It would be a stretch to say that Sibos news and chatter was dominated by generative AI (or Gen AI). After all, for banks at least, we are still in the early days of the generative AI journey, and no doubt a high percentage of delegates feel more pressured by ISO 20022 adoption! I digress... However, the level of interest was high (including for our research in this space), and vendors were starting to discuss solutions.
The interest in Gen AI is also reflected in the results of Celent’s Technology Insights and Strategy Survey, as published in Corporate Banking Global IT Priorities in 2023: Customer-first Strategies to Survive and Thrive. The category of advanced analytics and ML was rated the top technology priority in corporate banking, with 33% of responding banks selecting this in their top three priorities. AI (including Gen AI) was ranked close behind with 28% of responding banks selecting it as a top three choice. Perhaps that is not surprising since embedded analytics and AI will power a future of data-fueled banking products and services.
We also asked banks about the most transformative technologies over the next five years – and just as importantly – what they are doing about it. This analysis brings together the responses from two survey questions. The first (on the y-axis) shows the proportion of banks that are currently experimenting with (or evaluating their opportunities in) each technology/business model. The second (on the x-axis) highlights the technologies that banks expect to have the biggest impact on the market in five years’ time.
Note that the chart is non-exhaustive and only a few technologies are highlighted for this blog post. Although an important topic, let's park quantum computing for another day.
Gen AI was highly ranked by banks as a top three transformative technology in the next five years, with over 55% of banks currently evaluating or testing, while a further 23% have projects using this technology in their 2023/4 roadmap. Given the potential use cases and market hype around the technology, this is no surprise. Some key examples that surfaced at Sibos include:
- In the UK, NatWest Group announced an expansion of its collaboration with AWS to adopt Gen AI. NatWest Group data scientists and engineers will work with the AWS Gnerative AI Innovation Cneter to co-create AI products and services.
AWS Connect Wisdom uses Gen AI in customer contact centers where it provides agents with real-time “wisdom” to prove the outcome of the client interaction. Gen AI synthesizes the conversations or chats in real-time and provide contextual recommendations to the agent.
Intellect Design Arena announced a generative AI “copilot” product, powered by Microsoft Azure OpenAI. iGTB Copilot contains over 50 AI use cases – including for cash management, liquidity, cash forecasting, payments, and trade services – and is in trials with a tier one bank.
Trade Ledger in collaboration with Microsoft announced Aida, a Gen AI solution for receivables and working capital management. Aida is positioned as an assistant designed to help small and medium-sized businesses optimize order to cash cycles.
- Several vendors of receivables automation are implementing Gen AI for client communications, especially for collections where tenor and tone can be adapted based on risk criteria and value of the client relationship.
Another vendor I spoke with is experimenting with Gen AI for working capital narratives, insights, and recommendations based on trends in transaction and balance behavior over time.
For more on Gen AI in banking – I encourage you to follow my colleague, Alenka Grealish and her ongoing research in this fast-moving space.