The Influence of AI on Risk Management in Financial Services By Sanjana Madhavan

Over the last few years, there has been an increase in digital banking and online transactions. A survey taken by McKinsey & Company states that 80-90% of consumers in the UAE and KSA are heavy users of digital banking channels. Online and digital banking has become more attractive than traditional banking methods; it is faster and generally free to use compared to traditional banking, where it takes days to complete transactions and may require a fee to process transactions (KPMG, 2023).

But this has also become a big concern for many financial institutions around the world, as there has been a significant rise in fraudulent activities such as credit card scams, investment fraud, and money laundering. In a graph sourced by the Federal Trade Commission, 2012. Over the past decade, fraud complaints have increased from 0.2 million to 1.6 million (Blanton, 2012). To tackle these problems, financial institutions are turning toward the use of artificial intelligence for fraud detection and risk management. This article explores how AI is transforming fraud detection and risk management in the MENA region. 

AI-driven fraud detection systems leverage advanced technologies like machine learning algorithms to analyze vast amounts of transaction data and gain an understanding from previous fraud cases. These systems can predict fraudulent activities by assessing historical trends and identifying patterns (Gatla, 2021). They are highly dynamic, continuously adapting to new threats and monitoring user behavior, such as spending habits and login patterns. Any unusual activity deviating from a user's normal behavior triggers alerts.

According to reports, global credit card fraud losses incurred by financial institutions and individuals reached $32.3 billion in 2021, marking a significant 13.8% increase from the previous year. Additionally, a study by the Arab Monetary Fund found that “machine learning algorithms could enhance credit card fraud detection by 94%.” (ARAB NEWS, 2023). One of the most predominant advantages of AI-driven fraud detection

systems is their very advanced forecasting accuracy.

During crises, traditional statistical methods struggle to capture the complex relationship between the economy and the company's finances. Machine learning improves forecasting by identifying these patterns, leading to more accurate predictions (KPMG, 2024). Additionally, it also helps with better data segmentation; data segmentation is crucial for handling changes in financial data. Machine learning improves this by analyzing multiple factors. AI and machine learning algorithms can sort data more accurately, leading to better predictions and insights (KPMG, 2024). 

In the MENA region, financial regulations are constantly evolving to keep pace with digital transformations. Nevertheless, like any other industry, the MENA region's financial sector faces its own set of challenges. Among them, money laundering poses a great risk to financial institutions. The “United Nations estimated that 5 billion Saudi Riyals ($2 trillion) are laundered each year, and the traditional fraud detection techniques have proven to be inefficient and futile, with financial institutions being able to catch only 1% of these illegal and unauthorized transactions” (Team FOCAL, 2024).

To meet the demands of this growing problem, financial institutions in the MENA region have started to adopt innovative machine learning and AI technique solutions like e-KYC (electronic know your customer), that allows institutions to verify the identity of their customer using means of online platforms, deviating from the traditional in person verification process. By inculcating e-KYC methods, financial institutions and banks can speed up their process, being more efficient and able to manage risks better (Team FOCAL, 2024).

 The use of AI in financial and banking services is expected to reduce operational costs while enhancing the performance, liquidity, and profitability of financial institutions. By enhancing risk assessment, streamlining tasks, and improving decision-making, AI increases efficiency and strengthens financial stability. PwC mentioned that AI is expected to contribute approximately $15.7 trillion to the global economy by 2030, with $6.6 trillion from increased productivity rates in the workplace. “In the Arab region, AI applications are projected to contribute around $320 billion to the Middle East's economy by 2030, equivalent to 11% of the total GDP” (Arab Banks Union, 2018, p. 56). 

In conclusion, AI has become a crucial tool to combat financial fraud, offering advanced solutions transforming the financial landscape in the MENA region. The rise in digital banking in the MENA region has brought both opportunities and challenges, with the banks and financial institutions facing a surge in fraudulent activities such as credit card scams, money laundering, and identity theft. AI-driven fraud detection tools and risk management solutions have become a potent instrument, providing financial institutions the capacity to identify fraudulent activity instantly, anticipate possible risks, and improve operational efficiency. Beyond fraud prevention, AI assists institutions in promptly detecting suspicious transactions concurrently eliminating human errors, thereby boosting operational efficiency. 

As AI continues to evolve, its role in helping financial institutes and banks with fraud detection and risk management will only increase. Institutions that embrace AI-driven solutions will not only strengthen fraud detection and risk management but also improve operational efficiency and customer trust. The MENA region is leading this transformation by investing in AI-powered innovations. Through this, financial institutions can create a banking ecosystem that is safe, resilient, and prepared for the future.