BE - September 2026

WHY THE NUMBERS LAG THE NARRATIVE Three things explain the discrepancy between the story and the statement of income, and none of them is a rea- son for pessimism. Annual reports are not operating manuals. One bank may run sophis- ticated models and give them a para- graph. Another may describe an ambition it has not yet built. The re- port reflects the communications function as much as the technology function. What our findings really es- tablish is narrow and practical: dis- closure is not a usable signal. Technology pays late. Core banking transformations take years to reach the cost line. The benefits include shorter cycle times, fewer errors, staff redeployed to higher-value work, and losses that never occurred. None of those lands neatly in a single year’s return on equity. Judging by when the sector began discussing it seriously, the Arab deployment cycle gathered pace only around the turn of the decade. Expecting a clean profitability signal by 2025 was al- ways optimistic. Most of what has been deployed is the easy part. Chatbots, document capture, marketing personalization, and fraud alerting are useful and cheap to buy. They are also available to every competitor at the same price, which is precisely why they do not separate one bank from another in the results. The applications that would separate them sit deeper in the institution and are considerably harder to build. WHERE THE MONEY IS If the customer-facing layer is being commoditized, the question is where durable value lies. Four areas stand out for Arab banks. Credit. A better default prediction is worth more than all efficiency gains combined, for the reason established above: in this region, asset quality drives profitability. Models that draw on transaction flows, supply-chain relationships and sectoral exposures can see deterioration months before a payment is missed. For banks with concentrated corporate books, which describe much of the Gulf, six months of early warning on a single large exposure can be worth more than the entire annual technology budget. Financial crime. Industry estimates routinely put the false-positive rate in rule-based transaction monitoring above ninety percent, and every one of those alerts consumes an analyst’s time. Machine learning applied to the same flows substantially reduces noise while capturing patterns that static rules miss. Arab banks with heavy correspondent banking rela- tionships and cross-border remit- tance volumes have more to gain here than most international peers, in both costs and regulatory standing. The back office. Trade-finance docu- mentation, know-your-customer refreshes, collateral verification, rec- onciliation, and regulatory reporting are document-heavy, rule-bound, and repetitive. They are also where a surprising share of a bank’s head- count sits. Language models are un- usually good at exactly this work, and unlike customer-facing deploy- ments, it can be automated without a single client noticing. Risk and treasury. Scenario analysis, liquidity forecasting and stress testing ISSUE 213 SEPTEMBER 2026 the BANKING EXECUTIVE 47