Embracing emerging technologies, particularly artificial intelligence (AI), has become crucial for driving growth in today’s competitive banking landscape. Indeed, sectors embracing this technology are seeing nearly five times the productivity rise of those less exposed. Yet, in highly regulated industries like finance, the transformative potential of AI clashes with deep-seated concerns over compliance, bias, and security.
This hesitancy risks leaving significant value untapped. The key to unlocking AI’s full potential lies in blending the technology with existing human expertise. In doing so, organizations can navigate regulatory hurdles, mitigate risks, and drive innovation.
An innovation journey from admin tasks to customer delight
The expansion of generative AI in recent years has encouraged senior leaders to more seriously consider AI’s overall potential for their business. Whilst it can be tempting to think of AI as synonymous with the chatbots that millions of people now use daily, many of the technology’s enterprise applications have been around for much longer. The global banking sector is a good example of this, having leveraged traditional AI for data operations like classification and process automation for many years.
Generative AI promises to build on established machine learning (ML) approaches, with the added capability of generating creative, novel outputs. At present, many conventional AI tools are intended to support the backend of an organization, designed to reduce administrative burden for employees and therefore liberate their time for creative tasks.
As generative AI matures, it is likely to become more customer-facing. Potential use cases include developing more effective fraud detection systems for instant and cross-border payments or automating loan decisions to expand access to under-served populations.
Predictive analytics powered by generative AI can also help banks in risk management and fraud prevention. By analyzing patterns in transaction data, AI systems can identify potential fraudulent activities much faster and more accurately than traditional methods. This not only protects customers but also saves banks significant resources that would otherwise be spent on investigating false positives. Balancing machines with the invaluable human touch will be pivotal in advancing such implementations.
Blending human and artificial intelligence to unlock innovation
AI has a pivotal role to play in empowering growth, with the banking sector standing to benefit the most of any industry thanks to an annual revenue increase potential of $200 billion to $340 billion. However, at present, only 12% of firms have sufficiently developed their AI capabilities to drive significant expansion and transform their business operations. Achieving AI maturity requires a full-scale AI deployment strategy, including elements such as a robust data strategy, adequate technology infrastructure, and crucially, a plan for the organization’s people.
Introducing a new technology requires significant education and awareness-raising amongst the workforce. Leaders cannot assume that their people will possess the requisite skills; a mere one in seven (14%) UK workers have used generative AI in their professional lives to date.
Organizations must recognize that the integration of advanced technologies isn’t just about implementing new systems, but rather cultivating a workforce capable of leveraging these tools to their full potential. Employees should therefore have access to comprehensive training initiatives that cater to various skill levels and job roles. Beyond this initial training, organizations must foster an environment that encourages ongoing education and experimentation with generative AI tools.
Equally, given the heavily regulated nature of the financial sector, banks must address the regulatory challenges associated with generative AI deployment. For example, data privacy and security are critical concerns. As AI systems often require large amounts of data to function effectively, banks need to ensure they are collecting, storing, and using this data in compliance with regulations like GDPR or CCPA. Implementing robust data governance frameworks and leveraging privacy-enhancing technologies can help address these concerns while still allowing for the effective use of AI.
By taking a proactive and people-centric approach to generative AI adoption, organizations can ensure that their workforce is well-positioned to leverage these tools for enhanced productivity, creativity, and innovation. This strategy should also account for regulatory concerns to allow banks to retain trust with both regulators and customers. In doing so, leaders can ensure that AI never stands to replace the innate creativity and problem-solving capabilities of their employees.
Reshaping industries through platform-driven transformation
AI has the power to transform industries when applied to appropriate use cases by skilled staff. The technology sector, accustomed to ongoing advancements, has enthusiastically adopted AI. It’s already exploring sophisticated applications, particularly in the realm of generative AI. For the banking industry to follow suit, organizations will need to embrace a platform-driven approach.
Already, banking-as-a-service (BaaS) offerings are gaining traction, as evidenced by the fact that nearly half (42%) of consumers are now utilizing Buy Now, Pay Later (BNPL) services. This alternative payment option allows consumers to pay fractionally for their purchases, spreading the cost over a longer period.
Such tools are facilitated by BaaS, a model that enables non-banking entities to provide financial products through an application programming interface (API)-driven platforms, integrating banking capabilities into their offerings. Thanks to BaaS, the finance sector has seen the rise of platforms that consolidate various financial products from a range of institutions into a single, accessible space, therefore streamlining money management for businesses and individuals.
The convergence of AI and BaaS presents a transformative opportunity for financial services. AI technologies can be seamlessly integrated into BaaS platforms, providing everything from more sophisticated risk assessment models to personalized financial products. For example, AI could further personalize BNPL services, or detect fraudulent activities in real-time. By combining these innovative technologies, organizations can lead the way toward a more inclusive financial ecosystem.
As we look to the future of banking, it’s clear that AI will play an increasingly important role. Throughout its deployment, leaders should ensure that their workforce is prepared for the change. The key to success lies not in replacing human expertise, but in encouraging employees to use AI to enhance their creativity and problem-solving skills. While AI can process vast amounts of data and identify patterns that humans might miss, it’s the human touch that provides context, empathy, and ethical judgment. Combined with a platform-driven approach, financial organizations are well-placed to innovate, creating value for both internal stakeholders and customers alike.
