AI-Based Financing for Singapore SMEs
The use of AI in banking has been a boon for the industry, particularly in risk management. From identifying fraudulent activity to predicting customer financial stress, AI has helped banks in various ways.
Recently, DBS launched DBS Quick Finance, one of the first in Singapore to use it for working capital purposes. In addition, the bank will reach out to customers through the DBS IDEAL platform to offer instant financing of up to SGD300,000 to small and medium enterprises (SMEs).
In a press release, DBS announced that it designed the solution to help SMEs tide over post-pandemic challenges, from an impending GST hike to rising interest rates.
Gene Wong, Singapore head for SME Banking (micro & small segment) at DBS, said that the bank is tapping on its "digital capabilities and advanced data analytics to pinpoint potential financial needs with greater precision." According to Wong, they want to be proactive and reach out before customer needs become urgent.
To avail of the financing, SMEs will have to share their day-to-day accounting transactional records with DBS for credit assessment purposes. The application process is AI-powered and can be completed in as fast as one minute, with approvals in one second and even instant disbursements.
Customers may pick between an overdraft, which can be used as needed, or a working capital loan that must be repaid monthly. They can apply from Xero's accounting software platform, which DBS said could benefit customers by offering "personalized credit terms and loan quantums derived from a deeper understanding of SMEs' transaction and business flow patterns."
"Having worked hand in glove with our micro and small businesses to wade through the unprecedented challenges of COVID-19, we are confident that business owners will remain resilient, and we will emerge stronger together," Wong added
DBS has been working with SMEs for years to help them manage their finances and risks. The bank uses artificial intelligence and machine learning models to identify SMEs in financial trouble early on so that they can offer advisory support and financing solutions before it's too late.
They attribute their success in identifying at-risk loans to these capabilities, which have helped them identify over 95% of non-performing SME loans at least three months before the businesses experience credit stress. Out of all identified at-risk borrowers, 80% were able to avert risk.
