Top five AI trends the banking world could see in 2024

Artificial Intelligence is rapidly revolutionizing the banking sector, and 2023 saw a notable surge in the adoption of these technologies, especially in the realms of fraud detection and elevating customer satisfaction. The data-intensive environment of banking provides an ideal context for the swift and effective implementation of AI.

Entering 2024, a swift increase is anticipated in both the utilization and effectiveness of AI in its current domains. Banking is poised to remain a leader in implementing AI in practical, real-world scenarios.

Gen AI for banking

The rise of generative AI has the capability to usher in a wave of innovation, efficiency, and personalization for both banks and their clientele. This has the potential to revolutionize the delivery of banking services, introducing novel and distinct offerings, streamlining operations, and reshaping the way users interact with banking services.

According to McKinsey, this technology holds the promise of generating an additional $200 billion to $340 billion annually within the banking sector. These gains would primarily arise from enhancing backend processes to achieve greater efficiency. Customers can also anticipate improved support and an elevated standard of banking services and experience.

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Use of responsible AI

With the increasing prevalence of AI in banking and finance, it is essential to deploy AI models that are genuinely explainable. These models should be easily comprehensible, subject to scrutiny, and adjustable by both business professionals and regulatory bodies. Furthermore, the outcomes of these models should be clear and accessible for everyday users to understand and analyze.

Ensuring that the outcomes of these models are impartial, devoid of favoritism towards any customer group or demographic, and guaranteeing fairness and safety is crucial. Embracing responsible AI practices is the sole means to ensure its widespread adoption in the banking sector.

Governance through AI

Across the globe, governments and regulators are prioritizing the establishment of robust AI governance to harness the complete potential of AI. This involves viewing AI as a potent technology that must be both powerful and safe, subject to appropriate regulations. The overarching goal of this approach is to guard against any unintended consequences.

With the increasing prevalence of AI in diverse banking and financial institutions, there will be a rising need for stringent governance and compliance processes to guarantee its secure utilization.

Financial wellbeing with AI

Explainable AI has the potential to play a vital role in helping banks and financial institutions attain financial well-being. This encompasses responsibilities such as managing backend processes, forecasting intra-day liquidity, conducting sentiment analysis, and more.

Customers will also benefit from capabilities like predicting cash flow, providing assistance during financial challenges, aiding in selecting the appropriate mortgage, and offering wealth advice. Explainable AI will contribute to maintaining stable financial markets and ensuring robust financial support for banking customers.

Leveraging more data

With the continual expansion of the Internet of Things (IoT) and social media, an increasing amount of data becomes available regarding the banking industry and its customers. AI can play a pivotal role in extracting valuable insights from unstructured social media data and extensive volumes of IoT data, merging this information with customer banking data.

This empowers banking applications to aid and support both banks and their customers in diverse ways, laying the groundwork for the development of innovative and distinctive services that have the potential to reshape the future of banking.

AI is also ready to take over the medtech scene

AI has proven itself in healthcare, predicting genetic diseases, improving cancer treatments, and creating vaccines that can handle various variants. It’s a game-changer for addressing significant healthcare challenges.

“In 2024, we will see significant strides made in the field of techbio, particularly in the promising area of generative AI for drug discovery,” Dr Diana Rottger, Principal at APEX Ventures, tells TNW. Dr. Röttger thinks more companies in the field will be diving into clinical development soon, using both computer-based and real-life approaches. The drive for improved diagnostics is expected to continue, especially with the assistance of large language models capable of handling vast amounts of information.

“AI algorithms can analyse vast amounts of medical data, including patient records, genetic information, and imaging results,” says Dag Larsson, CEO and founder of Doccla, a healthtech startup providing a virtual hospital ward. “By identifying subtle patterns and correlations that may not be visible with smaller datasets, AI can therefore assist in the early detection of diseases. This can lead to more accurate predictions and insights, particularly in complex and heterogeneous patient populations.”

Julia Hawkins, a key player at the VC firm LocalGlobe, mentions that another trend revolves around relieving the pressure on the healthcare system.

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AI in cancer care

AI represents a significant improvement over older technologies in several aspects. It becomes more precise as it processes more data, enhancing accuracy and detecting subtle differences among different groups, such as ages or races. Additionally, it’s straightforward to set up, starts working immediately, and can be deployed on the cloud, which is nearly ubiquitous.

Capitalizing on these benefits, AI can be implemented universally, guaranteeing top-notch treatment for everyone, regardless of their location. It’s akin to supercharging personalized care for a much broader demographic than ever before.

An intriguing development revolves around employing AI in novel tests to predict tumor growth and assess treatment efficacy. These tests utilize smart programs to examine images of patient tissue samples in conjunction with their medical data. As a result, doctors can use this information to devise a personalized treatment plan for each individual, occasionally avoiding treatments that might pose more harm than benefit.