Since 2018, open banking in credit risk has transformed UK lending. With 16 million+ active users, API success rates over 98%, and 53% annual payment growth in 2025, the infrastructure is proven.
Yet, adoption remains uneven: niche entrants are using it for core decisions, while many large lenders treat it as a bolt-on. With BNPL now under affordability scope and the FCA sharpening expectations on financial distress, lenders ignoring this risk being left behind as Open Finance expands access to pensions, investments, and tax data.
Key takeaways
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Why the adoption split happened in open banking credit risk
Structural issues tend to be the number one reason large lenders have been slower to adopt open banking in their credit decisioning. Here’s why:
- Legacy IT systems. Larger lenders tend to be tied into more complex infrastructure, which makes it more difficult and more expensive to implement real-time, unstructured open banking data.
- Data volume. They already hold a large amount of existing data on their customers, which can make the benefits-versus-effort calculation less compelling compared to a niche lender or a new-to-market entrant with limited customer history to draw on.
- Regulatory comfort. Credit scorecards are a predictable and established process that can be explained to the regulator. Incorporating open banking data can feel more like an unvalidated approach, particularly for teams whose model governance is built around bureau data and internal behavioural history.
Of course, consent adds another problem. Open banking requires customers to actively agree to their data being used, and some are hesitant, particularly those who already view themselves as having strong credit profiles and see little personal benefit in sharing. In fact, research published in 2026 found risk aversion to be the dominant barrier to open banking adoption among UK consumers, driven by privacy and security concerns.
Where open banking in credit risk changes the decision
Open banking tends to be used alongside the existing scorecard process (instead of replacing it). Of course, the regulatory safety of going through a typical scorecard route, using bureau and internal data in an explainable, validated way, is super important. Bureau data also contains information that open banking can’t provide, such as CCJ flags, bankruptcy markers, and the like.
Where open banking creates genuine decisioning value is in the population that falls between auto-accept and auto-decline.
As you’ll be aware, customers with thin files, erratic incomes, or limited credit histories frequently get rejected through the standard scorecard route and affordability assessment - usually because the data available to assess them is insufficient.
Open banking can be used to assess the transactional history of those individuals, verify their incomes, and understand their financial commitments, without requiring reams of payslips and bank statements. Used well, it converts legitimate declines into approvals and extends credit access to people who are creditworthy but invisible to a bureau-only model.
That is also where affordability comes into focus. With BNPL now brought into scope for affordability assessment and the FCA's broader tightening of affordability rules, open banking provides transactional data that removes the requirement for customers to manually gather and submit historic financial documents. Third parties that clean and categorise this data, grouping spending into income, bills, and discretionary categories, make the process significantly easier for lenders to process than manually reviewing bank statements line by line. The effort required from the customer, once they have given consent, is minimal.
Worth noting here, too: With Open Finance being rolled out, it goes beyond open banking in ways that are particularly relevant to affordability assessment. It gives access to banking data such as current accounts, transaction data and savings, and also opens up views of wider financial data including pensions, investments and tax information. For business lending specifically, Open Finance can give direct access to a business's accounting platforms, real-time sales, and tax portals, providing a level of financial visibility that transactional banking data alone cannot match.
What’s required to embed open banking for credit risk?
When a lender decides to embed open banking data into its models and processes properly, there are some additional things that need consideration. This can be the difference between a failed and a successful project:
- Infrastructure. Particularly for larger lenders with legacy systems, integration is complex and costly.
- Model retraining. Incorporating open banking data requires revalidation and, for IRB-approved firms, regulatory approval, which is a significant body of work.
- Consent withdrawal planning. If a customer withdraws consent after open banking data has been incorporated into their model, there needs to be a fallback to a model that does not require it.
- Scorecard monitoring. Monitoring scorecards that include open banking data requires a specific approach to understand whether that data is providing genuine lift, and what the cost-versus-benefit position is.
- Real-time data. If real-time open banking data is being used rather than a snapshot at application, the infrastructure considerations become more complex again.
Overall, it is much harder to disaggregate open banking from a model once it is embedded, whether due to technical issues, withdrawn consent, or a determination that the data is providing insufficient uplift to justify the cost. That is something lenders need to plan for before they embed, and build in from the outset.
The data quality reality
Something else worth noting. Transaction data is fed in volume and in a format that is not ideally structured for lenders. There is a lot of it, and it is formatted for banks, not for the lender's decisioning needs.
However, there is good news here. Third parties acting as intermediaries between banks and lenders can cleanse, structure, and categorise that data, grouping transactions by income, bills, and discretionary spend, which is particularly valuable for smaller lenders who do not have the resources to do this in-house. In these partnerships, transaction categorisation has improved substantially, though significant differences still exist between how different Account Information Service Providers classify the same transactions.
Ultimately, lenders building automated decision rules around categorised data need to account for those inconsistencies.
Open banking in credit risk beyond the application stage
One thing I’d like to focus on is the pay-off of open banking. Yes, it can be difficult to embed if infrastructure is messy. But, it can be extremely beneficial too.
Open banking goes beyond replacing payslips and bank statements. Its value is much, much greater when used across the customer lifecycle. Which also happens to be where many lenders are underusing it most significantly.
For instance, Open banking enables real-time monitoring of financial behaviour instead of relying on delayed monthly bureau data updates. And it is particularly valuable for identifying pre-delinquency customers, those showing early signs of financial difficulty before a missed payment occurs:
- The FCA has previously found that many firms missed opportunities to identify customers showing early signs of financial distress and offer appropriate support before their situation worsened.
- Early identification is critical because financial circumstances can change quickly, and even a single missed payment can escalate into persistent arrears or default, with significant impacts on customers' financial and emotional wellbeing.
- Early warning signs are often absent from traditional repayment data, and predicting who is likely to miss a future payment is difficult.
- Open banking provides a more up-to-date and detailed view of income, spending, and financial commitments, which allows lenders to detect emerging stress earlier and intervene before issues escalate. An increase in spending habits, or a sudden drop in income, can allow lenders to react to these changes, reach out to the customer, and provide support.
Where open banking in credit risk goes next
Adoption will continue increasing as open banking enables faster, more streamlined credit decisioning and removes the need to manually collect and verify documents on both sides. The third-party services that categorise and structure open banking data reduce manual effort and improve efficiency further. Used correctly, it helps identify early warning signs and pre-delinquency, which is important for managing customers' situations and ensuring good outcomes.
There is also a fraud benefit worth flagging. Paperwork can be edited; open banking data arrives directly through an API, making it far harder to manipulate. For lenders still using manual document submission, the fraud risk reduction from moving to open banking verification is a meaningful secondary benefit.
And as customers become more aware and educated about open banking, they will likely become less apprehensive about consenting to it, which should improve consent rates further.
The bigger development on the horizon is Open Finance, underpinned by the Data (Use and Access) Act 2025. Where open banking provides access to current account and transaction data, Open Finance extends that further:
- For consumer lending: pensions, investments, savings, and tax information, giving a significantly fuller view of a borrower's financial position.
- For business lending: direct access to accounting platforms, real-time sales data, and tax portals, going well beyond what transactional banking data alone can provide.
The lenders who have built the infrastructure and governance to use open banking data well will be best placed to extend into Open Finance when that data becomes available. Those still treating open banking as an optional bolt-on will find a more substantial distance to close.
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