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Neobank diary: Data is everything

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Neobanks in Southeast Asia rival traditional banks with unique digital propositions built on vast amounts of customer data

Micro, small and medium sized businesses are the backbone of many Southeast Asian economies. In particular, Indonesia and the Philippines have more small businesses than most of their regional counterparts and yet, only 40 percent can access formal financial credit. Traditional banks have failed to close the SMB funding gap, leaving this segment majorly underserved.
The risk of SMBs falling outside of the digital banking system could worsen with the current climate of the Covid-19 pandemic. Businesses face the challenge of solving their liquidity problems for an unknown period, while banks will be limiting their risk appetite—and the impact could be millions of SMBs coming out of the crisis unbanked.

However, a wave of new fintechs, neobanks and even telecom operators are creating their own digital lending systems to better serve SMBs. But how can they ensure they overcome the existing challenges? And with so many players contending for banking licenses, who will win the race to support SMB lending?

Data is key to build trust
Small businesses in Southeast Asia face the same struggle when accessing credit: it is crucial for them to have a credit history to prove their creditworthiness. It’s a vicious cycle. Financial institutions are cautious and have strict risk policies which do not match the reality and needs of this vibrant but potentially underserved sector.

Data is the missing link. Traditionally, SMBs would need to provide a multitude of data for the bank to score their creditworthiness and underwrite a loan—but this is often not available in the same way as it is for larger businesses.

Recognising this challenge, new entrants into the market have experimented with alternative ways of scoring businesses using different types of data. In Southeast Asia, Mobile Network Operators (MNOs) have access to vast amounts of data on customers compared to banks. Alternative data such as phone airtime consumption, bill payments and other customer behaviours are being used where traditional credit scoring data points are not available.
Other players are similarly shifting toward community or behaviour-based data to assess businesses using the data that is available. Advancements in data science and machine learning are giving new players a predictive power to assess the ability to repay a loan.
Neobanks reinvent SMB lending
Among those looking to overhaul current SMB lending practices are neobanks. Typically birthed out of the idea of challenging the current processes of the incumbents, neobanks are not bounded by legacy systems, or burdened by branch networks. New neobanks like TONIK in the Philippines boast lower operating costs than the incumbents, meaning they can generally offer lower rates on business loans.
Business owners are open to a purely digital proposition. However, it is simply not enough to provide digital channels to access financial services. Similarly, neobanks will need to find creative ways to assess businesses looking for a loan.

In addition to neobanks entering the Asian market, there are several non-banks looking to reinvent themselves in this sector. Many are seeking to acquire a digital banking license including Grab in Singapore and Gojek in Indonesia increasing competitiveness; both companies have started out as ride-hailing service providers in their respective markets.

With that, both of them have recognised the opportunity and are now repositioning themselves as neobanks to start provisioning loans to underserved businesses. Once again, the common factor here is data. Grab and Gojek already have large volumes of data on their customers and are using that knowledge to effectively boost lending to small businesses.

Local market offers meaningful insights
Understanding the intricacies of the local market is essential if neobanks and other new players are to get SMB lending right. They need to look at what factors make most sense when underwriting a small business loan. They need to sync with what data is available and the likelihood of the repayment based on the local circumstances.

Where traditional banks have gone wrong is mandating small businesses to comply with pre-existing policies and rigid systems. New players must understand the challenge first and then build a solution. They must consider many alternative models and data sources if they hope to meet the needs of small businesses across Southeast Asia. After all, neobanks have made a great start, but the race is far from over—and it requires them to build from a true understanding of the local market.

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