A recent study conducted at the Chalmers University of Technology analysed the emerging field of embedded lending and derived five key success factors, which are briefly presented in this article.

Ross Republic’s partner Adrian Klee was lately interviewed by Casper Svensson and Matthias Ydström, who researched the phenomenon of embedded lending as part of their Master Thesis at the Swedish Chalmers University of Technology. The research part utilised a qualitative, inductive research approach with the goal to uncover early applications of embedded lending, i.e. debt financing services that are tightly integrated into third party (non-financial) propositions. Additionally, the thesis revealed the key characteristics and success factors of these early use cases.

Five success factors of embedded lending

Digital interaction points: Based on the expert interviews with both embedded lending players and industry experts, the study concluded that the prerequisite for embedding financing solutions is a digitally-enabled end-customer journey. As the whole point of embedded lending is to provide financing right at the point of need, i.e. directly when and where the customer needs it most, as well as with the right and contextually relevant offer, there needs to be a minimum level readily available data for underwriting as well as digital interface for the promotion of the financing offer. A common example is invoice financing that is prompted directly in an accounting SaaS tool.

Availability of general underwriting data: Fundamentally, embedded lending can be implemented wherever a customer generates data that can be plugged into an underwriting engine, such as  transaction data, information about assets or revenues. Open banking was often mentioned to be a game changer in this regard, as the regulation creates a level playing field by enabling banks and third parties to aggregate data from any other bank.

Availability of unique underwriting data: Due to digitalisation, modern lenders have access to a plethora of alternative data that can be utilised to radically enhance traditional underwriting data, such as customer loyalty, marketing data (return on ad spend), revenue growth per channel, etc. Again, one example is to plug into customers’ accounting systems like Xero to review accounts payables and receivables in real-time.

Instant processing: A seamless financing journey turned out to be a critical success factor, specifically the speed of the payout as a factor to increase customer satisfaction. As soon as data for underwriting has been collected, the speed of processing is not determined by the application itself, but rather by the capabilities of the underwriter.

“You have to have instant decision, you have to use the data that is presented to you, you have to keep the customer engaged there and then, and in order to
create an embedded financial service product you have to do all of that on a single platform” – Roger Vincent (Managing Director UK&I  at Trade Ledger)

Brand trust: Customers that are exposed to embedded lending propositions need to trust the brand that provides the lending service: “Adrian Klee drew upon experience from a research project he was involved in where customers were exposed to an unknown fintech brand in an embedded lending customer journey. When customers did not recognize the brand, they felt confusion and distrust. Klee argued that such issues with trust could be overcome by branding embedded lending products with a well-known and trusted brand. Klee exemplified Klarna as an embedded lending company that has managed to build recognition and trust among customers, which platform partners that integrate Klarna’s embedded lending solution could benefit from.”

You can download the embedded finance research paper here.