Between billions of dirhams in investment and data confidentiality: how swarms of agents are imposing new rules on banks?

Banks and investment firms in Abu Dhabi are putting billions of dirhams behind a precise practical test: can financial evaluation and fraud detection tasks be delegated to AI systems without compromising account confidentiality or breaching regulatory compliance standards? This question shapes the current session of the Ai Everything Abu Dhabi 2026 summit held at the ADNEC centre, with participation from the UAE Ministry of Investment and international financial institutions, at a time when the deployment of technology to re-engineer capital management and daily banking operations is accelerating.

The scale of this transformation is reflected in the figures of the Abu Dhabi Global Market, which is injecting more than 400 million dirhams by 2029 to expand its digital infrastructure and upgrade its AI-driven operational and regulatory systems. This expansion occurs in an asset-management environment that now includes 190 fund and asset managers overseeing 276 investment funds, making financial-process automation a unavoidable necessity to handle the rapid increase in liquidity and portfolios.

The UAE Ministry of Investment adopts a strategy that goes beyond merely attracting foreign capital; Minister Mohammed Hassan Al-Suwaidi said the primary goal is to build and expand AI companies within the country, deepen local capabilities and create high-value jobs. The plan rests on direct domestic investment, estimated at between $100 billion and $119 billion, roughly two to 2.5 times the annual foreign direct investment inflows, supported by sovereign wealth funds, family offices and private firms investing alongside international capital.

Our editorial team observed how companies are moving away from single-model approaches toward multi-agent systems; Genesis AI, operating from Cairo and Dubai, unveiled its “Financial Identity” platform that coordinates the work of more than 15 specialized agents for valuation, portfolio risk, market sentiment, trade signals, fundamental and technical analysis, and compliance with Sharia principles.The technological bet is no longer based on a single generic model that answers everything, but on a central control layer that manages specialized swarms and produces a reliable, auditable investment recommendation.In parallel, the FairValuation.com platform offers tools to automate valuation models for listed companies and employee stock-ownership plans within minutes, enabling ready-made outputs for board-level oversight.

The biggest friction point in banking always lies in protecting sensitive data; this is where federated learning solutions emerge. The local FedTuna platform showcases technology that lets banks train shared fraud-detection models while keeping customer records on each bank’s own servers. An operational trial involving two banks showed an early-fraud detection increase of between 2.0 and 3.7 percentage points at a false-alarm rate of 1 percent, translating into the identification of roughly 43 additional fraud cases during the test period without a single financial statement leak.

Conversely, infrastructure firms such as Red Hat are driving open hybrid-cloud solutions and sovereign AI capabilities, with regional executives stressing that the success of AI agents depends on local teams’ ability to monitor system behavior and provide direct oversight. These experiments also extend to the consumer sector through applications like SouqView, which focuses on interactive investing and is unveiling its second version after attracting more than 400 registered users with virtual portfolios covering UAE and US markets, supported by a grant from the Khalifa Fund.

What actually changes for the financial and technical practitioner in the region?If you lead risk management or compliance at a Gulf bank or a financial institution in Egypt or the Levant, the workspace changes fundamentally; these tools compel a shift from post-data auditing to real-time supervision of automated agent inference. Data engineers can now train financial-crime-prevention models without moving records outside the organization, using a collaborative architecture that preserves sovereignty while leveraging patterns discovered by peer institutions.

For development teams and startups in Cairo, Riyadh and Dubai, the message is clear: market value does not stem from building simple query interfaces, but from delivering specialized tools that address compliance, valuation and financial auditing with a reliability that convinces the stringent audit committees of banks.