The Credit Information Bureau (CRIB) has spent 35 years building what its Director/General Manager Pushpike Jayasundera describes as the foundation of a digital economy: an updated, well governed, validated data lake. But with roughly half the country’s working-age adults holding no formal credit profile, CRIB is now moving beyond this traditional role.
It will soon add a mobile app, an AI-driven SME rating model, digital ID verification tool, SME Score and a cross-border data sharing framework to expand its reach and improve access to financing across the country.
What will the CRIB mobile app offer users, when it launches in July?
The app is designed as a one-stop digital platform for all credit-related services, from understanding your credit standing to disputing errors and sharing your report with third parties for greater financial empowerment.
Every user gets a free dashboard showing their credit score the moment they download it. From there, they can access their full credit profile, credit score, receive AI-driven advice to improve their creditworthiness, and get real-time alerts, such as the status of your guaranteed facilities, changes in credit records, credit status changes etc.
CRIB expects 20,000 to 25,000 users per month to adopt the app, supporting greater access to credit and financial services at the grassroots level.
Half of Sri Lanka’s adults still rely on informal lending. How does CRIB’s push into non-traditional data like insurance, utilities, telco help to close that gap?
Of Sri Lanka’s 17 to 18 million working-age adults, CRIB holds profiles on roughly half. The other nine million or so have no formal credit footprint, which is precisely why they remain dependent on informal lenders outside the banking system. Alternative data sources such as utilities, telecommunications, and insurance records will provide the means to create the credit profiles to bring them into the formal credit ecosystem.
Having relevant data with proper context is valuable, but we’re also conscious of the quality of what is collected. CRIB runs incoming pre-validated data through more than 600 internal validation rules, updates records once a month, and complies with ISO 27001;2022 and ISO 8000 standards using advanced technology. Simply capturing basic data fields like mobile number or address at a supermarket checkout is not the same thing, data must be gathered, validated, governed and used within a robust framework to generate meaningful insights.
For someone in a rural area whose only financial footprint is a prepaid mobile account, that validated telco data or utility information becomes the basis for building a credit profile. In turn, it eventually becomes a pathway to formal credit on better terms.
Most Sri Lankan banks now factor in credit scores. What does that mean for loan applicants, and how does CRIB ensure the underlying data is reliable?
Adoption across the banking sector now sits at around 85%, and the practical impact is significant. Retail credit decisions that once took three to four days can now be executed in minutes, with some banks granting facilities digitally for borrowers with high scores and no additional collateral expected. Corporate facilities, previously taking weeks to grant, have seen similar compression. A credit score acts as a form of reputational collateral, removing the need for brick-and-mortar due diligence built on unverified information.
Reliability is maintained through a multi-layered process. Data is verified at source before it reaches CRIB, then passed through our 600 validation rules. Where anomalies are flagged, such as data elements that have been consistent for months and suddenly shift, an AI-driven monitoring model raises an alert and the relevant institution is asked to verify. CRIB also offers lenders retrospective portfolio analysis going back on decisions, allowing them to check how borrowers with particular scores have actually performed after facilities were granted. Solutions we provide are data-driven, scientifically developed, and built on accuracy, consistency, and predictive performance.
The Digital Dynamic Credit Ratings (DDCR) model uses AI to generate ratings for small businesses. What does this enable for businesses that have historically struggled to access formal credit?
The distinction between a credit score and a rating matters here. A score is derived purely from credit behaviour and it is a model to ascertain probability of default (PD). A rating takes a wider view, including income and affordability, equity invested in the business, and the capability of its management. For the roughly 1.3 million Micro, Small, and Medium Enterprises (MSMEs) operating in Sri Lanka, fewer than 17% of which are formally captured in any structured way, this broader assessment is what makes the difference between being bankable or not.
The DDCR model blends CRIB’s existing credit data with income data and non-traditional sources to produce a dynamic rating, reviewed twice a year, that a business owner can present directly to lenders. The practical outcomes are tangible: faster approval, lower interest rates, longer repayment periods, reduced security requirements, and low post execution cost.
Income data assessment is handled by Lanka Rating Agency, under a formal agreement with CRIB, providing human validation alongside the AI-driven model.
CRIB is building a cross-border data sharing framework so investors and migrant citizens can share their credit histories with them. How does that work?
The model is bureau-to-bureau. Where CRIB has signed MOUs with a counterpart bureau in another country complying with regulatory requirements, individuals and entities can port their credit history across borders. For a Sri Lankan exporter entering a new market, that means credit lines can be arranged from day one. For an investor arriving in Sri Lanka, it means immediate access to the banking system without having to establish credibility from scratch.
South Korea is a practical example. Large numbers of Sri Lankan workers seek employment there, and a verified credit profile is a formal requirement for entry into the country’s banking system on arrival. Agreements with each bureau have to be negotiated individually, with data sharing frameworks adjusted to meet varying regional requirements. For an economy that needs foreign investment, the ability to verify a visitor’s creditworthiness from day one is worth the work.