How Artificial Intelligence is Changing Banking – Financial Services Outlook 2024

Do you know what generative AI is? It’s all the trending applications generating text and visual content based on the AI model. The rise of generative AI in banking has reevaluated the approach to developing, for example, the source code, which is part of banking customer applications. The right prompt and a few clicks are saving an increased number of hours for developers working on solutions to improve the use of banking services. 

By producing valuable content in seconds, GenAI has a fundamental impact on the latest revolution in the banking market. As mentioned in the opening, data compiled by McKinsey estimates that generative AI tools can displace humans for up to 70% of their work time. In the same report, they state that increased productivity using AI allows for additional revenues of $200bn-$340bn across the banking industry. 

At the same time, full implementation of generative AI has the potential to reduce the finance industry costs by as much as 10% annually. According to Juniper Research sources, using AI-powered fraud detection solutions as early as 2027 would save as much as $10.4bn. Employees replaced by AI would not have to lose their jobs. On the contrary, they would stop spending most of their time on repetitive tasks and tackle areas of greater responsibility. The Accenture report estimates that productivity could increase by 20-30%. 

Properly leveraged, AI has the potential to enhance revenue streams and reduce risk exposures significantly. Let’s delve into some pivotal trends that drive this evolution. 

The digitalization happening in banking over recent years has somewhat eroded the traditional, strong ties between financial institutions and their customers. The rise in customer expectations for personalized services further exacerbates this challenge. With multiple banking relationships becoming the norm, customers increasingly seek tailored financial advice, especially as many navigate the complexities of financial planning. This creates a tremendous opportunity for banks to leverage AI to offer tailor-made financial advice. Such initiatives promise to rekindle customer relationships and amplify customer lifetime value by navigating them through their financial journeys with personalized insights and recommendations. 

Fraud prevention is another critical area where AI is poised to make substantial advancements. We will likely witness more widespread implementation and refinement of AI-based fraud detection and prevention systems in the upcoming months. Integrating biometric technologies with AI-enhanced anti-money laundering (AML) and know-your-customer (KYC) protocols will streamline those processes, significantly reducing the manual labor involved. By enhancing the accuracy of these algorithms, banks can look forward to minimizing losses due to fraud, curtailing operational costs, and diminishing the likelihood of human error in these crucial checks.

The rapid advancement of AI technology is outpacing the development of corresponding legislation, although Europe is leading the charge with initiatives such as the EU AI Act. Compliance is no longer the sole concern; AI introduces potential risks related to biases, discrimination, and handling Personally Identifiable Information (PII). Forward-thinking banks are thus closely monitoring regulatory developments, ensuring their AI innovations are not only compliant but also ethically and securely managing risks associated with data governance. 

Current AI trends in the banking sector highlight a dynamic landscape where technology drives opportunity and challenge. The industry is gearing up for a transformative era that puts the customer at the heart of its digital transformation initiatives. 

The digital transformation of your financial institution isn’t just about saving money, speeding up work, and new growth opportunities. Before AI technologies start performing tasks as well as humans, you have to deal with several challenges that arise at the beginning of AI implementation at financial services providers. 

Is your bank’s IT department not specialized in implementing AI processes and solutions? 52% of companies are not starting AI adoption due to a lack of expert talent. You would like to implement AI technologies as best as possible, but you are falling behind your competitors by doing nothing. If you’re having trouble hiring the right people, you can enlist the help of specialists offering outsourcing data and AI services. 

Are you worried that solutions based on artificial intelligence and machine learning will not work as presented by the manufacturers? Your concerns may be justified. One common problem that arises when using AI is the black box problem. It describes a situation in which AI creates output, leading to an incorrect decision. It is hazardous in the financial industry, as it can result in unexpected negative credit decisions. In this case, the lack of transparency in the decision-making process carried out by AI results in problems in determining which element led to the unsuccessful decision.

Banks and other financial institutions are environments consisting of many complex systems that interact with each other every day. In such environments, implementing AI solutions may seem like a huge challenge at first glance. However, you don’t have to do everything at once. Start with the elements AI can transform the most, such as marketing or customer service. The first successes and growing profits will motivate you to automate more business areas. 

When it comes to new technologies such as AI, you need to invest a lot of resources, strength, and time to implement these solutions in your company. It may not seem profitable to you initially because the models don’t work immediately. AI needs time to train on the massive amount of data before producing financial results. You can measure ROI in various ways to avoid disappointment, such as customer satisfaction, employee productivity, or software development progress.

As the financial sector increasingly embraces Artificial Intelligence (AI), significant mishaps related to faulty implementations have so far been absent. This is likely thanks partly to rigorous discussions on AI ethics and strict regulatory oversight. However, this is not to suggest a landscape devoid of challenges.  

For instance, a Canadian couple’s $21,000 loss to an AI-generated deepfake voice scam underscores AI-driven attacks’ sophistication and personal nature. It also highlights a rising trend in sophisticated phishing attempts that exploit both individuals and businesses. This calls for heightened public awareness and customer education. Such events also necessitate a robust response from banking entities to fortify their defenses and invest in innovative fraud detection technologies capable of countering such advanced threats. 

On the other hand, the Centre for Economic Policy Research (CEPR) uncovered instances of AI misappropriation, such as a GPT-4 powered AI engaging in insider trading breaching explicit instructions and ethical guidelines. This example highlights the potential for AI’s exploitation to undermine market integrity, accentuating the need for stringent safeguards. These protective measures must be comprehensive and rigorously evaluated to withstand potential breaches and exploitation tactics. 

Financial institutions can get the most out of AI capabilities. Starting with marketing activities, i.e., creating strategies, advertising campaigns, and social media posts that attract new customers. AI can also be an invaluable aid in creating new products based on insights gathered by the technology and developing existing offerings – from the marketing and programming side. 

The use of AI chatbots to communicate with customers who need answers to their questions is nothing new anymore. The bots are available 24/7, positively impacting brand perception for those who need an immediate answer. The adoption of AI allows brands to take care of their customers at all times, and the addition of advanced features even lets them perform money transfers or submit loan applications. AI applications also allow shared services to streamline operations and speed up the information flow. 

After a gentle introduction, let’s look at how banking institutions have already implemented AI strategies to optimize their processes. The first key reason is substantial cost savings and a significant reduction in TCO (even a 20% decrease). It is influenced by the ability to automate financial document analytics and claims processing. AI tools enable KYC process enhancement by creating personalized digital experiences for bank customers. Automating fraud detection is estimated to bring in about $31bn by the end of 2024. 

The already mentioned Accenture report estimates a 20-30% increase in productivity through the use of AI systems. Accelerated code development allows banking developers to deliver software even 40% faster and noticeably reduce tech debt. Internal and external data gathered through machine learning techniques enable the generation of accurate financial forecasts in three-quarters of the primary time amount. Data collected about customers and predicting their future needs based on them opens up further selling of additional products and services. 

The development of AI’s role is priceless in the case of risk management. At this point, credit risk is determined through advanced systems. However, it is vital to remember emerging AI laws, such as the EU AI Act, which regulate the safe management of data by artificial intelligence systems. 

Several leading companies are already showcasing groundbreaking applications of AI to their services. Here are just some highlights. 

OCBC Bank in Singapore has introduced a GenAI-powered chatbot for its 30,000 employees, significantly enhancing efficiency by assisting with administrative tasks, research, and coding. This innovation has led to a 50% increase in work pace, with plans to expand AI applications within the bank’s operations due to the successful outcomes observed. 

Similarly, ING has deployed a GenAI chatbot to elevate customer service standards in the Netherlands, achieving a 20% boost in assistance rates. The bank is poised to extend this technology to its 37 million customers across various markets following the encouraging results of the pilot phase. 

Bank of America’s virtual financial assistant, Erica, has recently surpassed 1.5 billion customer interactions. Erica offers comprehensive financial management tools, including day-to-day transactions, subscription management, and credit score monitoring, showcasing the bank’s commitment to leveraging genAI to enhance customer experience. 

These examples indicate the dynamic evolution of the financial sector through AI, hinting at even more sophisticated implementations in the near and distant future. 

At Scalo, we know what the financial services companies need. We offer AI-based solutions to streamline employees’ work, reduce rising costs, and guarantee satisfactory profits. You can ask us to conduct the ideation workshops. You can also hire our AI experts individually or whole AI teams. 

Our professionals have gained experience by developing software for many companies in the banking sector while facing numerous challenges and tailoring products to individual needs. You will receive software developed with insightful industry expertise by working with us. Products created by Scalo experts are based on Agile innovations, which, in the long run, will ensure your company’s stable growth and efficient resource utilization. In addition to functionality, we also care about the security and alignment of mobile banking and retail banking services with the laws in the area where you operate. Contact us today and let generative AI develop your business!