Today, embedded lending in the UK is entering a new phase. Lenders now use real-time affordability checks powered by Open Banking data to make credit decisions instantly within third-party digital platforms. For advanced lenders, this is more than innovation—it’s a strategic advantage in underwriting accuracy, regulatory compliance, operational efficiency, and risk mitigation.

Why 2025 Is a Breakthrough Year

Open Banking adoption is at an all-time high, 13.3 million UK consumers and small businesses actively using Open Banking, about 20% of online banking users, experiencing approximately 70% year-on-year growth. There are 145 live Third-Party Providers (TPPs) with open banking propositions, including 22 focused on lending and credit services.

These metrics signal a mature and scalable ecosystem: Open Banking is no longer experimental, it’s embedded, and lenders using it for affordability are gaining ground fast.

What Real‑Time Affordability Checks Entail

Real-time checks refer to live, consent-based retrieval and analysis of bank account transaction data, income deposits, bills, and outgoings while a borrower is still actively applying. This enables:

• Immediate income verification
• Automated categorisation of expenses
• Accurate calculation of disposable income
• Consent-driven, auditable logs compliant with FCA frameworks

SaaS companies like Pulse offer live AIS feeds and real-time dashboards with easy-to-integrate APIs supporting 99% UK bank coverage with no upfront setup cost.

Benefits for Embedded Lending Lenders

Precision Risk Grading

Traditional bureau scores lack granularity. Open Banking reveals actual cash flows. As per a working paper by the Federal Reserve Bank of Philadelphia, it was found that lenders denying applicants on bureau data alone experienced 70% more defaults than those leveraging transaction‑level and real-time insights.

One lender partner reported one-quarter of declined applicants had unflagged gambling expenses revealed only via transaction analytics.

Fuller Inclusion & Lower Loss Rates

Transaction-based models reduce default rates by ~22% compared to standard bureau-only underwriting, particularly for customers with thin or irregular credit profiles.

Pulse took things a step further with the creation of Einstein aiDeal, a solution that automates underwriting decisions for 90% of deals in under 60 seconds.
This enables lenders to process more applicants with greater accuracy and speed. Thus, lenders can responsibly extend credit to segments that are often excluded.

Straight Through Processing & Reduced Friction

Embedding checks into the user flow means loans can be approved and funded almost instantly. This integration eliminates manual uploads or form-based income verification, improving conversion and speeding decision to disbursement cycles.

Post Loan Monitoring & Dynamic Risk Scoring

Continual access (with consent) to transaction feeds supports accounts receivable insights, early warning signals for vulnerability, and dynamic risk scoring via ML models.

Pulse’s aiPredict for cash flow forecasting and DebtorIQ for accounts receivable management are ideal examples of how real-time data feeds enable users to leverage powerful automation and functionality.

Technical and Operational Challenges

Real-time affordability isn’t plug-and-play. Even in 2025, lenders face the following challenges:

• Data cleanliness issues from legacy systems and inconsistent categorisation
• Scalability constraints in API architecture, especially when balancing cloud vs on-prem deployment
• Regulatory and compliance complexity in embedded lending chains
• Fairness and bias risks: ML systems built on transaction data must avoid indirect discrimination

To succeed, lenders must invest in explainable AI, reliable Open Banking infrastructure, and clear consent and compliance processes.

Best Practices for UK Lenders

• Consent-first architectures are essential. Every data retrieval instance should include a time-stamped audit log aligned with GDPR and FCA guidelines.
• Feature engineering should focus on disposable income. Prioritising recurring deposits, fixed obligations, and accurate spending categorisation will support risk-adjusted lending.
• Adopt explainable AI models, not black-box ones. Declines must be auditable and transparent under relevant regulations.
• Consider hybrid deployments that combine cloud elasticity with on-prem reliability—especially if your embedded lending runs across multiple digital partners.
• Enable ongoing monitoring with consent. Detect financial stress early and support proactive engagement or dynamic pricing models.
• Start with embedded partnerships. Integrating with third-party digital ecosystems can expand your market reach. For example, integrating with Pulse’s Unified Lending Interface (ULI) can give lenders a massive competitive advantage. From automating loan origination and underwriting to automating the entire loan journey, lenders can scale up in terms of business volumes and revenue with one simple integration. To know more about Pulse’s ULI, book a demo today.

Strategic Implications

In 2025, real-time affordability checks are a critical enabler of modern, scalable lending. For UK lenders operating in embedded environments, the ability to evaluate a customer’s financial position instantly, using verified transaction data, offers both competitive and compliance-driven advantages.

With increasing scrutiny from the FCA and upcoming BNPL regulation, real-time checks are becoming a prerequisite for responsible lending. Lenders that adopt Open Banking-powered workflows can improve approval precision, reduce default rates, and serve previously inaccessible market segments, all while maintaining audit-ready processes.

Platforms like Pulse have significantly lowered the barrier to entry for real-time decisioning, offering lenders the ability to embed, test, and scale affordability solutions with minimal integration friction. This opens the door to strategic benefits: faster time to market, product innovation, lower risk exposure, and embedded lending readiness across multiple digital touchpoints.

Falling behind in this area means not just missing out on opportunity, but also failing to meet future compliance standards or losing borrower trust in an increasingly competitive, transparency-driven lending landscape.

Conclusion

In the UK, real-time affordability checks are increasingly an important part of credit decisions. Adoption has gone beyond innovators and early adopters; mainstream lenders are already using transaction-level data to make lending more accurate, inclusive, and compliant.
As embedded finance becomes the most popular way to distribute funds, lenders that include real-time affordability from the start will set the standard for product speed, portfolio quality, and compliance.

Lenders can embed affordability checks and lending solutions directly into their origination, underwriting, and servicing workflows by engaging with data-infrastructure providers like Pulse. This lets them make proactive, data-rich decisions on a large scale and transform the lending process. People who think ahead will be best able to deal with changes in regulations and do better in the next era of digital lending.