AI is revolutionizing global banking by predicting defaults, preventing fraud, and enhancing compliance. Ghana must adopt AI-driven solutions to strengthen financial stability and prevent future crises

International banks are increasingly turning to artificial intelligence (AI) to predict loan defaults, combat fraud, and strengthen regulatory compliance. By leveraging AI-driven solutions, these institutions are not only mitigating risks but also enhancing efficiency and resilience, ensuring they can withstand economic shocks and prevent systemic failures. 

Recognizing AI as a necessity rather than a luxury, leading banks worldwide are investing billions in the technology to stay competitive and secure, the McKinsey Global Banking Report, 2023 said. 

As the global banking landscape evolves at a rapid pace, Ghana’s financial sector faces persistent challenges, including high non-performing loans, fraud-related losses, and regulatory compliance gaps. To build a more stable and resilient banking system, Ghanaian banks can draw valuable insights from how AI is transforming financial institutions in advanced economies.

The risks facing the banking sector today are not new. History is filled with financial crises that exposed systemic weaknesses, from poor regulatory oversight to unchecked fraud. One of the most striking examples was the collapse of the Bank of Credit and Commerce International (BCCI) in 1991—a failure that underscored the devastating consequences of inadequate financial controls. This crisis, like many that followed, serves as a stark reminder of what happens when the banking system lacks resilience.

The collapse of the Bank of Credit and Commerce International (BCCI) in 1991 sent shockwaves through the global financial system. I first learned about this crisis during my early years, and its impact left a lasting impression. My grandfather, a retired banker, would pace our living room, clutching newspaper clippings with a deep sense of concern. His voice was heavy as he warned, “This is what happens when banks operate without proper oversight.” He spoke of money laundering, accounting fraud, and regulatory failures—concepts I didn’t fully understand at the time. But I could see the fear in his eyes and grasp the gravity of what had happened: thousands of people across multiple countries had lost their life savings overnight.

BCCI’s collapse wiped out $20 billion in assets and affected nearly a million depositors worldwide [Kerry & Brown, 1992]. The devastation was unprecedented, yet to my younger self, it felt like a distant crisis—one unfolding in faraway financial hubs like London and Luxembourg.

Since 1992 there have been several major bank failures underscoring weaknesses in the global financial system. The 1995 Barings Bank collapse resulted from unauthorized trading, while the 1997 Asian Financial Crisis led to multiple bank failures across Southeast Asia. The 2007 Northern Rock crisis in the UK exposed liquidity risks, and the 2008 global financial crisis saw the collapse of Lehman Brothers, Washington Mutual, and Iceland’s major banks due to excessive risk-taking and exposure to bad loans. In 2009, Anglo Irish Bank failed due to unsustainable property lending, contributing to Ireland’s financial crisis. These failures highlight the need for strong regulatory oversight, risk management, and financial stability measures.

By 2016, I found myself at the center of Ghana’s unfolding banking crisis. As a Relationship Manager, I had built a reputation for helping clients—friends, family, and colleagues—make sound investment decisions. Trust was at the core of my work, but that trust was soon shaken. 

In August 2017, what started as whispers of trouble at Capital Bank and UT Bank quickly escalated into a full-blown crisis. By 2019, nine banks had collapsed, along with 347 microfinance institutions and 23 savings and loan companies [Bank of Ghana, 2019].

The devastation was personal. Years of hard work vanished overnight—not just for institutions but for individuals. I watched as retired teachers, market women, and young professionals gathered outside closed bank branches, some in tears, others in frustration. More than GHS 21 billion in deposits were wiped out, affecting over 4.6 million Ghanaians according to the PwC Ghana Banking Survey, 2019.

One night, as news of yet another bank closure flashed across the TV screen, a troubling thought gripped me: Couldn’t someone have seen this coming? The question haunted me. In an era of rapidly advancing technology, why had we failed to prevent such a catastrophe? My search for answers led me to one key realization—banks in developed nations were already using artificial intelligence to prevent precisely these kinds of failures.

By 2023, Ghana’s Non-Performing Loan (NPL) ratio had reached 14.8%, indicating that nearly 15% of all loans were in distress. As businesses struggled to repay their debts, the resulting ripple effect destabilized banks, eroded customer savings, and slowed economic growth. In contrast, global banks have been tackling this challenge with AI-driven predictive analytics, allowing them to identify risks early and prevent defaults before they escalate.

JPMorgan Chase leverages AI-powered risk assessment models to analyze borrower behavior in real-time. By tracking spending habits, transaction patterns, and economic news trends, the AI enables the bank to proactively adjust lending terms, preventing defaults before they occur. This approach has reduced bad loans by 20%, saving billions. 

Similarly, OCBC Bank in Singapore has revolutionized SME lending with AI-driven alternative credit scoring models. Rather than relying solely on financial statements, the bank assesses mobile money transactions, e-commerce payments, and supplier records to evaluate creditworthiness. This has led to a 25% increase in SME loan approvals while maintaining low default rates.

In 2022, Ghanaian banks recorded GHS 67.4 million in fraud-related losses, driven by cyber fraud, ATM skimming, and insider corruption. Mobile money fraud alone accounted for GHS 26 million, with scams becoming increasingly sophisticated each year.

To combat such threats, HSBC has implemented an AI-powered fraud detection system capable of analyzing 500,000 transactions per second. For instance, if a Ghanaian customer makes a large withdrawal in Dubai just minutes after using an ATM in Accra, the AI system immediately flags the transaction and freezes the account to prevent financial loss.

Similarly, Wells Fargo has strengthened security with AI-driven biometric authentication, enabling customers to log in using facial recognition and voice ID instead of traditional passwords. This has led to a 30% reduction in unauthorized account takeovers.

In 2018, Ghana faced the risk of being blacklisted by the Financial Action Task Force (FATF) due to deficiencies in anti-money laundering (AML) compliance [FATF Ghana Mutual Evaluation Report, 2018]. Traditional compliance methods, often slow and labor-intensive, created loopholes that criminals could exploit.

To address such challenges, Deutsche Bank has adopted AI-powered compliance tools that scan millions of transactions in real time, identifying suspicious patterns before they escalate into legal violations [Deutsche Bank Annual Report, 2023]. Similarly, Standard Chartered has automated its Know Your Customer (KYC) verification process, reducing onboarding time from two weeks to just two days, enhancing both security and efficiency.

The traditional banking model is rapidly evolving, giving way to an AI-driven financial ecosystem. Ghana cannot afford to wait for another crisis before embracing this transformation. To build a more resilient banking sector, financial institutions within the country must:

When implementing artificial intelligence in banking institutions leaders need to watch out for various risks that may emerge.

The banking industry of Ghana stands to gain substantial benefits from AI implementation yet its deployment needs proper assessment of potential risks according to the World Economic Forum’s 2023 Banking Report. 

The security of sensitive financial data takes priority while data privacy requirements remain essential because financial institutions handle such information. Organizations in banking need to establish comprehensive security infrastructures which protect financial databases from unauthorized breaches and unauthorized access.

AI systems display the same biases as the training data they receive because biases can persist through algorithms thus banks must take steps to prevent discrimination against particular customer groups. The implementation of AI in banking requires substantial financial investments toward technological resources while developing skilled team members along with regulatory frameworks that structure its banking practice.

Banks must strike a strategic equilibrium to incorporate innovation techniques with their need to protect bank stability and customer trust in financial institutions.

With Ghana’s non-performing loan ratio still at 14.8% and fraud-related losses reaching GHS 67.4 million in 2022 alone, inaction is not an option. The technology to address these challenges already exists—what remains is the commitment to adopt and integrate it. Embracing AI-driven solutions can transform risk management, enhance fraud detection, and ensure greater financial stability for Ghana’s banking sector.

Having witnessed the BCCI collapse through my grandfather’s eyes and experienced Ghana’s banking crisis firsthand, I understand the devastating human cost of financial system failures. Yet, I also recognize the immense potential of AI to transform banking and prevent future crises.

To my colleagues in Ghana’s banking sector: the time for action is now. We owe it to the market women who lost their life savings, the young professionals whose aspirations were shattered, and the next generation who deserve a stable and trustworthy financial system.

The question is not whether Ghana’s banks will embrace AI—it’s whether we will do so before the next crisis strikes. The technology is here. Are we ready to use it?