Openpay Group, which operates in the buy now, pay later (BNPL) space, is looking to raise $20 million in new funds, according to a Friday (May 20) Financial Review report.
The report noted that about 85% of the book was covered through cornerstone pre-commitments pre-launch. Some of the early takers were investment and advice firms Meydan Group and Alteris Financial, as well as Hong Kong conglomerate Chow Tai Fook.
Investors were reportedly told the additional funding would help Openpay’s Australia and New Zealand business become profitable by the 2023 financial year. The company is also looking at getting a capital partner to expand in the U.S.
BNPL has seen a surge in popularity since the pandemic, especially among younger buyers trying to save money amid the various economic problems of the past several years. BNPL services have also been integrated with numerous facets of retail and various kinds of merchants.
To that end, Openpay made a move earlier this year to expand into the auto sector, adding BNPL options for franchised auto dealerships so customers in need of “major car repairs” can access the service.
Read more: Payments Firm Opy Offers Financing for Car Repairs
Brian Shniderman, Opy U.S. CEO, said the company’s plan was created after “extensive discussions with many auto dealerships,” and the company wanted to offer services for various needs and preferences.
According to the report, Openpay research has shown that customers spend an average of over $2,000 on car repairs, helping to fuel an increasingly expensive auto repairs industry.
Additionally, PYMNTS wrote last August that Openpay had teamed with Kyriba, a cloud-based finance and IT solution firm, to add the OpyPro Software-as-a-Service firm to help B2B payments for companies.
The companies integrated OpyPro with Kyriba’s Enterprise Liquidity Management platform and working capital solutions, helping to digitize and automate customer onboarding. The solution was designed to curb manual tasks and allow access to transaction, invoice and statement data.