Introduction

The rapid evolution of artificial intelligence (AI) has been a driving force in reshaping industries across the globe. As we step into 2024, the anticipation for groundbreaking AI trends reaches unprecedented heights. On top of that,  banks and financial institutions (FIs) find themselves at the forefront of this technological revolution, navigating a complex intersection of innovation and financial services. In this article, we will explore the top 4 popular AI trends that are projected to shape the future of AI in 2024. Additionally, we will discuss how these AI trends can benefit banks and financial institutions. This understanding is not just about technological prowess but a strategic investment in the future of financial services.

1. Quantum AI

Quantum AI is an interdisciplinary field that combines principles from quantum computing and AI. In other words, it harnesses the principles of quantum mechanics to revolutionise AI by enabling the development of more powerful AI models capable of processing vast amounts of data and performing complex calculations at an unprecedented speed. This will have a significant impact on various industries, including finance, healthcare, logistics and more.

In the finance context, Quantum AI can significantly impact portfolio optimisation by handling complex mathematical computations involved in analysing multiple investment scenarios simultaneously. For instance, Goldman Sachs and AWS have released a detailed end-to-end assessment of a quantum algorithm for portfolio optimisation, which is a revealing case study on the utility of quantum algorithms. Besides that, Quantum AI provides banks and FIs with the ability to predict market trends and assess potential risks with unparalleled accuracy. Woerner and Egger have proved that a quantum algorithm analyses risk more efficiently than Monte Carlo simulations traditionally used on classical computers, offering a more accurate and efficient approach to risk assessment. 

On top of that, Google has developed Google Quantum AI, a division of Google that is focused on advancing the state of the art in quantum computing and developing the hardware and software tools to operate beyond classical capabilities. The potential applications of Google Quantum AI in finance and banking are significant, including portfolio optimisation, risk assessment, and more. However, the adoption of quantum computing in finance and banking is still in its early stages, and there are significant challenges to overcome, including data quality and security concerns.

2. Generative AI

Generative AI refers to a class of artificial intelligence systems that have the ability to generate new content, such as text, images, audio, or other forms of data. ChatGPT, Google Bard, MidJourney and Bing AI are some of the examples of generative AI that are widely utilised by individuals from different industries nowadays. 

A report by MarketResearch.biz forecasts that the global market size for generative AI in financial services will soar to around USD 9,475.2 million by 2032, a substantial increase from USD 847.2 million in 2022. This growth is expected to be driven by a Compound Annual Growth Rate (CAGR) of 28.1% during the period from 2023 to 2032. The potential of generative AI in the finance and banking sectors is substantial, with McKinsey & Co. reporting that on an annual basis, generative AI could add between $200 billion and $340 billion in value (9%-15% of banks’ operating profits) if the use cases are fully implemented.

In particular, generative AI can automate the tedious task of report generation for financial analysts, allowing them to focus on more strategic aspects of their work. Moreover, generative AI can even provide clients with tailored market insights, and more sophisticated credit risk assessment through analysing large datasets to identify patterns, trends, and correlations. Banks and FIs can even adopt explainable and automated Machine Learning (AutoML) and AI platforms that can make predictions through analysing vast amounts of historical data. As a result, generative AI can assist banks and FIs effectively improve efficiency and profitability over time.

3. Composite AI

Composite AI, which involves the combination of multiple AI techniques to create more powerful and accurate AI systems, is anticipated to be a significant trend in 2024. It leverages various AI and analytic techniques, such as machine learning (ML), deep learning, natural language processing (NLP), computer vision, descriptive statistics, knowledge graphs to improve AI systems’ learning level of “common sense” and ability to solve a wide range of business problems. 

Composite AI can enhance existing rule-based systems by combining techniques such as NLP, machine learning, and deep learning to detect fraudulent transactions more accurately and efficiently. Dr Bernd Schopp also asserted that composite AI can help banks and FIs manage and mitigate risks more effectively and even improve the sales pipeline. This clearly shows that banks and FIs truly require an AI-driven platform that combines ML techniques to make intelligent business decisions and gain insights.  

4. Edge AI

Edge AI brings the power of AI to the edge devices, such as smartphones, tablets, and Internet of Things (IoT) devices. Unlike traditional AI models that rely on centralised cloud computing, edge AI processes data locally on the device, providing real-time insights and reducing the need for constant connectivity. According to Grand View Research, the global edge AI market size was valued at USD 14,787.5 million in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 21.0% from 2023 to 2030. This clearly indicates that edge AI is projected to be a prominent trend in 2024.

Edge AI can enhance real-time fraud detection by processing data directly on devices, allowing for immediate response to potential threats without relying on centralised systems. In mobile banking applications, it enhances user experiences by locally analysing behavior and preferences, ensuring a seamless and personalised interface. This enables customers to effortlessly leverage AI on their devices, assisting banks and FIs in accelerating the time-to-market for their financial products and facilitating cross-selling. Moreover, edge AI facilitates seamless customer onboarding by processing and analysing data directly on users’ devices. By harnessing the power of edge AI, banks and FIs can offer a more efficient and user-friendly onboarding experience.

In Conclusion

It is essential for banks and FIs to stay informed about these trends in order to leverage these advancements to drive innovation and improve operational efficiency. In order to do so, banks and FIs can wisely exploit the potential of AI by implementing JurisTech’s explainable automated ML and AI platform. Banks and FIs can seamlessly integrate our autoML platform  to their operations to effortlessly make predictions and intelligent business decisions. As banks and FIs embrace these transformative AI trends, it becomes evident that staying abreast of technological innovations is not merely an option but a strategic necessity. The convergence of these trends reflects a commitment to efficiency, innovation, and customer-centric solutions, paving the way for a dynamic and promising future in the finance and banking industry. 2024 presents unparalleled opportunities for those willing to embrace and harness the potential of AI.

About JurisTech

JurisTech (Juris Technologies) is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, telecommunications, and automobile companies in Malaysia, Southeast Asia, and beyond.