Data science skills are becoming essential for operational and non-financial risk management as teams evolve to become more data-driven.
Our strategic vision for operational and non-financial risk
highlights that industry leaders are building strong foundations for digitalisation. As operational and non-financial risk (ONFR) demands evolve, new digital skills are needed and teams are becoming multidisciplinary.
Our research shows that domain knowledge, data literacy, and data storytelling are key priorities, while AI-related skills are rapidly gaining importance.
Building out the data science skills base
Financial firms are working towards building a digital core to support more data-driven risk management. We are seeing domain knowledge, basic data literacy and data-driven decision-making top the list of data skills for day-to-day operational and non-financial risk management activities. Due to increasingly advanced technology, the ability to understand the problem and interpret data meaningfully has become a crucial asset.
Data is also becoming more important for business and strategic decision-making. Insights must be actionable and clearly communicated. Over 40% of firms we surveyed plan to further develop skills like data storytelling and data analysis and manipulation in the short term, which are already considered some of the most important competencies.
Importance of data skills and plans to develop
Source: The drive towards digital ONFR management (2024)
AI is gaining ground
While AI-related skills are not yet central to daily operational and non-financial risk activities, they are rapidly growing in importance. In particular:
- Basic AI literacy (e.g. using GenAI assistants)
- AI ethics and responsible AI
- Prompt engineering
These skills saw the biggest increases over the past 12-18 months, with up to 59% of participants saying they have become more important. This demonstrates that while operational and non-financial risk teams are not building risk management or reporting systems themselves, they are increasingly expected to engage with AI tools securely and responsibly, in accordance with regulatory guidelines or legislation.
Firms are developing multidisciplinary teams
The growing importance of AI-related skills, along with the continued focus on skills like data literacy and storytelling, speaks to the breadth of capabilities that modern teams are required to develop. Teams must upskill quickly and effectively while continuing to attend to core responsibilities.
Over half of the firms we surveyed reported fostering both formal and informal development paths for employees, with a particular focus on the dissemination of AI skills. Examples include:
- Webinars, presentations and demos
- Peer-to-peer learning and knowledge-sharing sessions
- Mentoring
- Summer schools
- University courses
Prioritising skills that align with both current and future needs is essential. Technical skills involving developing AI systems from scratch and data architecture design are less critical and can be supplied by other teams.
Looking ahead
The Data Science Community will explore this topic more in a discussion session in October 2025.
Get involved with our data science activities
The Data Science Community
The Data Science Community is open to anyone interested in the practical and strategic use of data science and AI. It explores topics such as operational applications, user perspectives, AI risk management, and evolving regulatory landscapes. The community provides a space to connect with peers, share insights, and contribute to relevant studies.
The Data Science Working Group
The Data Science Working Group (DSWG) brings together data scientists and ONFR professionals who are actively involved in or overseeing data science initiatives for ONFR management. The group meets regularly to explore use cases and share learnings. Current focus areas include the leveraging machine learning and AI and developing a digital core to achieve a holistic view of ONFR. If you are interested in joining the group, please get in touch.
