How AI Is Helping Financial Services Companies in United Arab Emirates Cut Costs and Improve Efficiency

The United Arab Emirates is rapidly becoming a testbed for AI in finance: Credence Research forecasts the UAE AI-in-finance market will leap from USD 67 million in 2023 to USD 514 million by 2032 (CAGR 25.3%), fuelled by government programs like the UAE AI Strategy 2031 and vibrant fintech hubs in Dubai and Abu Dhabi (Credence Research UAE AI in Finance market forecast).

Banks and fintechs are already rolling out Arabic-first virtual assistants, generative-AI tools and real‑time fraud detection to cut handling times, boost security and deliver hyper‑personalized services - innovations detailed in regional coverage of AI in banking (Consultancy Middle East: AI innovations in banking).

For professionals who want to turn these trends into concrete projects, practical upskilling matters: Nucamp's 15-week AI Essentials for Work bootcamp teaches prompt-writing, tool use, and business-focused AI application to help teams move from pilot to scale (Nucamp AI Essentials for Work - syllabus and registration).

Metric	Value
UAE AI in finance (2023)	USD 67M
UAE AI in finance (2032)	USD 514M
Forecast CAGR (2024–2032)	25.3%
Market share: Dubai	60%
Market share: Abu Dhabi	30%

Customer-service automation is already changing the day-to-day of UAE finance: banks and service providers use chatbots and voice assistants to handle routine requests around the clock, bridge Arabic–English language gaps, and free human agents for complex problems.

Emirates NBD's EVA is a standout example - announced as the region's first intelligent voice-and-chat virtual assistant and later shown in pilots to cut response times by about 35% and reduce call‑centre volume by roughly 20% - while phone‑banking automation rose from 11% to 19% and calls to agents fell 14% in related reporting, underlining real operational gains (Emirates NBD EVA intelligent virtual assistant announcement, UAE AI customer support automation case studies, Emirates NBD phone-banking automation results and optimisation).

Telecoms and retailers echo the trend - Etisalat's bilingual bot resolved about 70% of queries without humans in early months and Talabat boosted first‑response speeds by over 50% - so the practical “so what?” is clear: a single well‑tuned virtual assistant can turn peak‑hour queues into instant answers, cut operating costs and lift satisfaction across Arabic and expatriate customers in Dubai and Abu Dhabi.

Metric	Result
Response time (EVA)	-35%
Call centre volume (EVA)	-20%
Phone‑banking automation	11% → 19%
Calls to agents	-14%
Etisalat self‑resolves	~70%
Talabat first‑response time	+50% faster

“EVA™ will soon be an exciting new addition to our customer service toolkit, acting as an intelligent virtual assistant to help customers with their banking needs,” said Suvo Sarkar, Senior EVP & Group Head – Retail Banking & Wealth Management at Emirates NBD.

Back‑office automation is quietly remaking the ledger rooms and compliance desks of UAE banks: rule‑based RPA bots now handle invoice processing, reconciliations, KYC verifications and loan paperwork at scale, shrinking cycle times, cutting errors and creating audit‑ready trails so human teams can focus on exceptions and client relationships; First Abu Dhabi Bank's intelligent automation programme alone turned a seven‑day admin task into one day and deployed over a hundred robots to process millions of transactions - proof that well‑governed automation delivers measurable ROI (read the FAB case study on UiPath) and aligns with regional guidance on “how RPA transforms back‑office operations” for 40–70% cost and time savings.

Local providers from Dubai offering UiPath, Automation Anywhere and specialist DPA services help banks pilot small, high‑impact processes (AP, reconciliations, regulatory reports) and then scale, while integration with AI/OCR powers near‑touchless accounting and faster regulatory filings - so the practical payoff is simple: fewer manual errors, faster turnarounds and freed capacity for higher‑value risk and customer work.

Metric	Value
FAB robots deployed	110
Transactions processed	9.2 million
Hours saved	1.3 million
Handling time reduction	56%
Reported cost savings	AED 210M+

“We've already deployed numerous IA solutions by integrating RPA with chatbots and email classification technology. There is much more potential to explore,” says Suhail Bin Tarraf.

Fraud detection and AML in the UAE are moving from reactive playbooks to millisecond‑scale prevention: the Central Bank's May 2025 Notice (No. CBUAE/FCMCP/2025/3057) forces banks to retire weak SMS/email OTP and static‑password flows, require strong identity checks (e.g., Emirates face recognition for first‑time access) and mandate real‑time transaction analysis so suspicious transfers can be stopped as they happen - practical compliance and engineering work that security teams must turn into production fast (CBUAE Notice May 2025: fraud and authentication requirements).

At the same time, UAE firms are adopting AI-driven, behavior‑based monitoring and adaptive risk scoring - systems that can flag anomalies in 200–300 ms and cut false positives while linking across channels - so banks can reduce losses and keep friction low for legitimate customers (Real-time AI fraud detection engines for banking use cases).

Local case studies show concrete gains: faster onboarding, fewer false alerts and better synthetic‑identity detection, and the new regulatory timeline (most requirements due by 31 March 2026) turns these technologies from “nice to have” into operational must‑haves for Dubai and Abu Dhabi financial institutions.

Metric	Value
CBUAE compliance deadline	31 March 2026 (most requirements)
Prohibited sole auth methods	SMS OTP, email OTP, static passwords
AI decision latency	200–300 ms
Royal Cyber: onboarding time reduction	60%
Royal Cyber: false positives reduction	40%

“It was a pleasure working with Royal Cyber. The involvement from Royal Cyber at every stage from discovery to go-live is commendable, and in a short span of time the team was able to deliver the product and even accommodate changes on the go. Well, done!” - Chief Technical Officer

Compliance automation and RegTech are turning a regulatory headache in the UAE into a competitive advantage: automated KYC workflows and biometric checks now cut onboarding friction and human error while producing audit‑ready records that regulators expect, anchored in the UAE's AML/CFT laws such as Federal Decree‑Law No.

20 of 2018 and Cabinet Decision No. 10 of 2019; practical guides show how KYC automation creates digital customer profiles for continuous monitoring and quicker risk reassessments (KYC automation guide for AML compliance - AML UAE).

Market tools bundle identity verification, PEP/sanctions screening and transaction monitoring, with vendors like Binderr offering end‑to‑end biometric KYC plus ongoing AML screening to keep alerts manageable (AML and KYC software solutions in the UAE - Binderr).

For high‑volume review tasks, AI agents can be game changers: vendor case studies show automated agents that triage sanctions and adverse‑media alerts and can reduce manual review effort dramatically - WorkFusion cites up to a 70% reduction on PEP/sanctions work - freeing teams to handle true exceptions and regulatory reporting (WorkFusion AI agents for UAE AML compliance - WorkFusion).

The practical takeaway for Dubai and Abu Dhabi firms is simple: pick modular RegTech that integrates with goAML, enforces a risk‑based approach, and turns continuous screening into faster decisions and cleaner audits, not just another inbox of alerts.

Capability	Example / Benefit
KYC automation	Digital customer profiles, faster onboarding, fewer human errors (AML UAE)
End‑to‑end AML/KYC platforms	Biometric KYC + ongoing screening (Binderr)
AI Agents / Alert triage	Reduces manual PEP/sanctions review (up to 70% WorkFusion)
Regulatory integration	Connects to goAML and produces audit‑ready trails (KYC Hub / NorthLark)

AI is quietly unlocking credit for people and small businesses across the UAE by folding alternative signals - rental and utility payments, telecom bills, employment records and even device and digital‑footprint data - into automated scoring models that reach “thin‑file” and expatriate customers traditional models miss; regulators and infrastructure are catching up too, with onshore rules and open‑banking APIs plus AECB collaborations (for example PolicyBazaar and Nova Credit integrations) making secure data sharing practical and compliant (Chambers: Regulation of Credit Data and Open Banking in the UAE).

Engineers and risk teams in Dubai and Abu Dhabi now combine ML models with device intelligence and transaction signals to cut decision times and false negatives while broadening access - Intellias and sector guides show alternative data can accurately score a large share of applicants who would otherwise be “no‑hit,” and digital signals have become decisive for auto, small business and remittance‑linked loans (Intellias: How Alternative Credit Data Can Increase Accuracy in Credit Scoring, SEON: Alternative Credit Scoring Guide).

The practical payoff is vivid: a steady trail of paid mobile and rent bills can act like a passport to a first loan, turning everyday financial habits into measurable creditworthiness for millions in the UAE.

Metric / Fact	Value / Example
UAE fintech ecosystem share (startups)	46% of regional fintech startups (Chambers)
UAE fintech funding share (MENA)	69% of all fintech funding in MENA (Chambers)
Alternative data scoring impact	Can score >90% of applicants otherwise classed as no‑hit (Intellias)

Wealth management in the UAE is becoming a study in practical personalization: AI‑driven robo‑advisors and hybrid platforms use algorithms to tailor portfolios, lower friction and stretch every dirham - robo fees typically sit in the 0.25%–0.50% range while traditional advisory averages around 1.02% AUM, so choosing the right delivery model has measurable impact on net returns (Wealth management fees in the UAE - Quadra Wealth analysis).

Dubai's tech‑savvy population and a growing fintech ecosystem (players like Sarwa, FinaMaze and CBD Investr) are driving adoption of both pure and hybrid robo‑advisors as firms balance low‑cost automation with bespoke human advice for high‑net‑worth clients (UAE robo-advisory industry outlook - Research and Markets report), and recent engineering work on secure, cloud-native robo platforms means scalable, personalised modelling with no large minimums is now practical for retail and mass‑affluent segments (AI-powered cloud robo-advisors in wealth management - Seasia Infotech analysis).

The “so what?” is vivid: by pairing inexpensive, algorithmic portfolio construction with targeted human advice where it matters, UAE firms can widen access, reduce fees, and deliver genuinely personalised wealth plans that fit expatriate and Emirati lives across Dubai and Abu Dhabi.

For UAE treasuries the promise of AI is practical, not theoretical: machine learning and generative tools are replacing fragile spreadsheet forecasts with real‑time, scenario‑driven cash views that spot patterns humans miss and cut forecast error dramatically - J.P. Morgan notes AI models can halve error rates and enable stress‑testing at scale (J.P. Morgan AI-driven cash-flow forecasting report).

Local dynamics make this urgent - e‑invoicing, VAT cycles and cross‑border payroll create timing spikes - so guides for UAE firms advise coupling short‑term rolling forecasts with automated receivables/payables workflows to free trapped liquidity (Alaan UAE cash-flow optimisation strategies and techniques).

Practical deployments show the payoff: AI can extend visibility (one client tripled its forecast horizon to 91 days), cut manual reconciliation, and save six‑figure sums annually when combined with bank and ERP integrations; treasury vendors like Kyriba emphasise API‑led data ingestion and on‑demand dashboards for CFOs (Kyriba cash forecasting case studies and API-led data integration).

The takeaway for Dubai and Abu Dhabi teams is clear: start small with high‑quality data connectors, automate short‑term scenarios, and scale the models that turn operating signals into cash - so treasury becomes a strategic lever, not a month‑end scramble.

Metric	Value / Source
AI forecast error reduction	Up to 50% (J.P. Morgan)
Forecast horizon improvement	30 → 91 days (Prysmian / J.P. Morgan case)
Annual savings (case)	$100,000 (Prysmian)
Electronic transactions processed (Sharjah)	~70% processed electronically (Kyriba / HSBC case)

“Around 70% of transactions are now processed electronically and we have gained full visibility over our cash and financial transactions.” - Sean De Silva, Cash Management Section Head, Sharjah Finance Department

Unlocking AI at scale in the UAE depends as much on where data lives as on the models that run on it, and Abu Dhabi's multi‑year sovereign cloud deal with Microsoft and Core42 is the connective tissue financial firms have been waiting for: a high‑performance, Azure‑powered sovereign platform - backed by Core42's Insight controls - promises data residency, lower latency for real‑time fraud and treasury models, and a compliant route to deploy Arabic models such as Jais in regulated environments; the partnership underpins an ambitious AED 13 billion (USD 3.54 billion) digital strategy and a plan to process more than 11 million daily digital interactions while rolling out 200+ AI solutions for public services (Abu Dhabi sovereign cloud deal with Microsoft and Core42, Core42 Sovereign Public Cloud overview, Microsoft and G42 AI partnership announcement).

For banks and fintechs in Dubai and Abu Dhabi the practical payoff is straightforward: keep sensitive customer and transaction data under local control, run low‑latency scoring and AML pipelines close to source systems, and scale compliant AI pilots into production without sacrificing speed or sovereignty.

Metric	Value
Daily digital interactions capacity	11 million+
Investment (Abu Dhabi Digital Strategy 2025–2027)	USD 3.54 billion (AED 13 billion)
AI‑driven solutions planned	200+
Target	Automate 100% of government processes / AI‑native government by 2027

“Technology has the power to transform how governments interact with people, making services more efficient, intuitive, and impactful.” - Ahmed Tamim Hisham Al Kuttab, Chairman, Department of Government Enablement, Abu Dhabi

UAE AI progress isn't just about clever models - it's being driven by deep-pocketed partnerships and mammoth infrastructure that directly matter to banks and fintechs in Dubai and Abu Dhabi.

Strategic deals like Microsoft's $1.5B investment in G42 partnership and the CNBC analysis of the US–UAE AI coalition have concentrated compute, cloud and developer funding locally - from sovereign‑cloud controls to plans for a 5GW Abu Dhabi AI campus and an initial 200‑MW cluster - so financial firms can run low‑latency fraud detection, real‑time scoring and treasury models without leaving the country.

Public‑private moves (core sovereign platforms, developer funds and green data‑centre projects) also crowd in global partners, talent and capital while easing compliance and data‑residency hurdles; that means pilots move to production faster and with fewer legal headaches.

The practical payoff for UAE financial teams is concrete: on‑shore compute and partnership capital that turn AI experiments into scalable, auditable services for customers across Arabic and expatriate markets (G42 and Microsoft digital ecosystem initiative announcement).

“AI will transform how governments operate and serve their citizens everywhere, and Abu Dhabi is leading the way. Through our partnership with the Department of Government Enablement – Abu Dhabi and G42, we are setting a standard for AI adoption in the public sector, as we help Abu Dhabi become the world's first AI‑native government.”

- Satya Nadella

Operational challenges in the UAE's finance sector are now front and centre: KPMG benchmarking shows adoption is widespread but fragmented, with 49% of organisations running AI plans and 59% planning or running pilots - yet only 37% of UAE finance leaders report positive ROI compared with 66% globally - largely because scattered data, legacy systems and weak MLOps/governance stop pilots from scaling into production (KPMG benchmarking report on AI adoption in UAE finance – Khaleej Times).

The practical next steps are clear and local: tighten model governance, invest in data pipelines and audit trails, pick realistic first use cases that prove ROI (for example the generative-AI work already automating internal reporting and regulatory disclosures), and lean on industry programmes and knowledge‑sharing to speed safe rollouts - initiatives led by the Emirates Institute of Finance with HSBC, Presight and Core42 create the controlled pilots and playbooks needed to move from experiment to scale (Emirates Institute for Finance AI in finance initiative – FintechNews).

Anchoring these efforts in the UAE National AI Strategy 2031 helps align governance, talent and testbeds so AI becomes an operational advantage, not a compliance headache.

Metric	Value
Organisations with AI plans	49%
Planning or running pilots	59%
Finance leaders reporting positive ROI	37% (UAE) vs 66% (global)
IT budget to AI	10%
See regulation as barrier	25%
GenAI in reporting (now → 3 years)	41% → 88%

“The UAE Government's national vision and ongoing investment in AI are a catalyst for immense growth. However, challenges remain, with AI usage still fragmented despite interest from major organisations. Some Finance teams are ill-equipped to lead large-scale AI transformations, or they simply lack the know-how to integrate day-to-day decision-making with AI. To succeed with AI, it is critical for Finance teams to assess whether their ROI is robust and whether their first use cases are realistic given scattered data and legacy systems in many cases. This will enable them to gain buy-in and scale quickly through more focused implementation.” - Bhaskar Sahay, Partner, Head of Accounting and Finance for the UAE and Oman, KPMG Middle East

Conclusion and practical checklist for UAE beginners: with the UAE AI‑in‑finance market poised to jump from USD 67M in 2023 to USD 514M by 2032, the opportunity is real - but practical, governed steps win: pick one measurable pilot (fraud detection, a bilingual virtual assistant or a small RPA reconciliation), set a clear ROI horizon and success metrics, and design data flows to meet PDPL and local sandbox rules rather than retrofitting later; useful guidance on the evolving legal landscape is in the UAE AI legal and regulatory guide (UAE AI legal and regulatory guide (Bird & Bird)), and market sizing/sector hotspots are summarised by Credence Research (Credence Research UAE AI in Finance Market forecast).

Start small with pre‑trained models and bank/ERP connectors, prove value, lock compliance and data‑residency, then scale with robust MLOps and auditing; for teams new to applied AI, pragmatic upskilling such as Nucamp's 15‑week AI Essentials for Work helps turn pilots into production-ready projects (Nucamp AI Essentials for Work - 15-week practical AI training).

Think of this as a stepwise playbook: choose a focused use case, secure data and legal guardrails, measure ROI fast, then scale the winners into auditable services across Dubai and Abu Dhabi.

Metric	Value
UAE AI in finance (2023)	USD 67M
UAE AI in finance (2032)	USD 514M
Forecast CAGR (2024–2032)	25.3%