SAS Report: Why Most Banks Struggle to Build Trust in AI

Even though banks are investing in artificial intelligence (AI) technologies faster than other industries, a recent report from SAS reveals a big gap between how much they're investing and how much they actually trust these technologies. This really highlights the urgent need to strengthen the core foundations of reliable AI. In banking, trust isn't just a nice-to-have; it's absolutely essential for making sure decisions are sound and customers are protected, especially with how complex operations are becoming and how much we rely on data. The study, which used research from IDC and looked at government, insurance, and life sciences sectors too, found that only about 11% of banks have high internal confidence in their reliable AI systems. On the flip side, nearly half of banks are dealing with what the study calls a 'trust dilemma.' This often happens because they're using unproven systems or simply aren't using AI in a way that's reliable and well-documented. Stu Bradley, Senior Vice President of Risk and Fraud Management Solutions at SAS, pointed out, "While the banking sector is ahead of others in adopting AI, nine out of ten banks haven't yet found the perfect balance between trust and proof. About a fifth of them are even relying on fragmented data, which makes closing this gap a top priority for the industry." The report stresses that while most banks are pouring money into AI, key foundational elements like data governance, integrated infrastructure, and specialized skills are still weak. This puts them at risk of losing trust or seeing a lower return on their AI investments. Interestingly, while some banks are just focused on cutting costs, those institutions that make responsible innovation a core part of their strategy actually see better financial returns. For example, banks that focused on improving customer experience saw a return of $1.83 for every dollar invested, compared to $1.54 for banks that only focused on efficiency. The report suggests that leading banks are the ones that prioritize transparency, explainability, and data governance *before* expanding their AI efforts. By developing AI systems reliably, they can really boost innovation and earn customer trust for the long haul. Michel El Ghareeb, Executive Director at SAS in the UAE, shared, "Banks in the Middle East have solid foundations when it comes to data and governance. This puts them in a great position to scale up their AI investments and get reliable results, as long as they focus on boosting transparency and making it easier to understand the decisions these systems produce." Ultimately, the report's findings confirm that just investing money isn't enough. Trust, good governance, developing the right skills, and building reliable systems are all super important for ensuring AI adoption in the banking sector is sustainable and successful.