Feature
Artificial intelligence (AI) is expected to reshape the banking industry, offering banks the ability to automate tasks, enhance operational efficiency and personalize customer experiences. The banking industry may be one of the industries most impacted by AI, displacing more than 50% of jobs, according to a report by Citi Global Perspectives and Solutions. Even without these severe impacts on the industry and labor, banks will need to navigate increased risks, maintain customer trust and avoid the pitfalls of over-adoption of a still-early technology. Here, we look at some of the top applications of AI that are catalyzing change in the banking sectors.
1. Digital Innovation
AI initiatives may require a shift in how banks approach innovation. A recent McKinsey study on AI in banking found that centralized operating models enhance the effectiveness of AI initiatives more than decentralized models or business-unit driven models. This may be, in part, because the systems design nature of AI adoption requires clear coordination. Those companies with high levels of organizational agility — or the ability to iterate quickly and match the fast pace of AI development — are thus far seeing the most success in the form of launched initiatives, regardless of their operating model.
2. Digital Transformation
AI initiatives are only as effective as the digital banking infrastructure supporting it. Banks that have not digitized their operations will face an uphill battle in an increasingly digital-first banking system. Digitization is already the “paradigm shift” of modern banking, and AI is accelerating the process. Smaller banks in particular must prioritize digitization if they want to compete with larger institutions.
3. Digital Differentiation
AI is likely to widen the gap between large and small banks. Large banks, with access to vast data troves, are well-positioned to capitalize on AI-driven automation and personalized services. In contrast, smaller banks — even those with successful digitization — may struggle to compete on the same level, resulting in their continuing to emphasize the human touch and local insights as their key differentiators.
Both types of institutions, however, may be able to creatively use AI to emulate the other’s strengths. Regional banks, for example, may use AI to address operational gaps that would typically require a big bank’s scale, such as advanced analytics or pseudo-admin assistance, which SouthState Bank in Florida implemented. Conversely, large banks are leveraging AI chatbots and other tools to recreate the personalized service traditionally offered by smaller banks. For example, Virgin Money saw success with a chatbot that emulated regional slang.
4. Fraud Detection
Deepfakes increased across fintech by 700% last year, according to a report by the identity verification platform Sumsub. The human-sounding abilities of AI will challenge established approaches for identity verification. Rather than focusing on evaluating web traffic or avoiding phishing attacks, bank security may become increasingly challenged by these social engineering attacks or scams of communication. In turn, verification may itself turn to use more generative AI tools, such as compliance around know your customer (KYC) practices.
5. Risk Management
Traditional risk management models often rely on broad, generalized data. AI, however, can provide more granular, nuanced assessments by analyzing a customer’s full financial history. Additionally, AI offers the ability to create “virtual experts” that add another layer of analysis to complement top-down algorithms. However, this increased granularity introduces potential risks, such as overfitting models to specific data sets or over-narrativizing predictions based on a narrow component of the prompt fed to the AI.
6. Debt Collection
The debt collection process is complex, juggling considerations of regulatory compliance, customer relations and financial recovery, while addressing challenges, like potential bias in decision-making and maintaining ethical standards. Many debt collection agencies are already using AI in some form. In the future, AI agents may likely handle most of the collection negotiation. Automated AI agents can tailor their communication strategies based on the debtor’s behavior and preferences, increasing the likelihood of successful collection while maintaining a positive customer relationship. However, this area will likely be the focus of significant regulatory scrutiny, given ongoing concerns about bias and aggressive practices.
7. Analytical Insights
AI democratizes access to data by enabling non-technical staff to perform complex data analysis and initiatives. This bottom-up analysis allows banks to be more responsive to market changes and provides better insights for centralized innovation strategies. Investing in long-term team resources and providing clear strategic direction are essential parts of any AI initiative. By building a company-wide strategic collaboration — like Scotiabank’s “ethically engaged AI culture” — teams are able to own new AI-empowered domains.
8. Automated Customer Service and Support
AI chatbots are revolutionizing banking customer service by providing instant, around-the-clock support. Banks, like Bank of America, are seeing significant increases in chatbot usage. Bank of America’s “Erica” bot passed 1.5 billion client interactions. Nearly 50% of bank executives expect to, or are using, chatbots as part of their plans.
However, widespread chatbot adoption can also result in frustrating and annoying customer experiences. In fact, it’s become such a headache that The White House asked the Consumer Financial Protection Bureau (CFPB) to investigate and address customer pain points across a variety of industries, including banking chatbots.
9. Hyper Personalization
It’s all about the product offering now. Reactive banking is "dead," Forbes says. Banks that can most effectively identify new, personalized opportunities for their customers — using AI to deliver tailored offers at precisely the right moment — are more likely to succeed. Customers consistently prioritize a wide variety of financial products, and AI-generated, personalized outreach of the future should increase engagement and retention. However, new financial instruments and offers will face stricter regulations, with a likely emphasis on customer protections.
