Ask a GCC bank how well its digital lending is performing, and the answer will often come back in seconds — literally. Approval times have become the headline metric of the region’s lending race, with institutions competing to move borrowers from application to decision faster than ever. But according to Khaled Al Ahli, Middle East senior business executive and growth leader at Swiss digital-banking firm CREALOGIX, that scoreboard measures the wrong thing.
His argument is not that speed doesn’t matter — it does — but that a decision delivered in seconds has little value if it misjudges affordability, stores up credit risk, or can’t be explained to a customer or regulator. As AI takes on a larger role in credit decisions and regulators in the UAE and Saudi Arabia sharpen their focus on fairness, transparency and accountability, the tension between moving fast and lending responsibly is coming to a head.
Here, Al Ahli talks to Gulf Business about why approval time should be an operational indicator rather than a definition of success, the risks of automating weak decisions at scale, and how banks can improve the borrowing experience without loosening the controls that protect credit quality.
GCC banks have invested heavily in reducing loan approval times. Why do you believe speed is becoming the wrong measure of success?
Speed is important, but it is not the ultimate measure of digital lending performance. A loan decision delivered in seconds has limited value if it misjudges affordability, increases future credit risk, or cannot be explained clearly to the customer or regulator. The real measure is whether a bank can make the right decision quickly, consistently and responsibly. In lending, speed only creates value when it is supported by strong data, sound risk controls and clear decision logic.
KPMG’s analysis found that net loan provision charges in the GCC rose 19.4 per cent in 2025 year-on-year, even as the average non-performing loan ratio improved from 3.4 per cent to 3 per cent. This illustrates why no single metric provides a complete picture of lending performance, and why banks must assess approval speed alongside credit quality, expected losses and the long-term health of loan portfolios.
Banks should therefore judge digital lending by the quality of the resulting portfolio, customer outcomes and regulatory defensibility. Approval time should remain an operational indicator, but it should never become the main definition of success.
What risks arise when banks prioritise rapid approvals over the quality and accuracy of lending decisions?
When banks prioritise speed without the right controls, they risk making faster decisions rather than better decisions. The main risk is approving customers whose affordability or risk profile has not been properly assessed, or rejecting creditworthy customers because the decision logic is incomplete. The result is higher credit, fraud and provisioning risk on one side, and weaker customer trust and lost business on the other.
The risk increases when banks automate weak decision processes instead of improving them. If the data foundation is incomplete, the model logic is outdated, or the decision rules rely on too narrow a set of indicators, errors can scale quickly across thousands of applications. In that environment, automation does not reduce risk; it accelerates it.
The regulatory direction is also clear. The CBUAE’s 2026 AI guidance emphasises accountability, fairness, transparency, human oversight, data management and privacy, while Saudi Central Bank (SAMA) consumer protection and responsible lending principles reinforce the need for fair and transparent lending decisions.
Faster approvals must therefore remain reproducible, reviewable and defensible. The goal is not automation for its own sake, but controlled automation that improves speed without weakening credit discipline, customer protection or regulatory confidence.
Which indicators should banks track instead of, or alongside, approval time to assess the effectiveness of their lending processes?
Banks should treat approval time as one operational indicator, not the main measure of lending performance. A stronger lending dashboard should combine three views: credit quality, process quality and customer outcomes. On the credit side, banks need to monitor whether faster approvals are supported by healthy early delinquency levels, controlled defaults, expected credit losses, fraud indicators and appropriate decision overrides.
The second view is process quality. Banks should track where applications drop, where exceptions increase, and whether decision explanations are clear enough for review and customer communication. If approval time improves but abandonment, complaints or rework increase, the process is faster but not necessarily better.
The goal is not automation for its own sake, but controlled automation that improves speed without weakening credit discipline, customer protection or regulatory confidence.
As banks use more AI in credit decisions, how can they ensure that outcomes remain explainable, transparent and free from unintended bias?
As AI becomes more embedded in credit decisioning, explainability cannot be treated as a technical add-on. It has to be part of the decision framework itself. Banks need to understand not only the outcome of a credit decision, but the logic behind it: the data used, the risk factors considered, the rules or model applied, and whether the result is consistent with the bank’s risk appetite and customer fairness standards. In lending, an AI-supported decision is only credible if it can be explained, reviewed and challenged when needed.
Avoiding unintended bias requires active testing, not assumptions. Banks should monitor outcomes across customer groups and maintain regular model validation, performance monitoring and human oversight. The objective is not to remove human judgement, but to use AI to improve consistency, speed and decision quality while keeping accountability clearly with the bank.
How does CREALOGIX’s Lending Origination Hub help banks balance faster decisions with auditability, regulatory compliance and effective risk controls?
In digital lending, speed and control should not be treated as separate objectives. The strongest origination models are those where auditability, compliance and risk controls are built directly into the journey, not managed outside. A bank should be able to trace what information was collected, how the customer was qualified, which decision steps were followed, where human review was required, and how the outcome was reached. This is what allows digital lending to become faster without becoming less controlled.
CREALOGIX‘s Lending Origination Hub supports this by helping banks digitise the origination journey while keeping their credit policies, approval steps and control points inside the workflow. It allows banks to configure products and approval paths, support qualification and proposal generation, manage onboarding and contracting, and combine automation with human validation where needed. The result is not simply faster processing; it is a more traceable, consistent and controlled lending journey that supports auditability, compliance and responsible decision-making.
How can GCC banks improve the borrowing experience without weakening underwriting standards or creating additional regulatory and credit risks?
The best borrowing experience removes avoidable friction, not unnecessary scrutiny. Customers should not have to repeat information, chase updates or navigate unclear documentation requirements. A better journey gives them clarity on what information is needed, where the application stands, what the next step is, and why a decision has been made.
At the same time, banks should not remove the controls that protect credit quality. A stronger lending journey uses early qualification, better data capture and clear routing rules to separate straightforward cases from those that need deeper review. Simple applications can move faster, while more complex or higher-risk cases can be directed to the right team for human assessment.
This is where digital origination becomes valuable. It improves the customer experience while preserving underwriting discipline by connecting the front-end journey with credit policies, documentation, approval workflows and audit trails. For GCC banks, the opportunity is to make borrowing faster and easier for the customer, while keeping decisions controlled, explainable and aligned with responsible lending standards.
