Financial services and banking (FS&B) companies are setting the pace for implementing AI policies within their organisations, according to research from Alteryx, the AI platform for enterprise analytics. The Defining the Enterprise of the Future report sheds light on the sector’s cautious approach, with a resounding 91% of professionals in the sector advocating for regulations and standards governing the use of AI and Generative AI (GenAI). 

AI apprehension spurs diligence 

In light of this absence, FS&B organisations are taking matters into their own hands. The majority (86%) have already implemented AI security, ethics and governance policies to secure the future success of their businesses – a significant 11% increase on the global average across all sectors.  

The emphasis on data governance in the sector could stem from numerous sources: a heightened sense of scepticism around AI about its benefits, being a highly regulated sector and the expectation of being impacted by the EU’s upcoming AI Act. Surveying 2,800 professionals across the world, including 700 in FS&B, the research found that 80% harbour concerns about using AI-produced answers, versus 73% across all sectors.  

Furthermore, FS&B professionals are less optimistic about the impact of AI on enterprises, with just 37% saying they think it will have a positive impact. Damage to workplace desirability (42%), damage to brand reputation (41%) and loss of intellectual property and data (36%) were all identified as looming threats of getting AI wrong.  

The greatest potential risks of not having an AI policy, however, are the legal and ethical consequences (49%). This is echoed by 92% of FS&B organisations saying that AI policies are the key to implementing responsible AI into businesses. Transparency and explainability (54%), accountability (52%), and inclusive growth, sustainable development and wellbeing (34%) are cited as the key ethical considerations shaping policy development for the industry. 

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Preparing for a secure AI future 

There is a focus within FS&B on talent acquisition to bolster data governance within firms. A quarter (24%) in the sector say that data governance leads are an urgent priority to prepare the business for the future. This trend of ensuring there are people within organisations specifically to develop, uphold and enforce data governance policies is set to continue in the future as 44% of FS&B professionals say that they expect more data ethics and privacy roles to emerge. 

FS&B also leads in adopting security, ethics and governance strategies. The most widely adopted approaches within FS&B are multi-factor authentication (MFA) to access systems, applications and data (44%), integrated security implemented into the development process (42%) and zero trust security models/secure access service edge security frameworks (40%). 

In the future, MFA (45%) and integrated security implemented into the development process (35%) are set to remain key approaches to security, ethics and governance for FS&B. Regular security awareness training for employees (40%) and robust governance frameworks that define roles, responsibilities and decision-making processes related to security (35%) are also expected to grow in priority. 

Commenting on this, Alteryx SVP EMEA, Jason Janicke, said: “The evolution of AI capabilities, specifically generative AI, has presented the FS&B sector with significant opportunities to unlock the power of data to automate tasks for productivity value creation while lowering costs. However, it has also promoted data privacy, ethics and cybersecurity concerns. Financial services and banking professionals are stewards of highly sensitive data, so any misuse of AI – even if unintentional – may leave organisations vulnerable. From opening new avenues for hackers to breach advanced cybersecurity software to users of these systems accidentally sharing confidential or proprietary data with the open AI community, it’s right for the sector to take a proactive approach to the implementation of effective guardrails that include practical checks on data quality, privacy, and governance. Data literacy upskilling will help establish a robust data-centric approach to AI, which is critical to safeguarding the business and maintaining security and trust amongst stakeholders and customers.”