Is AI the Master Key to Banking’s Next Era?

For banks and financial institutions (FIs), systemic adoption of artificial intelligence (AI) technologies is perhaps the industry’s most formidable litmus test of adaptability since the global embrace of digital banking in the 1990s. On one hand, embracing AI could lead to unparalleled efficiencies and granular insights, offering a competitive advantage over those slower to adapt […]

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For banks and financial institutions (FIs), systemic adoption of artificial intelligence (AI) technologies is perhaps the industry’s most formidable litmus test of adaptability since the global embrace of digital banking in the 1990s. On one hand, embracing AI could lead to unparalleled efficiencies and granular insights, offering a competitive advantage over those slower to adapt in a market increasingly defined by advanced digital-first strategies. On the other hand, effectively achieving this transition within a competitive time frame requires that banks overcome a multiplicity of challenges regarding the use of AI tools — including earning consumer trust, meeting regulatory compliance, and countering the inherent advantage Big Tech companies hold in building and deploying the advanced solutions they are now using to enter the financial space.

• The AI Effect: Transforming Banking From Within
• From Transactions to Interactions, Can AI Make Banking Better?
• Decoding the Challenges Banks Face in AI Integration
• Finding the Keyhole: Where AI Meets Banking’s Locked Doors

The AI Effect: Transforming Banking From Within

As banks and FIs increasingly implement AI tools, the financial industry’s morphology will rapidly undergo unprecedented change. All facets of the industry, from how leaders strategize and operate to how the labor force carries out tasks, will be touched by this transition.

From detecting fraud to delighting customers, AI has use cases in the industry.

AI’s applications within the financial industry are strategically significant and notably varied. Nearly three-quarters of finance leaders report currently using AI, in roles including fraud detection (64%), risk management (64%), investment management (57%) and automation (52%). Meanwhile, 42% of banking chief experience officers see AI’s potential to automate customer onboarding, including know-your-customer (KYC) procedures, as its top use case, with 25% saying their chief aim in using AI is to create better customer experiences. These perspectives highlight AI’s broad potential to sculpt the future of the financial industry.

Nearly every bank’s board now stamps ‘yes’ on generative AI.

An Ernst & Young survey finds, moreover, that almost all banks and FIs are already using or planning to use generative AI, with 55% of the industry’s leadership feeling optimistic about it. The potential benefits of this usage are already widely recognized by leadership, including the creation of new offerings and hyper-personalized marketing (38%). Additionally, 91% of bank boards have endorsed generative AI initiatives, underscoring the industry’s awareness of its strategic importance. These trends are in their infancy, but they signal a significant ongoing transition toward broad-based usage of AI solutions to improve operations in the banking industry.

The industry’s workforce faces an AI overhaul, ready or not.

AI is rewriting the work schedules of banking professionals. Recent research by Accenture shows that AI will soon handle tasks that historically occupied nearly three-quarters of a bank employee’s day. From Citigroup’s 40,000 software developers getting the green light to experiment with AI tools to BNY Mellon analysts leveraging AI for research preparation, banks and FIs are only just beginning to scratch the surface of AI’s place in the workforce. In doing so, however, they could be setting in motion profound structural changes to the industry’s labor profile. As tasks are redefined and workflows optimized, banks and FIs may have to navigate the complex intersection between AI usage and workforce transformation.

From Transactions to Interactions, Can AI Make Banking Better?

Pain points threaten to drive nearly half of United States retail banking consumers into the arms of Big Tech for their financial needs. Can AI deliver on the promise of revolutionizing the retail banking experience for good?

In the customer service arena, AI remains an ace up banking’s sleeve.

Superlative customer service is a cornerstone of best banking practices, yet the potential of AI tools to facilitate more memorable customer experiences remains largely untapped by most banks and FIs. A recent Syntellis survey revealed that just 12% of FIs currently utilize AI for customer service. However, fully half say they will adopt AI tools specifically focused on personalizing customer experiences within 12 to 18 months, making it the top projected growth area for AI use in banking.

Intelligent virtual assistants stand ready to replace chatbots.

Intelligent virtual assistants (IVAs) are AI-driven superpowered chatbots that are gaining traction in the financial industry, with 72% of retail banking consumers recently expressing a preference for them over traditional chatbots. As banking consumers crave personalized experiences and 67% of finance leaders target customer service as a key area for AI usage, tools such as these are ripe candidates for the industry’s innovation agenda.

In the shadow of Big Tech, banks and FIs find hope in AI.

Nearly half of all retail banking consumers view Big Tech’s personalized and seamless experiences as more appealing than those offered by traditional banks and FIs. Confronted with this threat, traditional banks are turning to AI-driven solutions such as IVAs to improve their experiences. However, while 83% of banks recognize the critical link between customer experience and loyalty, just 45% plan to ramp up investments in these next-generation technologies. This disconnect is partly explained by the complex obstacles banks must overcome to implement these solutions.

Decoding the Challenges Banks Face in AI Integration

The path to realizing AI’s potential for the financial industry is laden with hurdles, from technology and cybersecurity challenges to consumer mistrust.

AI in banking has yet to win consumer trust.

U.S. consumers harbor substantial skepticism about AI usage in the financial industry. Twenty percent believe AI tools pose an extreme risk of fraud or security breaches, with anywhere between 14% and 26% refusing outright to use AI for financial-related purposes, depending on the application. Although significant, these shares nonetheless represent a relatively thin slice of all retail banking consumers. More telling are the numbers of consumers actually using AI banking tools: Just 21% do, while 57% hesitate to rely on AI-generated financial advice. This highlights the critical challenge for banks of bridging the trust gap between consumer perceptions and the reliability of AI banking tools.

Banks’ AI dreams battle cybersecurity nightmares.

The financial industry itself faces monumental internal obstacles that compound the complexity of adopting AI technologies. Thirty-seven percent of banks and FIs worry that AI integration could amplify their vulnerability to cyberattacks. Even leadership is not immune to such worries, with 12% of finance leaders confessing to a measure of unease, largely stemming from a limited understanding of the technology as well as the prevailing uncertainties about regulation and safety. These concerns, magnified by consumer skepticism, hint at the colossal challenges the financial industry must overcome.

Structural hurdles call for bold moves.

The way to AI integration in finance is also barred by structural challenges. A recent survey by Nvidia finds that 38% of banks and FIs view data issues, including the tangled nexus of privacy, global data distribution and disparate regulatory regimes, to be the biggest obstacle to harnessing AI’s full potential — up from 28% last year. Moreover, 39% worry they are underinvesting in AI infrastructure, while 32% struggle to secure and retain domain-specific talent. These issues are deeply structural, suggesting that a systemic revamp — addressing both infrastructural and human capital deficiencies — is required for banks and FIs to achieve widespread AI usage.

Finding the Keyhole: Where AI Meets Banking’s Locked Doors

The extraordinary utility of AI tools to modernize and improve almost every aspect of financial services is already evident. Widespread adoption, however, is slowed by challenges ranging from technical integration hurdles to regulatory and consumer trust barriers. These obstacles heighten the complexity of implementing AI solutions — but solving them is quickly becoming the master key that will open the door to FIs’ long-term viability.

PYMNTS Intelligence offers the following actionable roadmap for banks and FIs to get started:

• Implement hyper-personalized financial health platforms: Hyper-personalized financial health tools offer immense potential to garner consumer trust. By leveraging AI to provide tailored insights and advice based on individual transaction data and financial goals, banks can demonstrate the tangible benefits of AI and thereby boost consumer confidence in using the technology.
• Revolutionize fraud detection with AI-enhanced kinetic user authentication: Introducing AI-driven kinetic user authentication could help address consumers’ security concerns head-on by offering a novel, highly secure method of verification that is both difficult to replicate and deeply personal. This biometric authentication method would utilize the unique kinetic patterns of mobile banking consumers as they interact with their devices to augment existing authentication methods, showcasing AI’s potential to create safer banking experiences.
• Advance predictive risk management with AI: Evolving risk management into a predictive, AI-driven framework offers a forward-thinking solution to both current and emerging threats. By deploying AI for deep analysis of market trends and cybersecurity data, banks can proactively identify potential risks before they manifest. This strategy not only enhances the security and resilience of financial operations but also builds a foundation of trust with consumers.
• Form strategic innovation alliances: The complexities of AI usage in the financial industry underscore the importance of collaboration across the financial ecosystem — from banks and FIs to FinTechs and even large technology companies. By emphasizing cooperative development over competitive standoffs, these partnerships could accelerate industrywide adoption of secure, effective and compliant AI tools that meet the stringent demands of consumers, regulators and industry insiders themselves.

Banks and FIs stand to unlock unprecedented levels of personalization, risk management and operational efficiencies through the use of AI. Careful curation and stepwise implementation of AI-based solutions will ensure the technology’s effectiveness as a key to banking’s future success.

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