The financial services sector is taking its first tentative steps on its journey into artificial intelligence (AI) with the technology predicted to change everything from the way financial institutions detect fraud to the way they serve customers.
By Dean Wolson, GM of the Infrastructure Solutions Group at Lenovo, Southern Africa
The bank of the future is likely to see more AI-powered talking avatars, reduced queue times and more efficiency for people looking for better deals on mortgages. The challenge for business leaders in the coming months is to work out where AI can deliver results, and how to implement it safely and effectively.
Business leaders in the sector already recognise the transformative potential of AI, with 50% of leaders in the banking, financial services and insurance (BFSI) sector seeing AI as a ‘game changer’ according to new research.
With expectations that the biggest impact of AI will be in intelligent automation and more personalised customer services, these technology pioneers are moving quickly – 67% have already invested in generative AI for use cases such as customer service chatbots.
The rewards are potentially enormous: used correctly, AI could add a significant amount in annual value to the banking sector, according to a 2023 McKinsey report.
The Promise of AI in African Banking
AI’s potential in banking extends across various dimensions, from improving customer service to enhancing risk management. In Africa, where financial inclusion remains a significant challenge, AI offers solutions that can bridge the gap and democratize access to financial services.
According to the World Bank, nearly 57% of adults in Sub-Saharan Africa are unbanked, lacking access to formal financial services. AI-driven solutions, such as chatbots, virtual assistants, and mobile apps, can provide personalized financial advice, budget management tools, and easy payment options, reaching underserved populations without the need for physical infrastructure.
Microloans and Creditworthiness
AI can revolutionize the microfinance sector by offering alternative creditworthiness assessments.
Traditional banking models often exclude individuals without a formal credit history, but AI can analyse non-traditional data sources, such as mobile phone usage and social media activity, to assess creditworthiness. This approach can extend financial services to millions who were previously considered un-bankable.
For instance, companies like Tala have leveraged AI to offer microloans based on smartphone data. As a result, they have disbursed millions of loans to underserved populations, demonstrating AI’s power to foster financial inclusion and economic stability.
Enhancing Customer Experience
In the competitive banking landscape, customer experience is paramount. AI-powered tools can enhance customer interactions, providing timely and efficient services.
AI-driven chatbots and virtual assistants are becoming commonplace in African banks. These tools can handle a wide range of customer queries, from account balances to loan applications, reducing wait times and improving customer satisfaction. For example, Absa Bank’s AI-powered chatbot, handles over 10 000 customer interactions daily, demonstrating the efficiency and scalability of AI solutions.
Predictive Analytics
AI’s data-crunching capabilities enable predictive analytics, giving banks insights into customer behaviour, market trends, and investment opportunities. This information allows banks to tailor their products and services to meet the diverse needs of their customers. AI further enhances risk management and fraud detection by analysing vast datasets in real-time to identify irregularities and potential threats.
The global cost of fraud in the banking sector is staggering, with the Association of Certified Fraud Examiners estimating losses of over $3.6 billion annually. AI algorithms can quickly detect unusual patterns and flag suspicious activities, preventing fraud before it occurs.
In Africa, banks like First National Bank (FNB) have implemented AI-driven fraud detection systems, significantly reduced fraudulent transactions and enhanced security.
Credit Risk Assessment
AI can improve credit risk assessment by analysing a wide array of data points, leading to more accurate lending decisions. This capability is crucial in Africa, where traditional credit data may be sparse or unreliable. AI-driven credit scoring models can incorporate alternative data, providing a more comprehensive view of a borrower’s risk profile.
Addressing Challenges
Despite its potential, AI adoption in African banking faces challenges, including concerns about job displacement, data privacy, and the digital divide.
The automation of certain banking functions may lead to job displacement. However, AI also creates opportunities for new roles focused on AI development, maintenance, and oversight. Upskilling the workforce to collaborate with AI systems is essential for mitigating the negative impacts and ensuring a balanced integration.
Another challenge is AI’s reliance on data, that raises ethical concerns about privacy and security. Robust data protection frameworks and transparent AI practices are necessary to safeguard customer information and build trust.
A Vision for the Future
Looking ahead, the future of banking in Africa is bright, with AI playing a central role in driving innovation and growth. In the next 5-10 years, we can envision a banking sector characterized by enhanced financial inclusion, reaching even the most remote and underserved populations.
Superior customer experience. Advanced fraud detection and risk assessment capabilities ensuring a secure banking environment. Lastly, we can expect informed decision-making for business leaders, thanks to predictive analytics providing valuable insights for strategic planning and customer engagement.