Artificial intelligence must be embedded in and across the business—from human resources to finance to customer service.
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By Anuj Kumar, Industry Strategy and GTM lead for Financial Services at SAP UK
“It’s no coincidence that every trend we believe will help shape the future of financial services in the next 12 months and beyond is influenced, to a greater or lesser degree, by the adoption of generative AI,” says Accenture’s top ten banking trends for 2024 report. And while AI adoption reads well in analyst reports, actually knowing the ‘how to’ is essential.
For years, the complex architecture in financial services has hindered the ability to embrace new technology. The organizational objectives remain consistent – how to improve customer service in the back office and reduce costs. AI is an opportunity to address these priorities, but Samuel Coleridge’s famous line, “Water, water everywhere, and not a drop to drink” is as true today when it comes to AI as it was at 18 years old.th poetry of the century.
Today, HE is here, there, everywhere. However, there is no clear path that financial services should follow. Here are five critical steps to consider.
1. Think big, think strategically – Instead of trying to keep pace with competitors, outdo them. The goal is to empower the business and employees to reach their full potential. This won’t happen with a piecemeal tactical approach with AI tools improving an isolated process. Financial services need to think beyond that. Artificial intelligence capabilities must be incorporated into and across the business—from human resources to finance to customer service. Think strategically, not tactically.
2. Start with AI embedded in existing solutions – It’s time to take a closer look at existing enterprise systems and what they are capable of doing – and then modernize if necessary. Rather than treating AI as an external add-on, recognize that AI is already being integrated within modern cloud-based enterprise systems. ERP is a perfect example as embedded AI makes it easier to unlock value. By adopting solutions where AI is a natural extension of current technology, financial services begin to reap the benefits immediately. Without an intelligent cloud-based platform, financial services can be caught in a never-ending game.
3. Focus on high-impact use cases – The real power of AI lies in its ability to transform specific areas of financial services that can bring the most significant profits. For example, prioritize AI applications in customer experience, where personalized interactions can drive loyalty, and in risk management, where AI can provide real-time insights that prevent fraud and optimize credit ratings. Measurable results will be key to getting wider organizational buy-in. Today, the use cases are numerous, the key now is to develop a logical structure to prioritize and execute.
4. Strengthen databases – The effectiveness of AI depends on the quality of the data it processes. Before diving into AI, make sure the data infrastructure is strong. Clean, organized and accessible data is essential for AI to deliver actionable insights. A strong database also facilitates compliance with financial services regulations. The underlying platform should already do this. If not, deploy a more robust cloud platform that automatically handles data quality issues.
5. Experiment and scale strategically – Start with targeted pilot programs to evaluate AI capabilities in real-world scenarios. Prioritize, test and refine before you go full scale. By viewing AI integration as an evolutionary process, financial services can mitigate risks and build a scalable and sustainable AI strategy to meet and exceed objectives. It’s an evolution, not a revolution!
