Global lessons, local action: What Bangladesh can learn from global credit models

In today's data-driven economy, the credit scoring system has become a cornerstone of modern financial infrastructure. By enabling more efficient risk management, score-based lending is playing a crucial role in advancing financial inclusion.

As Bangladesh enters a new phase of digital transformation, the establishment of resilient credit scoring systems is no longer optional—it is essential.

Building credit profiles for all adults

To further strengthen Bangladesh's financial infrastructure, it is imperative to develop score-based credit profiles for all adult residents. A robust, analytics-driven framework for credit assessment is necessary to evaluate credit risk seamlessly and effectively.

Despite several challenges, the recent initiative by the Bangladesh Bank (BB) to encourage the formation of private credit bureaus marks a significant and strategic step forward. This move aims to improve risk assessment practices and expand financial inclusion.

The policy outlines a framework for privately operated credit scoring systems that function within a regulated, secure, and ethical environment. It prioritises data privacy, customer consent, adherence to BB's ICT security guidelines, and mandates that data remain stored within Bangladesh.

Bangladesh Bank began accepting online applications for credit bureau licences on 1 July 2024. A final call for applications was announced via its web portal, with the submission window closing on 9 April 2025.

Current gaps in access to credit

Bangladesh's financial system is undergoing a transformative shift. However, a critical gap remains: millions of creditworthy individuals and small businesses still cannot access formal credit due to the absence of traditional credit histories.

Traditional credit assessments in Bangladesh rely heavily on formal banking relationships. This approach excludes nearly half of the adult population. Cutting-edge credit bureaus capable of utilising non-traditional data sources could revolutionise the system.

The promise of modern credit bureaus

Modern credit bureaus can create comprehensive credit profiles by incorporating alternative data—such as telecom records, utility payments, e-commerce activity, and other digital footprints. This innovation is essential to unlocking inclusive and responsible lending, thereby bridging Bangladesh's persistent financial divide.

Understanding credit scoring

Typically, credit scores range from 300 to 1,000, with higher scores indicating greater creditworthiness. AI-driven score engines can generate credit scores by integrating traditional financial data with alternative data and digital behaviour patterns.

When aligned with ethical AI practices and rigorous consent mechanisms, credit scores can influence more than just lending—they also impact employment decisions, housing rentals, and insurance premiums.

Rising digital adoption and data availability

Bangladesh's growing digital footprint presents vast opportunities. With over 90 million mobile wallet users, more than 3 trillion online transactions annually, and an increasing number of digital lending platforms, the nation is generating an enormous volume of alternative data.

These include mobile top-ups, utility payments, e-commerce transactions, and social media activity. When used responsibly, these data points provide powerful insights into consumer behaviour, enabling credit bureaus to develop financial profiles even for the unbanked.

Banks and financial institutions (FIs) are increasingly seeking faster, more accurate, and inclusive credit assessments. These assessments reduce the risk of default and help expand their customer base. Meanwhile, consumers and cottage, micro, small, and medium enterprises (CMSMEs)—particularly those previously excluded—are eager for tools that help them build a financial identity and access affordable credit.

Global experiences with credit scoring systems

Globally, innovative credit scoring systems are being harnessed to promote financial inclusion. In India, the rollout of private credit bureaus has proceeded smoothly. To enhance credit information systems, the Reserve Bank of India has established a Public Credit Registry (PCR), integrating financial and non-financial data from banks, non-banking financial companies (NBFCs), and tax records.

This initiative promotes transparency and strengthens credit risk evaluation. Advanced scoring models now draw from Aadhaar-linked profiles, Unified Payments Interface (UPI) data, utility bills, and mobile usage to extend credit access to individuals who are new to credit or outside the formal financial system.

In Malaysia, a robust open banking ecosystem is emerging. Organisations such as CGC Digital, PayNet, and the Malaysia Digital Economy Corporation (MDEC) are collaborating to close the RM90 billion MSME financing gap. They leverage alternative data to offer inclusive, data-driven credit access for underserved businesses.

Singapore combines transactional data through open banking principles, in partnership with fintech firms and credit bureaus, for more precise assessments. In the United States, the Fair Credit Reporting Act (FCRA) underpins the use of AI and machine learning to enable real-time credit scoring and increased use of alternative data.

The United Kingdom also utilises its open banking infrastructure for real-time scoring and promotes consumer transparency. Internationally, Experian, Equifax, and TransUnion remain leaders in this space.

AI/ML-driven scoring models are gaining global traction, particularly for small-ticket loans, women entrepreneurs, and underserved populations. These models address the cost and inefficiency of traditional credit evaluations.

Explainable AI (XAI), real-time monitoring, and bias detection support the dynamic generation of credit scores, ensuring transparency, compliance, and fairness in the decision-making process.

Challenges to overcome

Several challenges must be addressed to implement a fair and effective credit scoring system in Bangladesh. Strong regulatory frameworks, public-private collaboration, the use of alternative data, improved financial literacy, and the adoption of global best practices are essential.

However, these approaches must be adapted to Bangladesh's unique context. The country's large informal economy, fragmented data systems, bureaucratic hurdles, and underdeveloped digital infrastructure pose considerable obstacles.

A robust credit bureau architecture must begin with a comprehensive data ingestion layer. This should aggregate information from traditional sources—such as the Credit Information Bureau (CIB), banks, financial institutions, and microfinance institutions—as well as alternative channels like mobile financial services (MFS), utility companies, telecom providers, and public records (e.g., national ID, court documents).

With user consent, incorporating behavioural data such as mobile phone usage and e-commerce activity will enhance the sophistication and utility of credit scoring systems. It is also essential to avoid common international pitfalls, such as errors in credit reports and limited data coverage.

Path forward: Building a resilient credit culture

To foster a fair and effective credit culture, Bangladesh's regulators must implement strong data protection laws, ensure equitable access, prioritise transparency, and promote inclusive scoring models.

A locally tailored strategy—grounded in global best practices but aligned with domestic realities—will pave the way for a resilient credit culture. This culture must support financial inclusion and drive sustainable economic growth.

Bangladesh has the potential to make significant progress in credit penetration, lower borrowing costs, and empower its population. With strategic planning and robust infrastructure, a dynamic and inclusive credit bureau system could be fully operational by 2030, unlocking new economic opportunities for millions.

Md Abdul Kader serves at a leading private commercial bank and is the author of "Banking of Tomorrow: The Art and Science of Risk Management in Retail, CMSME, and Digital Banking."

Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the opinions and views of The Business Standard.