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Written by Cognizant Benelux
28 June, 2024
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4 mins
In a recent interactive roundtable discussion with Microsoft, The Banking Scene and key players in the banking industry uncovered the opportunities, challenges, and strategic imperatives associated with tools like generative AI and Copilot.
The financial services industry is at a crossroads. Generative AI has exploded onto the scene, captivating the imagination with its potential to revolutionize everything from customer experience to risk management. Yet, beneath the hype lies a sobering reality and challenges, including multi-year implementation complexities, high costs and questions over ROI. Alongside this, businesses are still unsure if what we’re witnessing is a fleeting trend or a transformative force about to reshape an entire industry.
Flashy tools like ChatGPT might grab the headlines, but the reality is more complex. Implementing and maintaining large language models (LLMs) is one thing, but doing this in a trusted financial services environment is completely different. How should banks start with this new technology, respecting their current commitments to the customer? What should banks do cautiously when building on the opportunities of Generative AI, respecting the resilience levels that are expected from banks?
These developments require significant time, resources, and expertise, raising questions about long-term ROI and practical impact. Here we share some key takeaways from the thought-provoking discussions:
One of the critical takeaways was the emphasis on change management. The integration of GenAI into banking operations necessitates a focus on critical thinking and the evaluation of AI outputs. Participants stressed the importance of high-quality unstructured data to ensure that GenAI delivers clear and actionable insights.
Furthermore, while productivity and internal process optimization are significant benefits, it is vital to explore how GenAI can address customer problems and create new value propositions. The consensus was that technology should enhance, not replace, the human element, thereby maintaining the trust inherent in customer interactions. Specifically, it was noted that GenAI could improve personalization in service delivery, optimize workflows, and enhance risk management, making financial services both more secure and more accessible.
Generative AI can also help create emotional connections, loyalty, and digital connections for merchants and managed service providers. By leveraging AI-driven personalization, businesses can tailor their offerings to meet individual customer preferences, fostering a deeper emotional bond. For instance, GenAI can analyze customer behavior to suggest personalized rewards and offers, enhancing customer satisfaction and loyalty. Additionally, AI can facilitate seamless digital interactions, providing consistent and engaging experiences across various touchpoints. This not only boosts customer engagement but also strengthens the overall brand relationship, making customers more likely to return and recommend the service to others.
Furthermore, the potential of GenAI to build a personal finance manager for SMB clients was emphasized. This virtual financial advisor could assist businesses in managing their finances more effectively by providing real-time insights, forecasting cash flows, and suggesting cost-saving measures. Banks are uniquely positioned to offer this service because they are trusted custodians of financial information. This trust, combined with their access to vast amounts of data and expertise in financial management, allows banks to create highly personalized and reliable financial tools.
Discussions also highlighted the substantial productivity gains achieved through AI tools like Copilot. Testimonials revealed that Copilot can save 12-15 minutes per day for users, significantly enhancing their daily work experience. For example, one bank reported that 63% of their CRM entries were more up to date thanks to Copilot, and employees spent 64% less time on emails.
However, the adoption journey is fraught with challenges, including the need for substantial educational efforts and the development of effective prompt templates. The potential of Copilot AI Studio and its applications in coding, UAT, and work management was seen as a game-changer, though the technology remains in its nascent stages. Moreover, while the promise of increased efficiency is alluring, it is essential to balance it with the mental well-being of employees, ensuring that the drive for productivity does not lead to burnout.
The event concluded with a recognition of the need for federated AI solutions, emphasizing the role of data quality and governance. Ultimately, the evening underscored the need for a strategic and measured approach to integrating GenAI, with a clear focus on quality data, human oversight, and the ongoing evolution of AI capabilities.
“We are all together on a journey: bank executives, technology partners and system integrators. As I reflect on this session it becomes clear that a new potential business model is emerging for Merchant SMEs enveloped by the power of generative AI.” says Gregory Verlinden, Associate Vice President Consulting & AI at Cognizant.
In the dynamic landscape of organizational transformation, change doesn’t occur overnight; it’s a gradual journey. Key to successful change is effective change management, which hinges on literacy and understanding. Perhaps we should shift our focus from mere productivity to value-driven outcomes. Technology plays a pivotal role as an enabler, but it’s the robust business case that propels initiatives forward. In this new world of work, the interplay between exposure and friction determines our progress.
Discover how Cognizant can help solve some of the banking industry’s greatest challenges. Visit our banking hub to watch our latest GenAI use case video presented by our banking, digital experience and artificial intelligence experts.