Simultaneously, business lending has become a distribution, data and automation play, which requires a revolution rather than evolution of established lending approaches. How can lenders evolve to profitably lend to SMEs in this new era?
Key trends shaping business lending in 2024
Over the past decade, SME digital lending has significantly evolved within lending business models, marked by three major phases of innovation. Initially, Fintech lenders created a vastly more efficient playbook for originating small business loans. Distribution was done cheaply via online platforms or marketplaces and applicants were serviced efficiently by utilising data-driven risk models and eligibility (pre-)decisioning . More recently, embedded lending by non-financial platforms has streamlined the underwriting process, making it more efficient by utilizing proprietary data for financial decisions. Currently, the industry sees a diversification into three business model innovations, reflecting a strategic shift towards efficiency and customer-centric solutions in small business financing:
- Fully digital lender: continuous optimization of the fintech lending model
- Orchestrator: utilizing composable banking to orchestrate a combination of own and 3rd party lending products
- Lending-as-a-Service: The “Stripe for SME lending”
While it’s easy to draw up new lending business models from scratch, in reality most lenders are already active in the market and are battling their own unique challenges. Most business model transformations start from very unique point of departures and their progression is often hampered by variables such as cost of capital, legacy technology or tech debt, which can decelerate business model shifts. Yet, all things being equal, we believe the three outlined core SME lending business models will outperform any other less differentiated competitor.
Digital transformation in lending
A recurring theme is the rise of data-driven lending solutions. In the report, we outline three key principles that have an outsized impact on lending practices: automation, data-driven decision-making and tailored solutions. Automating lending journeys and back-office workflows to eliminate manual processes and improve efficiency is a key success factor to lift unit economics. Data-driven strategies are just as pivotal, as APIs allow to integrate both in-house and external information into credit decision infrastructures, enabling real-time, accurate credit assessments. Lastly, next-generation lenders will go all-in on customized lending solutions that can fully address the specific needs of their target SME segments. A key part of offering tailored lending solutions is the agile adaption of credit policies by product or sector teams without overtaxing internal engineering resources.