Indonesia’s credit conundrum: Risks and opportunities in a fast-growing debt market

*This article is adapted from * The Business Times

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INDONESIA, South-east Asia’s largest economy, presents a paradox in its financial sector. Despite rapid economic growth and digital transformation, its credit system remains underdeveloped, leading to higher non-performing loan (NPL) risks and increased provision costs for banks.

Yet, rather than deterring investors, this landscape offers immense opportunities for fintech, embedded finance and alternative credit solutions. Understanding these risks and opportunities is crucial for those looking to tap into one of the world’s most dynamic financial markets.

The challenge: An underdeveloped credit system with high NPL risks

Indonesia’s banking sector has long struggled with structural inefficiencies in credit distribution. The country’s credit-to-GDP ratio remains at around 40 per cent, significantly lower than its regional peers, such as Malaysia and Singapore, where credit penetration exceeds 150 per cent, according to World Bank data. This is partly due to the country’s fragmented financial system, where many individuals and businesses remain outside the formal banking sector.

A key issue is the high proportion of NPLs. As of September 2024, Indonesia’s banking NPL ratio hovered around 2.21 per cent. This is an improvement from the year-ago number of 2.46 per cent, albeit with a lower credit growth rate. However, we need to pay attention to some major banks increasing their provision costs in the fourth quarter of 2024. According to Algoresearch, Bank Mandiri and Bank BRI both had a 100+ per cent increase year-on-year in their provision costs in Q4 of last year.

Coupled with the lack of reliable credit data, this forces banks to be conservative in lending, often requiring high collateral and extensive documentation.

The result? Many micro, small, and medium enterprises (MSMEs) and consumers turn to informal lending sources, which charge exorbitant interest rates and further exacerbate financial instability.

The opportunity: A market hungry for credit, where AI can be pivotal

Despite these challenges, Indonesia remains a high-potential market for financial services expansion. MSMEs contribute over 60 per cent to the gross domestic product but receive only around 20 per cent of total bank lending.

The demand for credit, particularly among businesses, is undeniable. Many small enterprises rely on loans for working capital, inventory purchases and business expansion. However, the traditional financial system’s inability to effectively assess risk means that fintech players have a unique opportunity to bridge this gap.

In this space, artificial intelligence (AI) is proving to be a game changer in risk assessment and credit scoring.

AI is revolutionising credit assessment by using alternative data to enable more accurate, real-time credit scoring. Traditional credit scoring relies heavily on formal banking history. AI-driven models, on the other hand, leverage a broader range of data.

Based on mobile phone usage, social media activity, and spending patterns, behavioral analytics can be incorporated to create a more holistic picture of an individual’s financial behaviour.

Additionally, e-commerce transactions, including purchase frequency, payment reliability and order volumes, can provide valuable insights into a customer’s spending habits and creditworthiness. Digital payment history, such as QR transactions, e-wallet top-ups and utility bill payments, can also be factored into credit-scoring models. For businesses, operational data like inventory turnover, supplier payments and cash flow trends can be analysed to assess creditworthiness.

By incorporating these alternative data sources, AI-powered models empower fintech companies to identify and serve high-potential borrowers whom traditional credit assessment methods might overlook due to a lack of formal financial history.

AI can also enhance fraud detection, risk mitigation and credit assessment. Advanced machine-learning algorithms analyse vast datasets to identify anomalous borrowing behaviour that could indicate fraud. Moreover, these algorithms can predict early signs of loan delinquency, allowing lenders to intervene proactively. Risk models can also be continuously improved using reinforcement learning techniques.

Financial institutions can maintain lower default rates and broaden financial inclusion to underserved populations by transitioning from manual credit monitoring to more automated processes. This shift can particularly benefit fintech companies and banks.

Embedded finance, platform-integrated lending

Embedded finance, the integration of financial services into non-financial platforms, has seen rapid growth due to Indonesia’s burgeoning digital economy.

Super apps like Gojek, Grab, and Shopee have successfully integrated lending solutions into their platforms. These apps leverage transaction data to provide credit to both merchants and consumers. Additionally, e-commerce platforms have embraced BNPL (Buy Now, Pay Later) services, granting millions of Indonesians access to financing for their daily purchases.

Furthermore, ride-hailing and delivery services utilise earnings data to extend microloans to drivers and couriers, thereby fostering a new level of financial inclusion. This model significantly reduces risk by leveraging real-time data instead of outdated credit bureau information, making it a viable approach for lending at scale. Financial institutions like Bank Sahabat Sampoerna forging a partnership with Xendit, and multifinance companies like Adira Finance collaborating with CarDekho SEA, are the two main examples of how this embedded finance mechanism is implemented.

Ripe for disruption

Indonesia’s credit market presents a clear challenge due to high NPLs, a lack of traditional credit data and regulatory uncertainties. The recent fraud cases also have not helped the case.

However, the sheer demand for credit, strong business fundamentals in financial services, combined with the rise of AI-powered credit scoring, alternative data-driven lending and embedded finance models makes this a market ripe for disruption. Investors who can identify scalable, technology-driven credit solutions will find themselves at the forefront of South-east Asia’s next major financial revolution.

For those willing to navigate the complexities, Indonesia’s financial services sector remains one of the most promising investment frontiers in the region.

The writer is executive director, Investment at Vertex Ventures South-east Asia and India

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