"SKT Launches 'Big Data-Based Innovative Finance' Supporting Small Businesses with 6 Months Future Sales Payment"

[Asia Economy Reporter Seulgina Jo] SK Telecom announced on the 25th that it will introduce new services, ‘Automatic Advance Payment’ and ‘Future Advance Payment,’ to the innovative financial service ‘11st E-commerce Factoring,’ in collaboration with 11st and Hyundai Capital.

Automatic Advance Payment is a service that automatically advances 80% of the sales amount of goods awaiting purchase confirmation every day once the seller completes the shipment of items purchased by customers on 11st. Any seller with monthly sales of over 300,000 KRW for two consecutive months can apply, and it is offered at an industry-low fee of 0.1% within a limit of 50 million KRW. The service is free for the first three months and automatically renews after a one-year contract. No additional fees are charged even if the customer’s purchase confirmation is delayed.

Additionally, Future Advance Payment analyzes up to six months of sales data from sellers and pays future sales in a lump sum. It offers same-day deposit upon online application within an industry-high limit of 70 million KRW. This service does not affect the seller’s personal credit score, allowing additional use while maintaining overdraft accounts or credit loans. The usage fee is approximately 0.46% per month.

These services are new offerings of ‘11st E-commerce Factoring,’ launched by SK Telecom after passing the Financial Services Commission’s regulatory sandbox in May last year. 11st E-commerce Factoring, which provides operating funds to small business owners using 11st, received strong responses by offering benefits such as increased loan limits and interest reduction to small business owners who were disadvantaged by traditional credit evaluations.

Jang Hongseong, Head of Advertising and Data at SK Telecom, said, “We expect these newly introduced services to be of great help to small business owners struggling due to COVID-19.”

Meanwhile, SK Telecom has also developed a model called ‘Seller Score’ that analyzes hundreds of non-financial data points?including ▲sales ▲settlements ▲order cancellations and returns history ▲buyer reviews ▲customer response information?from small and medium sellers who consented to data use, using machine learning technology to complement existing credit evaluation methods based on financial information.