Small businesses are the backbone of Southeast Asia’s economy, but many struggle to secure working capital loans because they don’t have traditional credit records or collateral, say the founders of Funding Societies. The fintech, which claims to be the region’s largest SME digital financing platform, uses alternative forms of credit scoring and has disbursed more than $2 billion in financing to MSMEs since it launched in 2015. Today, Funding Societies announced it has raised $144 million in an oversubscribed Series C+ equity round led by SoftBank Vision Fund 2, with participation from new investors like VNG Corporation, Rapyd Ventures, EDBI, Indies Capital, K3 Ventures and Ascend Vietnam.
It also received $150 million in debt lines from institutional investors, some of which have been drawn down since last year.
The company’s previous round was a $45 million Series C raised between 2020 and 2021. Part of its newest funding, or $16 million, will be distributed to former and existing employees through its stock option plan in the form of share buybacks.
The company was founded in 2015 by Kelvin Teo and Reynold Wijaya after they met in Harvard Business School. It is now licensed and registered in Singapore, Indonesia (where it is known as Modalku), Malaysia and Thailand. It recently began operating in Vietnam and will use part of its Series C+ to enter the Philippines.
The platform disburses online loans ranging in size from $500 to $1.5 million. Since its launch, it has disbursed more than $2 billion in business financing to MSMEs through more than 4.9 million loan transactions. Funding Societies’ customers range in size from neighborhood stores and e-commerce vendors to medium-sized enterprises, like fast-growth startups and established corporations that want access to faster revenue-based financing than bank loans, which usually take about two to three months to disburse, Teo tells TechCrunch.
A recent impact study calculated using methodology by the Asian Development Bank showed that Funding Societies-backed MSMEs contributed $3.6 billion in GDP, and 350,000 jobs.
By covering a wide range of businesses, Teo says Funding Societies has better customer acquisition costs and loan-to-value ratios. It also accumulates data faster to train its data-scoring models, which draw from traditional and alternative sources of data. Traditional sources include bank statements and credit bureau information if available, while alternatives ones can include transaction information, online reviews and supply chain data flow.
One of Funding Societies’ advantages is that some of its data sources are proprietary, while they have exclusive rights to others through partnerships. This gives the startup an edge over newer players, Teo says, as well as the amount of loan repayment data that Funding Societies has collected since its launch. He added Funding Societies’ loan default rate is between 1% to 2%, even through the COVID-19 pandemic, which is why it was able to receive debt lines from so many institutions.
Funding Societies’ interest rates are generally higher than banks, but lower or equal to credit cards — in fact, it offers a credit card with a debit line to serve as a substitute for corporate cards. It also partners with businesses, including e-commerce platforms like Shopee and Bukalapak, bookkeeping app BukuWarung, fintech Alterra and agritech platform Tanihub that offer access to working capital loans to their SME customers.
Teo and Wijaya say Funding Societies’ main competitors are not banks. Instead, Teo says many of its customers were relying on loans from friends or families, their savings and personal credit cards to finance their businesses. “The opportunity is huge because it’s a $300 billion U.S. dollar quality financing gap,” he says.
In a prepared statement, SoftBank Investment Advisers managing partner Greg Moon said, “SMEs across Southeast Asia have historically struggled to access institutional finance and instead been forced to mainly rely on personal funding to support growth. Funding Societies is establishing a bridge for these companies to access more sustainable and cheaper financing by building unique data sets on their performance and using AI-led technology to assess their creditworthiness more effectively than traditional models.”
