Can UK Lenders Copy SBI's UPI Data Model to Fund Small Firms?

India's State Bank of India has announced it will lend to small businesses using UPI transaction data instead of requiring formal GST tax registration. It sounds like a distant policy shift, but it maps almost perfectly onto a debate UK lenders are already having: should a small firm's Open Banking transaction history count more than its filing history when deciding who gets funded?

What is the Concept

SBI is replacing a paperwork gate, GST registration, with a behavioural signal: consistent, verifiable payment activity captured through India's UPI network. Translated into a UK context, this is cash-flow-based underwriting through Open Banking, where a lender reads a business's actual current account and card transaction data rather than relying purely on Companies House filing history, VAT registration status, or years of audited accounts.

The contrarian insight is that formal registration status was never really a proxy for creditworthiness in the first place. It was a proxy for administrative visibility to the lender. A sole trader in Manchester turning over £8,000 a month through card payments but below the VAT threshold and only recently registered at Companies House can be a stronger credit risk than the paperwork alone suggests.

Why It Matters Now (2025–2026 Context)

UK small business lending has tightened as high street banks pull back from unsecured lending to younger firms, pushing more sole traders and micro-businesses in London, Birmingham, and Leeds toward fintech lenders. At the same time, the UK's mature Open Banking infrastructure, built ahead of most other markets under the CMA's Open Banking mandate, means UK lenders already have the data rails SBI is only now building in India.

This is the gap SBI is closing that most UK lenders have been slow to exploit despite having better infrastructure for it. A café in Bristol trading well through its card machine but only eight months old on paper is exactly the kind of business Open Banking-based underwriting was built to price fairly, yet many high street lenders still default to rejecting it on time-in-business alone.

How AI Is Changing This

Machine learning models can now pull months of Open Banking transaction data and produce a real-time risk score, something a manual underwriter reviewing accounts and VAT returns could never match for speed or consistency. This is what makes Open Banking lending commercially viable at scale: AI converts messy, high-volume transaction data into a usable credit signal cheaper and faster than document-based underwriting.

The named framework worth adopting here is the 'Transaction-to-Trust Pipeline': pull Open Banking data across every account a business uses, normalise it into one cash-flow signal, then score it against outcomes from similar UK small firms rather than a generic credit bureau model. Lenders that build this pipeline in-house, instead of buying a single bureau score, get sharper pricing and a genuine data moat competitors cannot easily copy.

Real-World Examples

Tide, iwoca, and Funding Circle already lend substantially on transaction and Open Banking data rather than relying solely on traditional credit files, approving UK small firms in hours based on real cash flow. Starling Bank's business lending arm uses similar signals for its own current account holders. SBI's UPI move is the same playbook applied at state-bank scale in a market where digital payments have gone almost fully mainstream.

The founder mistake UK business owners make is treating these Open Banking-led lenders as a fallback option after a high street bank says no. In practice they are often faster and better priced for younger or thinly-documented firms precisely because they skip the paperwork bottleneck that sinks traditional bank applications.

Practical Insights / Actions

UK small business owners without a long trading history should consolidate transactions onto as few accounts and card processors as possible, ideally one primary business current account and one main payment provider, rather than fragmenting sales across several tools. A clean, concentrated transaction history is exactly what Open Banking underwriting models reward, and it is something a founder can control from day one.

The hidden opportunity for UK high street banks is competitive: SBI's move proves that even large, conservative institutions will underwrite off transaction data at national scale. A UK bank that fully commits to Open Banking-based small business lending, rather than treating it as a side product, can win back the younger firms it has been steadily losing to challenger lenders.

Future Outlook

Expect more UK high street banks to expand Open Banking-based lending products through 2026 as core banking platforms add native support for real-time transaction underwriting, encouraged further by the FCA's continued push on Open Finance. SBI's transaction-based model, if it scales successfully in India, will strengthen the case for UK regulators and lenders to treat transaction data as a first-class underwriting input rather than a supplementary check.

The strong opinion worth stating plainly: requiring two to three years of filed accounts to assess a small business loan is going to look outdated within a few years. Transaction data is a more current and honest read of business health, and UK lenders that lean on filing history alone will keep losing younger, digitally-native firms to challenger banks that already use Open Banking properly.

Conclusion

SBI's decision to lend against UPI transaction data instead of GST paperwork is a preview of where UK small business lending should be heading, using Open Banking data the UK already has in place but many lenders still under-use. Business owners should tidy up their transaction footprint now, and lenders should build the pipelines to price off it properly. RP SoftTech helps small firms and lenders build the automation and data infrastructure needed to compete in this shift toward cash-flow-based lending decisions.