The banking industry is on the cusp of a transformation driven by generative AI, a technology that promises to reshape customer experiences, risk management, and operational efficiency. This week for CDO Insights we have with us Devendra Singh Parmar, Enterprise Principal Product Owner – Data Science and Analytics at Discover Financial Services. With over 15 years of expertise in AI, data science, and digital transformation, Devendra has developed groundbreaking solutions for top institutions like HSBC and Discover, spearheading projects that enhance fraud detection, credit risk management, and personalized banking services. His tenure includes leading multi-million-dollar global projects in fraud detection and credit risk management at HSBC, significantly boosting the bank’s risk mitigation capabilities. At Discover, Devendra has overseen the development of cutting-edge analytical products that not only safeguard customer trust but also deliver substantial cost savings.
In this conversation, Devendra shares his insights on how generative AI is enabling banks to move beyond traditional automation toward a new era of hyper-personalized customer engagement and real-time risk management. He also sheds light on the future of AI in banking and the opportunities it presents for the industry to set new standards in customer trust, efficiency, and innovation.
AIM Research: How is generative AI transforming customer interactions in banking, and what are some examples of hyper-personalized services that were previously unimaginable with traditional automation?
Devendra: Generative AI is transforming customer interactions in banking by enabling a deeper level of personalization and responsiveness than traditional automation could achieve. By using advanced large language models, banks can now provide real-time, conversational interactions that feel human-like, facilitating a more intuitive and supportive customer experience. This transformation includes services like personalized financial advice, where generative AI analyzes a customer’s financial history, spending habits, and personal goals to offer tailored recommendations and insights.
Further, examples of hyper-personalized services include AI-driven financial planning that adapts to changing personal and market conditions, offering proactive savings or investment tips tailored to each customer’s risk profile and life stage. Another example is dynamic fraud prevention systems that can detect unusual transaction patterns unique to an individual customer, flagging or intervening in real-time without disrupting legitimate transactions. Additionally, generative AI enables personalized onboarding experiences, offering support and information specific to a customer’s financial background, which was previously unattainable with traditional automation. This shift from one-size-fits-all service to highly individualized experiences is reshaping how customers engage with their banks, setting new standards for satisfaction and loyalty.
AIM Research: With fraud detection models showing exponential improvements through generative AI, what role do you believe AI will play in redefining risk management and customer trust in the coming years?
Devendra: AI, particularly generative AI, is set to play a transformative role in redefining risk management and enhancing customer trust in banking. Generative AI models can identify fraud patterns with a high degree of accuracy, even detecting nuanced or emerging threats that traditional models might overlook. By continuously learning from vast amounts of transaction data, these models evolve to stay ahead of increasingly sophisticated fraud tactics, resulting in a more dynamic and proactive approach to risk management. In the coming years, AI-driven fraud detection will be integral to building and maintaining customer trust. Real-time monitoring and predictive analysis will allow banks to not only respond to threats instantly but also prevent fraud preemptively. This proactive protection strengthens the relationship between banks and their customers, as users feel more secure in their financial transactions. Additionally, AI will streamline compliance and regulatory processes, automating risk assessments and maintaining adherence to stringent standards. This shift not only boosts operational efficiency but also assures customers that their banks are equipped to handle risks responsibly, promoting greater transparency and trust. Ultimately, generative AI’s capabilities in detecting, understanding, and preventing fraud will redefine the standards for secure banking and foster a more resilient financial ecosystem.
AIM Research: In terms of compliance and regulatory processes, generative AI has shown promise in areas like KYC verification and document analysis. How do you see this changing the day-to-day operations of banks, and what are the benefits for both banks and customers?
Devendra: Generative AI is transforming compliance and regulatory processes, particularly in areas like Know Your Customer (KYC) verification and document analysis, by making these traditionally labor-intensive tasks faster, more accurate, and cost-effective. In day-to-day operations, generative AI enables banks to automate large parts of the KYC process, such as verifying customer identities, analyzing complex documents, and detecting potential compliance risks, all in real-time. This reduces the need for manual verification, allowing compliance teams to focus on higher-level analysis and decision-making. For banks, this shift brings substantial operational benefits. Automated KYC verification reduces onboarding times, allowing customers to access services more quickly and enhancing the overall customer experience. Generative AI also improves accuracy in detecting anomalies or discrepancies within documents, thereby minimizing compliance errors and reducing regulatory fines. Moreover, it can keep up with evolving regulations by quickly adapting to new compliance requirements, ensuring that banks remain aligned with legal standards.
Customers benefit from this transformation through a smoother, more efficient onboarding process, with fewer disruptions and faster access to banking services. Additionally, as generative AI enhances the security and precision of compliance operations, customers feel more assured about the safety of their data and the integrity of the financial system. This dual advantage of efficiency and enhanced security is redefining compliance in banking, creating a more streamlined and customer-centric environment that benefits both banks and their clients.
AIM Research: Generative AI is streamlining banking operations from automated reports to financial summaries—what role does this play in cost optimization, and how does it impact the jobs and tasks traditionally held by human employees?
Devendra: Generative (Gen) AI plays a significant role in cost optimization within banking by automating routine yet time-consuming tasks like report generation, financial summaries, and document processing. By handling these tasks autonomously, generative AI reduces the reliance on manual labor, cutting down on operational costs and allowing banks to reallocate resources toward higher-value activities. For example, generating real-time financial summaries or customer insights through AI-driven automation solution reduces the need for large teams dedicated to data processing and report compilation. This not only speeds up decision-making but also ensures a high level of accuracy, lowering the costs associated with human error.
While AI-driven automation may replace some routine tasks traditionally held by human employees, it also frees up these employees to focus on more complex, strategic roles that require nuanced decision-making and interpersonal skills. For instance, instead of spending hours compiling reports, analysts can now concentrate on interpreting the results and providing actionable insights. Generative AI’s role in cost optimization goes beyond workforce reduction; it empowers employees to take on more value-added roles in customer relations, strategy, and innovation, areas where human judgment and creativity remain essential. In this evolving AI landscape, banks have the opportunity to reskill and upskill their workforce, guiding employees toward roles that complement AI capabilities. This shift transforms the traditional banking workforce into a more agile, strategically focused team, optimizing costs without compromising the human expertise that remains critical to customer experience and complex decision-making in finance.
AIM Research: Conversational AI in banking is becoming more prevalent. Do you think it has the potential to fully replicate the personalized service of in-branch experiences, and where might it still fall short?
Devendra: Conversational AI in banking has advanced significantly, delivering personalized services that often replicate in-branch experiences. It offers benefits like 24/7 availability, efficient handling of routine queries, personalized recommendations using customer data, and seamless, omnichannel service across devices. However, it still has limitations compared to human interactions. For example, AI lacks emotional intelligence, making it challenging to provide empathy in sensitive situations. It also falls short in complex financial advisory, where human insight is essential, and struggles to build trust, especially in high-stakes or unpredictable scenarios. Ultimately, while conversational AI is valuable for routine interactions, banks may find the best results with a hybrid approach, combining AI for standard tasks with human advisors for high-touch, personalized engagements.
AIM Research: Generative AI adoption in banking is expected to skyrocket, with investment projected to reach $85 billion by 2030. As the pace of generative AI adoption accelerates in banking, what are the biggest opportunities you see for banks to differentiate themselves and deliver unparalleled customer value in the next few years?
Devendra: Generative AI presents transformative opportunities for banks to deliver exceptional customer value and differentiate themselves in a competitive landscape. With hyper-personalized financial products and proactive financial health monitoring, banks can position themselves as trusted, forward-thinking advisors. Advanced fraud detection and real-time lending decisions bolster security and operational speed, while streamlined customer support enhances onboarding experiences. Generative AI also drives predictive marketing, allowing banks to engage customers with timely, relevant offers. Immersive, multi-channel experiences ensure seamless service across platforms, meeting customers where they are, while AI-driven accessibility promotes financial inclusion by supporting underserved populations. Additionally, by embedding sustainability insights, banks can appeal to socially conscious consumers. As banks embrace generative AI, they can expect gains in customer loyalty, operational efficiency, and market leadership, marking a new era in banking.