g., income verification, account balances, repayment history), allowing for quicker and more accurate assessments.

• Operational Efficiency: Automated data retrieval reduces processing time, administrative workload, and manual errors, leading to faster decisions and lower costs.

• Better Compliance & Auditability: Every data access is traceable, transparent, and auditable, ensuring compliance with privacy regulations such as Malaysia’s PDPA.

By embedding open finance data integration into the loan underwriting process, financial service providers can not only improve approval rates and turnaround times but also deliver a more trusted, transparent, and seamless experience to consumers — laying the foundation for a more inclusive and resilient credit ecosystem.

3. How Manual processes impact Loan Underwriting?

The manual nature of data collection and authentication doesn’t just frustrate users — it creates compounding inefficiencies for users and DCs. Without structured access to data from DPs, DCs must rely on manual uploads and validations, which introduces friction, errors, and security concerns.

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Inefficient and Fragmented Data Collection

• Users must submit unstructured documents from various DPs (e.g. bank statements, EPF reports)

• DCs manually extract, standardize, and interpret data — slowing decisioning

High Operational Burden for Users and DC Administrators

• Users face friction resubmitting or clarifying data

• DCs validate authenticity manually (e.g. employer verification)

• Exception handling increases cost and cycle time

Inconsistent and Manual Authentication

• Onboarding and KYC practices vary between DCs

• Lack of standardisation leads to uneven user experiences

Security and Privacy Risks

• Data sent over unsecured channels (email, messaging apps)

• Users and DCs face privacy, compliance, and reputational risks

Slow and Cumbersome Onboarding

• Prolonged back-and-forth increases drop-off

• Users apply to multiple DCs in parallel to speed up approvals

4. Potential Improvements with Open Finance Adoption

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Centralised and Streamlined Data Aggregation

With user consent, data can be shared from one or multiple DPs to a DC — which may include the same institution retrieving its own data as well as from others — via secure APIs. This reduces the need for manual uploads and allows for standardised, machine-readable data formats.

Enhanced Data Integrity, Security, and Privacy

• Data is authenticated at the DP source, reducing manual fraud checks

• Transmission occurs through encrypted channels with traceability

• Consent is logged and governed end-to-end

Consistent and Trusted Authentication Flows

• DPs authenticate users using secure login and SCA

• DCs receive data only with valid, user-consented tokens

• Uniform UX improves trust and compliance

Faster, More Seamless Loan Onboarding

• Real-time data retrieval shortens time-to-approval for low-risk credit products

• Complex products like mortgages benefit from clearer, structured information

• DCs reduce overhead, improve throughput, and reallocate resources to higher-value activities

Improved Loan Portfolio Quality

• Access to fresh, standardised data enables better segmentation and pricing

• DCs can underwrite previously underserved users (e.g. gig workers)

• Risk models improve as data quality improves5. Key Retail Lending Segments in Malaysia

Credit underwriting is a foundational process applied across a range of retail lending products in Malaysia. Each segment varies in scale, credit risk profile, and approval dynamics , but all require the ability to assess borrower affordability, income stability, and financial behavior.

The table below highlights key loan categories in the Malaysian consumer credit landscape:

These segments form the core focus for digital lending innovation, where Open Finance has the potential to improve risk assessments, reduce onboarding friction, and expand access — especially among thin-file or gig economy users.

To support these loan products, credit underwriting typically draws on data such as:

• Income and cash flow patterns

• Outstanding liabilities

• Consistent payment behaviors (e.g. rent, utilities, credit repayments)

• Employment and EPF contribution history

• Debt servicing ratios

Retail Credit Instruments (for individuals)

6. How Other Countries Work on It: International Use Cases

Open Finance has enabled lenders in several countries to move toward faster, more data-driven credit underwriting. Below are examples of how consent-based data access is being applied in real-world lending across various credit products — from personal loans to mortgages and BNPL.

7. Key Takeaways – “Smarter Lending Starts Here”

Credit underwriting is one of the most immediate and impactful use cases under Malaysia’s Open Finance initiative.

By enabling secure, consent-based access to verified financial data, Open Finance helps improve risk assessment, streamline onboarding, and support fairer lending — especially for underserved or thin-file segments.

As our financial ecosystem evolves, Open Finance can play a key role in addressing the core challenges that financial institutions and borrowers face today:

✅ Reducing friction in loan applications by removing the need for manual document uploads
✅ Supporting dynamic and real-time affordability checks using verified income and liability data
✅ Enabling cashflow-based credit assessment for gig workers, MSMEs, and new-to-credit users
✅ Improving loan decision quality through access to fresher, authenticated data

With collective effort, we can build a credit underwriting experience in Malaysia that is not only more efficient — but also more inclusive, secure, and trusted.