Securing a loan can often serve as a profound turning point in an individual’s life, unlocking the necessary capital required to launch a new enterprise, purchase a home, or secure long-term financial investments. Yet, for a significant portion of Cambodia’s population, navigating the formal banking sector remains a formidable obstacle. According to data from the National Bank of Cambodia, a substantial 41 percent of the adult population operates entirely outside the formal financial ecosystem, relying instead on informal networks or managing without financial services altogether. This exclusion is largely driven by historical difficulties in accessing formal institutions and a total absence of the traditional financial data typically required by lenders to assess creditworthiness.
However, a profound transformation is currently underway across the nation’s lending landscape, offering a renewed sense of optimism for the unbanked and underbanked. Driven by a rapidly expanding fintech ecosystem and the growing viability of alternative-data credit frameworks, Cambodia is charting a clear path toward broader financial inclusion. These emerging frameworks seek to integrate non-traditional metrics into risk assessments, opening doors for individuals and micro, small, and medium enterprises (MSMEs) that have historically been left out of the formal credit conversation.
Industry leaders emphasize that this shift could fundamentally alter how risk is evaluated. According to Ms. Phal-Chalm Theany, Secretary General of the Association of Banks in Cambodia, alternative data holds tremendous potential to complement the traditional information historically relied upon by commercial banks. These non-traditional indicators range widely, encompassing everything from mobile wallet transactions to specific user behaviors recorded across various digital platforms. When harnessed correctly, these data points can be effectively utilized to evaluate the risk profiles of individuals and MSMEs alike.
Traditionally, financial institutions have relied heavily on debt repayment history, formal bank accounts, and established credit bureau files to determine whether a potential borrower is creditworthy. However, accelerated digitalization and rapid advancements in data analytics and machine learning have unlocked new horizons. Alternative credit scoring is fundamentally built upon non-traditional information that provides deep insights into a borrower’s true capacity and psychological propensity to repay loans. Within these modern frameworks, everything from telecom and utility payment histories to digital footprints and mobile data can be leveraged to establish reliable creditworthiness.
Banks operating within Cambodia are increasingly looking toward these alternative data sources as a viable mechanism for serving populations that have long been underserved by traditional banking models.
Mr. Mach Chan, CEO of Phillip Bank in Cambodia, points out that financial data within the country remains heavily fragmented and scattered across multiple distinct organizations and institutions. Because a large segment of the population does not hold formal loans with financial institutions, predicting their repayment capacity has historically presented a major challenge.
According to Mr. Chan, if institutions like Phillip Bank can seamlessly access and analyze aggregated alternative data, they can gain a much clearer understanding of a borrower’s creditworthiness based on social and behavioral indicators, spending patterns, and everyday habits. This comprehensive approach allows banks to form a much more holistic picture of an individual’s true risk profile. Consequently, lenders gain the opportunity to offer cheaper, more accessible loans to lower-risk customers, regardless of whether they were previously banked. Furthermore, because many small and medium-sized enterprises in Cambodia remain informally registered, lending to them has traditionally been fraught with risk. If financial institutions can safely access the payment data of these MSMEs, the wider industry will gain the confidence needed to properly support their operational and expansion needs.
Across the broader Southeast Asian region, governments, commercial banks, and key industry stakeholders are displaying a heightened interest in the capabilities of alternative data. The tool is increasingly viewed as an essential mechanism for expanding both the scope and accessibility of modern financial services.
A comprehensive, Southeast Asia-focused report published by the World Bank Group highlights four emerging data types born from the digital ecosystem that can significantly aid credit decision-making: mobile operator and app-based data, digital payments, e-commerce records, and enterprise-tech business-performance data. Similarly, the Asian Development Bank has repeatedly underscored alternative data as a cornerstone for driving sustainable financial inclusion throughout Southeast Asia.
Regional neighbors are already taking concrete steps to institutionalize these practices. In December 2022, the National Credit Bureau of Thailand announced ambitious plans to launch a dedicated non-credit data centre. By consolidating alternative datasets—starting initially with utility payment data from electricity and water providers—into its existing database, the bureau aims to streamline lending practices.
In Indonesia, credit reporting agency Experian collaborated directly with a major telecommunications company to boost financial inclusion for underserved populations. By utilizing real-time, telco-backed data insights, the initiative successfully reduced risk profiles for lenders while empowering unbanked citizens. Meanwhile, in the Philippines, the Credit Information Centre has been actively working on progressive policy adjustments to enable authorized entities to combine traditional credit bureau records with alternative data, ultimately painting a complete picture of a borrower’s overall financial profile.
In the specific context of Cambodia, utility bill payments and telecommunication histories serve as vital reservoirs of alternative credit data. When paired with the nation’s rapid shift toward digitalization and the widespread adoption of digital payments, the potential to capture a massive array of alternative data points related to daily transactions and digital footprints is immense. Globally, these exact categories of data have proven to be foundational drivers of digital financial inclusion.
With the proliferation of digital financial service providers, innovative payment catalysts, and expanding e-commerce networks across Cambodia, vast quantities of alternative data are generated daily. Given this reality, industry experts stress the absolute necessity of establishing an organized, secure ecosystem designed to collect, process, and utilize this information effectively.
On the regulatory front, the National Bank of Cambodia took a decisive step forward by revising its prakas on credit reporting, granting Credit Bureau Cambodia the legal mandate to collect alternative data alongside traditional metrics. This regulatory evolution is designed to actively support financial institutions as they work to strengthen their internal credit risk assessment capabilities.
Established in 2012 with the backing of the National Bank of Cambodia, the Association of Banks in Cambodia, and other key sector stakeholders, Credit Bureau Cambodia was created to maintain a fair, transparent credit market that underpins the nation’s broader economic development. In the years since its inception, the bureau has evolved into the preeminent provider of financial intelligence within the country. Although its current operations primarily manage traditional data reported by member banks and financial institutions, CBC is actively preparing a comprehensive roadmap to collaborate across multiple national sectors. Its ultimate goal is to build an inclusive alternative credit data ecosystem that operates hand-in-hand with the traditional framework, yielding tangible social and economic benefits for the Cambodian population.
Gordon Peters, co-founder and CEO of fintech firm Boost—which utilizes popular social media platforms like Facebook and Telegram to facilitate financial access—notes that Cambodia holds a distinct strategic advantage. He suggests the country stands roughly a decade ahead of comparable emerging market economies precisely because of its existing credit bureau and progressive lending environment. He praises CBC for its exceptional work in collecting, collating, and sharing data concerning the financial lives of everyday consumers, describing the infrastructure as a massive unlock for the local economy.
For firms like Boost, CBC provides an underlying layer of institutional legitimacy and security that has greatly strengthened the broader financial sector, allowing innovative companies to effectively plug gaps in the ecosystem. Because banks and financial institutions harbor deep trust in CBC as the country’s primary financial data infrastructure, the prospect of expanding its operational capabilities to encompass a robust alternative credit reporting system is viewed as entirely feasible. Having already managed the credit history data of more than 7 million individuals and business entities, the bureau is well-positioned for this expansion.
Elaborating on this vision, Ms. Theany explains that CBC functions as a centralized data hub for the entire financial sector, pulling data directly from participating banks and financial institutions, storing it securely, and analyzing it to generate precise credit scores. While individual financial institutions maintain their own isolated data silos, CBC holds a comprehensive financial view of the entire sector. Armed with advanced data analytics, artificial intelligence, and machine learning capabilities, the bureau is uniquely situated to ingest alternative data from diverse outside sources. This allows financial institutions to accurately assess the profiles of unbanked populations—predominantly women and rural farmers—alongside informal small businesses, estimating their real-world incomes with unprecedented precision. Consequently, lenders can offer appropriate credit and financial products even in the complete absence of formal financial footprints, traditional credit histories, or physical property guarantees.
Echoing these sentiments, Mr. Chan suggests that CBC could easily spearhead the aggregation of payment, telecommunication, and utility data, feeding these diverse datasets directly into a prospective customer’s overarching credit score. Pointing to the National Bank of Cambodia’s Bakong payment system as a major technological enabler that has spurred the rapid digitization of payments over recent years, he argues that payment data is just as critical as borrowing and repayment history and should be prioritized accordingly. Furthermore, he notes that establishing data-sharing connections with the General Department of Taxation would provide banks with invaluable assets regarding SME performance, ultimately enabling cleaner loans and stimulating wider economic activity.
At present, CBC administers the K-Score, an algorithmic credit score that utilizes machine-learning algorithms to process massive datasets and generate reliable credit scores in the absence of traditional financial records. As the sole industry-level credit score available in Cambodia, it was first introduced in 2015 and underwent a major algorithmic overhaul in 2020 to keep pace with a rapidly evolving market landscape. Today, the K-Score is accessible to all member financial institutions and is made directly available to individual consumers via CBC’s dedicated mobile application.
A 2023 study published in the Asian Journal of Law and Science highlights that algorithmic credit scoring serves as the vanguard of the global financial inclusion campaign, directly targeting unbanked and underbanked citizens to integrate them into formal financial markets and deliver affordable services, including credit, at fair prices. The study outlines the extensive benefits that alternative scoring tools bring to individuals across Southeast Asia who traditionally lack access to standard banking facilities.
Within the Cambodian framework, Credit Bureau Cambodia is exceptionally well-positioned to lead the charge in adopting these advanced methodologies. To successfully interpret the massive influx of datasets generated by widespread digitalization, CBC deploys sophisticated analytical tools. Machine learning algorithms and artificial intelligence mechanisms allow the organization to evaluate data at a scale that was previously unattainable. Regularly updated risk analysis profiles and dynamic loan portfolios represent just a few of the practical applications of these technologies. Ultimately, however, it is CBC’s extensive operational experience and its standing as the nation’s premier institution for financial data management that provide the most compelling argument for the widespread adoption of alternative data schemes throughout the country.
As Cambodia enters its second decade of formal credit reporting, CBC CEO Oeur Sothearoath emphasizes the bureau’s firm commitment to acting as a trusted national infrastructure element. The organization aims to provide reliable alternative credit data to strengthen risk assessment capabilities across its network of more than 190 member financial institutions, while simultaneously expanding access to credit for new-to-credit consumer segments. He notes that the bureau remains fully open to forging collaborations with alternative data providers—including telecommunication firms, utility providers, and payment service companies—to harness vital information absent from traditional credit reports and help integrate more Cambodians into the mainstream financial ecosystem.
As CBC leverages its firmly established presence within the financial sector, a growing cohort of local innovators continues to work alongside the agency to build out and refine the nation’s emerging alternative data ecosystem.
