AI in Financial Services: Solving the Key Challenges of the Middle East’s Fintech Sector

When Emirates NBD launches a virtual assistant to support customers with everyday banking operations, it’s not just a technical experiment. When Riyad Bank opens its “Center of Intelligence” to integrate AI technologies for analytics, fraud detection, and more, it’s not a technical experiment either. And when Mashreq Bank uses AI in financial services to analyze customer data and deliver personalized recommendations, that’s not a mere technical trial.

This is the way banks in the Middle East region respond to much deeper challenges. This involves navigating complex regulations, fragmented data, and a shortage of analytical talent, while also attempting to meet the expectations of young, digitally savvy customers. 

In this article, we are going to highlight the challenges that AI in banking and financial services can help solve, uncover the benefits it can bring to banks, and examine real cases for illustration.

Artificial Intelligence in Financial Services in the Middle East: Market Overview and Key Trends

Till 2028, the fintech market of the Middle East region is predicted to grow by 35% annually, as McKinsey states. Compared to other global markets, this is huge. During the year from 2023 to 2024, over $1.9 billion of investment fueled the birth of four unicorns, and this is only the start. This is one of the reasons MENA banks are looking to implement artificial intelligence in financial services.

According to FinTech Global, another reason for adopting AI in financial services is the change in the regulatory field. For example, Saudi Arabia’s new UBO rules, which came into effect in April 2025, are making life a lot trickier for banks. Now companies have to report detailed ownership data in a central register, or they face penalties, and with complex corporate structures, that’s no small task. This is where AI really helps: it can sift through documents, map ownership links, and keep everything updated in real time, making compliance much easier and less stressful.

The impact of AI on financial services in the Middle East is crucial. Let’s now focus on the challenges that lie behind, how banks deal with fighting them, and how it leads to digital transformation and innovation.

AI for Financial Services: Major Challenges and Ways to Solve Them

The Middle East fintech market is now coming into its own. There is a lot of investment, and banks use money to improve services, make customers happier, and thus grow bigger and much more profitable. This is where financial services and AI meet, tackling together a number of challenges.

Artificial Intelligence in Finance: Dealing With Fragmented and Outdated Data

Banks in the Middle East region work with outdated and isolated core banking systems. Information is stored in different formats. It is saved chaotically in different sub-systems, and often there are a lot of file duplicates and errors in managing these files. This is a huge blocker in operations.

Solutions

The problem of data fragmentation can be addressed with AI and data engineering practices. Here are the most effective solutions:

1. Unified data platforms or data lakes. It is a centralised data storage with all types of data, including structured, semi-structured, or non-structured. Having such a system helps AI models get access to the necessary data faster without the need to deal with each source separately. 

2. Standardization and data governance in banking. Banks need to set data/metadata quality rules and implement standards. For example, banks should have different formats of data for clients, transactions, errors, etc., without mixing them.

3. ETL/Ingestion frameworks. This is about automating the process of collecting, cleaning, and formatting data before transporting it to the analytics-driven investment platform or other financial system.

4. Real-time analytics. The faster the data is collected and managed, the more effectively banks can respond to client behavior changes, fraud, or other risks. Preparing data gets less time-consuming.

Real Case: Emirates NBD

Artificial intelligence in finance starts with data. And Emirates NBD is a good example of it. 

The bank had many legacy systems. Departments in different locations worked with different databases and according to different schemes of saving data. 

What did they do? They built an Enterprise Data Platform (EDP) with a single model of data for all sources and systems. This helped create AI models of client behavior, launch personalized recommendations in the mobile app, and set an AI chatbot for support. As a result, Emirates NBD enhanced the effectiveness of decision-making based on quality data.

Lumitech provides fintech software development services powered by AI to build unified data platforms to turn your legacy banking system into an effective solution. Just like Emirates NBD did.

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Fraud and AML: How AI in Banking and Financial Services Can Solve It

With the development of instant payments and open banking, the number of fraudulent transactions has grown significantly. Credit manipulations, SMS or WhatsApp fishing, synthetic identities, money laundering, and many more crimes cause harm and losses to banks. 

Traditional rule-based systems generate too many false positives, can’t detect new behavior patterns, and do not scale as the number of transactions grows.

Solutions

AI in Middle Eastern financial institutions addresses this problem quite effectively due to:

1. Machine learning for anomaly detection. AI analyzes the behavior of clients and detects when it becomes atypical. 

2. KYC/AML monitoring powered by AI. NLP analyzes client documents and data sources to check their authenticity. Algorithms assess the riskiness of the client/counterparties and track connections between companies.

3. Predictive analytics to prevent fraud. Not only does artificial intelligence in financial sector react to the crime, it also predicts the likelihood of fraud based on certain client behavior patterns. For example, if the client changes payment method or the way they behave in the app, the system can temporarily stop the operation.

4. Explainable AI (XAI). This helps show regulators why the transaction is marked as suspicious. It is important as the central regulators of the region (like SAMA or DFSA) demand transparency in using AI for AML. 

Real Case: Arab National Bank

Arab National Bank in Saudi Arabia uses AI development services to deal with fraud and financial crime in real time. With IBM, the bank launched the IBM Safer Payments system that analyzes transactions instantly, finds suspicious operations, and helps block fraud. The system works through all bank channels and reduces false positives. Due to artificial intelligence for financial services, clients get fast and secure service. 

How AI Deals with Regulatory Pressure and Compliance Complexity

This problem is closely connected with the previous one. 

Banks in the Middle East region, mainly in Saudi Arabia and the United Arab Emirates, face increased AML and counter-terrorism financing (CFT) requirements, including the necessity to integrate round-the-clock real-time systems for detecting fraud. 

This creates additional pressure on banks, which must adhere to these requirements, while simultaneously enhancing effectiveness and precision in detecting suspicious operations. Compliance teams in banks suffer.

Solutions

Artificial intelligence and financial services are perfect partners. AI helps banks automate fraud detection and compliance processes. Here is how:

1. RegTech platforms backed by AI automate the process of client verification (eKYC), transaction monitoring, and report generation.

2. NLP models analyze documents and detect inconsistencies or missed fields.

3. Machine learning helps assess counterparty risk based on indirect indicators like payment patterns or related companies.

Real Case: Bank Albilad

Bank Albilad in Saudi Arabia implemented a solution powered by AI for real-time fraud detection. It was made to ensure compliance with requirements established by the Saudi Central Bank.

AI Solutions for Сybersecurity and Data Leakage Risks

Numerous cyber threats, including malware, phishing, supply chain attacks, and data breaches, make banks in the Middle East sleep badly at night. According to Cyble's investigations in 2025, we see an increase in ransomware attacks in the financial sector, particularly in the United Arab Emirates, Oman, and Qatar. This is about exploiting zero-day vulnerabilities and compromising service providers, leading to customer data leaks and financial losses.

Solutions

PwC report states that organizations in the UAE are actively implementing AI in banking and financial services to detect malware and phishing, and manage vulnerabilities. Here is how they tackle the problem:

• Predictive analytics for detecting potential attacks before they take place.

• Data encryption and federated learning to train models without transmitting sensitive information.

AI systems to see atypical customer behavior.

Real Case: Khaleeji Bank

Khaleeji Bank in Bahrain is a perfect case. The bank uses the Recorded Future platform to protect its reputation, fight brand counterfeiting, and manage third-party risk. They integrated threat intelligence, brand protection, and third-party risk management into a single system. This enabled the bank to respond to cyber threats and mitigate potential losses effectively.

Top Middle Eastern Countries in Implementing AI for Banking and Fintech

With all the investments coming into the Middle East financial sector, some of the countries have already become leaders in implementing artificial intelligence in finance. Here is the list of the top 3 countries we think are the most perspective.

UAE

Leader in market share in the field of AI and financial services (nearly 40% of the regional market) according to Credence Research. Artificial intelligence in financial services in Dubai, as well as in other cities across the country, is used for fraud detection, risk management, personalization, and chatbots. 

Liv Bank by Emirates NBD is a good example of using AI in Middle Eastern financial institutions. It already has digital services with deep data analysis and personalization.

Saudi Arabia

More and more fintech companies appear in Saudi Arabia. Their digital transformation is powered by the state's Vision 2030 strategy, providing resources for development. 

So, what’s happening? Fintech sandbox, along with a regulatory framework, fuels the development of embedded finance, P2P lending, and SME credits. AIS Launch project illustrates AI transformations in Saudi Arabia. It uses Open Banking for assessing creditworthiness and provides fast lending to small businesses. 

Overall, banks focus on digital payments, instant transactions, and partnerships with global services like Google Pay or Alipay+ to enhance payment infrastructure. AI companies in Saudi Arabia invest in building automation programs, AI for compliance and risk management, and open fintech labs.

Bahrain

In Bahrain, we see well-developed regulatory frameworks for digital assets, cryptocurrencies, and digital payment platforms.

Bahrain FinTech Bay (BFB) focuses on the development of the fintech and AI ecosystem. For example, they launched a partnership with Labiba for Artificial Intelligence to create a VUI / Conversational Interface platform that supports the Arabic language and its dialects.

Also, in Bahrain, it is recognised that Open Banking APIs supported by AI are among the key trends that will grow, as per the Fintech Bay report.

AI Is Growing Fast: But Finding the Right Talent Isn’t Easy

Talent shortage is one of the challenges of implementing AI in financial services in the Middle East. According to the Research and Markets report, nearly 60% of fintech companies in the region are adopting AI, but only 14-28% managed to scale the technology across all business functions. They say the skill gap is one of the blockers.

So, what fintech companies are looking for? Below, you can check the list of expertise needed to effectively integrate and support AI in fintech and banking:

Summarizing the Benefits AI Brings to the Middle East Fintech Region

Artificial intelligence in financial services is quickly turning into one of the biggest enablers across the Middle East. Banks and startups are using it not just to automate routine tasks, but actually to change how financial services work. 

No matter whether it is neo-banking, payment solutions, wealth management, insurtech, regtech, or even AI patent screening, the benefits appear in all types of AI financial services.

Smarter risk management AI spots potential risks long before they turn into real problems. It analyzes credit behavior, spending patterns, and transactions in seconds.

More efficient operations From document checks to customer requests, AI for financial services takes care of repetitive work. This allows bank employees to focus on higher-value tasks. That leads to faster processes, lower costs, and smoother back-office workflows.

Connected data and real insights AI finally brings unstructured data together and links systems like core banking, CRM, and payments. Thus, teams can see the full customer picture and make smarter decisions.

Better business decisions Artificial intelligence and financial services help predict what customers might need next and guide business planning with real data, rather than intuition.

Stronger cybersecurity AI provides high-level security. It checks all transactions and network activity, detecting any suspicious action and helping prevent fraud or cyberattacks.

More personalized products AI lets banks create financial products that adapt to each customer. Thus, customers feel that the banks see their pains and needs. As a result, stronger relationships are built.

Here at Lumitech, we see the value AI brings to banks and fintech companies. We have strong expert teams that are dedicated to helping your business reach the next level, demonstrating that all the above-mentioned points are not mere words.

Let’s start the AI journey together.