by Lenders Expand Digital Footprint by Partnering with Third Parties
As consumers spend more time online and interacting digitally, embedded lending provides a seamless way for them to access financing options directly within the user experience of other applications and services. By partnering with third parties, lenders can extend their reach and make the borrowing process more convenient for customers.
Expanding Access to Credit
One of the primary benefits of Embedded Lending is the ability to provide financing options to more consumers. By integrating lending capabilities into the workflows of other businesses, lenders gain access to those companies’ existing user bases. This allows them to underwrite and approve loans for potential borrowers who may not have otherwise applied through a standalone online loan application. Embedded financial products remove friction from the borrowing process by bringing credit right to the customer’s point of need within the context of another service.
For example, many merchants and marketplaces now offer installment payment options at checkout. This grants approved customers the ability to split the cost of purchases over multiple billing periods. Rather than requiring a separate loan application, the financing decision and loan origination occur seamlessly as part of the normal shopping experience. Consumers benefit from increased purchasing power without much extra effort required on their part.
Driving Growth through Partnerships
RealTimeDecisionsFrom the lenders’ perspective, partnerships that facilitate it allow for expanded customer acquisition without much additional marketing spend. Since the loan approval happens behind the scenes during a transaction on another site or through another company’s mobile app, the lending institution’s brand is not top of mind for the borrower. However, successful loan performance still builds the lender’s portfolio size and generates interest income over time.
Many lending partnerships also include revenue sharing arrangements. The host company is compensated for each financed transaction on their platform. These types of models create a true win-win, as both the lender and their integration partner benefit financially from the Embedded Lending experience. The hosted company gains a new monetization stream without having to develop their own lending capabilities from scratch.
A great example of a company that pioneered embedded lending through strategic partnerships is Affirm. Founded in 2012, Affirm works with thousands of merchants across various industries to offer installment loans at checkout. Some of their largest partnerships include Amazon, Walmart, Peloton, and Expedia.
By integrating Affirms “Pay in 4” and other payment directly on these merchants’ sites and apps, customers are presented financing as a native payment option along with credit cards and debit. Approved Affirm users can split the total cost of purchases between $50-$1500 over 3 to 24 months with no late or hidden fees. This creates opportunities to convert more browsers into buyers by making big-ticket items more affordable through pay-over-time budgeting.
For merchants, Affirm payment drives higher conversion rates and larger basket sizes compared to traditional credit card transactions alone. Affirm also handles all account servicing and debt collection, removing the risk and administrative burden from the merchant. This full-service embedded financing platform has been tremendously successful, facilitating over $5 billion in transaction volume in 2020 alone according to the company’s financial reports.
Mitigating Risk through Automation
One challenge of embedded lending is the need to make rapid credit decisions without a traditional loan application. To mitigate risk, lenders rely heavily on automation powered by alternative data sources and machine learning models. Advanced underwriting systems can analyze thousands of data points, from traditional credit reports to new metrics like banking transaction history and device/behavioral data, to quickly gauge a prospective borrower’s creditworthiness.
Automatic decisioning also allows lenders the flexibility to integrate tighter controls over loan amounts, terms, and applicant eligibility criteria based on real-time performance of their portfolios. Partnerships with companies that facilitate embedded lending demand quick underwriting without much back-and-forth. Advanced systems help keep approval rates high while balancing risks appropriately through automation.
Regulatory Considerations
As embedded financial products continue growing in popularity, regulatory frameworks are evolving to establish clearer guardrails. All players in the ecosystem must comply with applicable lending laws and federal consumer protection regulations regarding disclosures, data privacy, and fair/responsible underwriting practices. Lenders also need robust fraud and identity theft prevention along with programs to avoid harming financially vulnerable populations.
Striking the right balance between facilitating access to credit while enforcing sensible guardrails remains an ongoing effort by policymakers. Additional guidance around subjects like electronic disclosures, lead generation, and oversight of third-party lending partnerships will be important to establish appropriate standards as embedded finance becomes more widespread. Responsible innovation in this area can expand opportunities equitably when all stakeholders prioritize legal compliance and consumer well-being.
Embedded lending opens the door for further digitization and optimization of the consumer credit experience. By integrating directly with other applications and services, lenders gain new customer touchpoints without heavy lifting. Partners too can expand their value propositions through the addition of financial services. When built upon a foundation of cooperation, innovation in this sphere benefits businesses as well as consumers through increased choice and convenience if executed responsibly and lawfully.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
