As we celebrate 25 years of the digital revolution in banking, it’s evident that the industry has undergone fundamental transformations. Branches witness significantly reduced foot traffic while the use of cash dwindles amidst the rise of new payment methods. Agile startups and tech giants have entered banking, reshaping competition dynamics.
Now, on the cusp of another transformative era, the convergence of artificial intelligence (AI), data processing, and cloud computing heralds unprecedented opportunities. We stand at the dawn of the Age of AI, evoking a sense of awe akin to a quarter-century ago.
Banking, inherently a business of digital transactions and trust, stands to reap unparalleled benefits from AI adoption. While AI won’t alter banking’s core functions, it promises to revolutionize its operational landscape.
In this article, we will delve into top banking technology trends that need to be looked for in 2024.
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The Rise of Generative AI
In 2023, virtually every bank embarked on experimental ventures with Gen AI, with many noting remarkable outcomes. The subsequent 12 months are poised to witness expanded adoption across various organizational domains, with more ambitious institutions utilizing it as a cornerstone for comprehensive reinvention.
According to a report, Generative AI in banking stands to gain the most compared to other industries, potentially experiencing a productivity surge of 22-30%.
Source
Nevertheless, the most significant impact of Gen AI in banking is projected to be on revenue and productivity growth, as per Accenture. Integrating Generative AI in banking processes like fraud, risk management, data privacy, risk analysis, sales, and customer interaction could yield a 6% revenue increase within three years. But, the crux of achieving this growth lies in an AI strategy prioritizing the workforce. -
Capturing Digital Dividend
Most banks have honed their digital customer experience, emphasizing service excellence. Accenture’s Global Banking Consumer Study 2023 shows that banking customers have used branches more often than other channels in the last 12 months.
However, envision a scenario where banks could transform these digital touchpoints from dead-ends into meaningful conversations and subsequently into sales opportunities, all without expanding staffing for interpersonal interactions. Solutions like Intelligent Document Processing can extract data from these digital touchpoints, interactions, service tickets and others to accumulate the data into the system.Banks can personalize interactions with each customer by leveraging their extensive repositories of consumer data in conjunction with AI chatbots. Using AI can enable banking organizations to create an ecosystem that can help customers check their account balances at a glance, register applications for loans, and get a tailored customer experience.
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The Risk Unseen
As per Accenture’s latest risk Survey, 72% of senior banking risk professionals said their organization’s risk management capabilities and processes have failed to keep pace with the rapidly changing risk landscape.
While risks may seem obvious in hindsight, identifying them in real-time proves challenging, if not impossible. Banks must enhance their risk planning for unforeseeable risks using AI and automation tools that can analyze and detect synthetic data and update detection algorithms to stay ahead of the evolving fraud schemes. Also, by utilizing historical data, Generative AI can identify and acknowledge potential financial risks, providing early warnings on fraudulent activities.
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A New Era of Working
In the era of the digital revolution, banks primarily resorted to hiring to fill skill gaps in critical areas. However, with the impending impact of AI on virtually every job within every layer of a bank, traditional hiring approaches are insufficient. A completely novel strategy is imperative.
To capitalize on this transformative opportunity, leaders must envision a fresh approach to the collaboration between humans and AI. It’s crucial not to underestimate the importance of human interaction in maintaining the bank’s human touch with customers. Employees must adapt to working alongside AI, emphasizing customer availability, nurturing relationships, and displaying authentic empathy.
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The Power of Pricing
Understanding the impact of pricing is fundamental in banking, as even a slight adjustment can yield significant repercussions. The challenge lies in accurately anticipating these outcomes. In theory, there exists an optimal price for every customer, product, and channel combination.
Generative AI simplifies the process for banks to identify these optimal prices. By analyzing thousands of variables, it swiftly generates targeted pricing strategies. Subsequently, it incorporates the results into its calculations, enabling banks to refine their pricing further. Through millions of iterations and continual learning, banks can progressively approach the ideal price point.
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Regulations Control
The regulatory landscape continues to evolve, with new legislation addressing AI and sustainability underway in various jurisdictions. While regulation is essential for the integrity of financial services, the sheer volume doesn’t necessarily equate to improved outcomes. Achieving a balance between regulatory oversight and operational feasibility is crucial. As per the Accenture report, only 26% of banking CEO have a future-ready strategy. Collaboration between regulators and banks is paramount to ensure regulators obtain necessary information without imposing excessive burdens or costs.
In 2024, striking this balance remains a pivotal challenge. Utilizing automation and digital solutions can enable banks to reduce the amount of time required by full-time employees to perform compliance tasks. It can have various advantages for the organization;. At the same time, the process becomes more efficient, the resource can be shifted from having to collect data to having to analyze the risk score to determine if the client should be onboarded or not.
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Think of Cloud First
The demands of AI in terms of computing power and data storage make it extremely challenging to achieve sufficient scale through on-premises infrastructure alone. Consequently, cloud computing has transitioned from being considered a luxury to becoming a necessity in 2024.
As banks gain firsthand experience with cloud technology’s capabilities, cloud migration support will grow across both IT departments and business leadership. A shift towards a cloud-first approach will become prevalent, with banks adopting standard, open operating systems that facilitate seamless integration between on-premises and cloud environments. This integration will streamline the application migration process, making it as straightforward as sending an email.
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Transition from Technology to Engineering
Transitioning from technology to engineering, the evolving landscape of banking technology prompts a critical question: what transformations await the IT function? Generative AI, cloud computing, and composable apps exert pressure to reassess the traditional 70:30 budget allocation between operational and innovation costs.
This paradigm shift influences not only the mindset of IT teams but also resonates with bank leadership. Banking technology teams should gravitate towards closer alignment and potential integration with business operations. Their primary focus will shift from infrastructure maintenance to actively contributing to the invention, scoping, and development of new Products and solutions. Technologies like ticket intelligence can enable the banking industry to look for more automation opportunities in their IT functions.
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The Key to Core
Bank’s core system has become more fragile and complex, leading to vulnerabilities. With their dependency on outdated COBOL codes to handle banking data, making the changes is difficult. As banks tried to make business more digital and user-friendly, the processing volume has surged, and the pool of experts familiar with legacy systems has dried up. As a result, banks opted for minimal upkeep, which has hindered their ability to adopt new technologies.
In 2024, modern technologies like Generative AI offer a way out of the traditional banking system. Generative AI can help banks decipher their old COBOL code and transform it into contemporary language. As per Goldman Sach’s report, around 40% of code generation is completed using generative AI. Indeed, Generative AI can potentially remove the biggest obstacles to banks resolving their legacy burden.
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Beyond Six Sigma
Looking back over the past twenty-five years, banks have maintained remarkably consistent cost-to-income ratios (CIRs), typically within the 50-60% range for most institutions.
However, we anticipate significant shifts in 2024 as executives turn to technology to reshape the cost curve permanently. Historically, banks relied primarily on quantitative approaches to address operational challenges. The emergence of generative AI introduces a new dimension by enabling the resolution of qualitative issues that previously necessitated human intervention.
This transformation can redefine banks’ cost structures and establish a new standard for performance excellence.
Conclusion:
In conclusion, the banking industry is at the cusp of transformative change driven by disruptive technologies such as Generative AI, digital banking, regulatory compliance management, shifting to cloud, and others. As we navigate the complexities of a digital-first economy in 2024 and beyond, banks must embrace innovation, agility, and collaboration to harness the full potential of emerging technologies and deliver unparalleled value to customers while ensuring regulatory compliance and data security. By staying abreast of these top banking technology trends, banks can position themselves as frontrunners in the ever-evolving financial services landscape, driving sustainable growth and competitive advantage in the digital age.