CRIB AND LRA JOINTLY ANNOUNCE THE SOFT LAUNCH OF AI-POWERED DIGITAL DYNAMIC CREDIT RATINGS (DDCR) MODEL
The Credit Information Bureau of Sri Lanka (CRIB), in partnership with Lanka Rating Agency (LRA) as its technical partner, today announced the soft launch of the AI-powered Digital Dynamic Credit Ratings (DDCR) model, a transformative initiative set to reshape how small and medium enterprises (SMEs) will be benefited when evaluated for creditworthiness and access to capital.
One of the most critical challenges faced by SMEs today in accessing credit and capital is the absence of structured and verifiable data on income, expenses, credit history, and transactional behavior, key elements required to accurately assess creditworthiness. This gap is substantially addressed through the introduction of the Digital Rating Model. This pioneering model leverages authenticated and reliable credit data from CRIB, combined with advanced AI-driven analytics developed by LRA, to deliver a forward-looking, dynamic, and scalable framework for credit assessment. The DDCR model is designed to enhance transparency, improve risk pricing, and support more informed financial decision-making across the ecosystem.
The model has been rigorously developed with comprehensive stress testing and calibration across key economic factors, including macroeconomic volatility, interest rate movements, inflationary pressures, and sector-specific risks. These stress-testing mechanisms ensure that the rating outputs remain robust, adaptive, and reflective of evolving economic conditions.
LRA is also partnering with INF Technologies Singapore, integrating advanced AI capabilities and global technological expertise to further strengthen the analytical depth and scalability of the DDCR framework.
Commenting on the initiative, Mr. Pushpike Jayasundera, CRIB Director/ General Manager, stated: “This initiative reflects CRIB’s commitment to strengthening Sri Lanka’s financial infrastructure through the use of trusted, authenticated data coupled with technology and econometrics. By anchoring this model on CRIB’s robust data systems and enabling rigorous economic stress testing, we are supporting the development of a more accurate and forward-looking credit rating framework. Our collaboration with LRA ensures that this data is transformed into actionable intelligence that can meaningfully enhance credit assessment standards across the financial eco system.”
Speaking on the technological collaboration, Dr. Alan Qi, globally recognized AI thought leader and partner at INF Technologies Singapore, stated: “Artificial intelligence is fundamentally redefining how credit systems are designed and interpreted. The DDCR framework represents a forward-looking approach that integrates structured data, predictive modelling, and adaptive intelligence to produce more dynamic credit insights. I am particularly aligned with LRA’s vision, as forward-looking rating agencies like this play a critical role in strengthening national balance sheet resilience. Our collaboration is focused on building credit rating systems that are not only accurate today, but also future-ready, capable of evolving alongside economic complexity and digital transformation.”
Dr. Kenneth De Zilwa, CEO of LRA, added: “This is a pivotal moment for Sri Lanka’s financial landscape. As the technical partner to CRIB, LRA has focused on building a model that fully harnesses authenticated data and advanced AI to deliver intelligent, predictive credit ratings. Through our partnership with INF Technologies Singapore, a technology partner specializing in enterprise agentic AI and data solutions, we are further enhancing the AI architecture underpinning the DDCR model. This initiative reflects our commitment to developing credit rating systems that are dynamic, resilient, and aligned with the future of financial decision-making.”
The CRIB–LRA collaboration represents a powerful alignment between national credit infrastructure, advanced financial analytics, and global AI expertise, positioning Sri Lanka at the forefront of innovation in credit rating methodologies.
The soft launch marks the beginning of a phased rollout, with further enhancements, integrations, and system-level adoption planned in the coming months.
