Governance gaps, AI implementation hurdles, and regulatory compliance risks are top of mind for senior leaders.
With over 30 years of experience in banking and consulting, Jeremy Bryson has seen how data strategies have evolved—and where many firms are still falling short. Now, as Jaywing’s Head of Data Management, he’s working with businesses to tackle these challenges head-on. We sat down with him to talk about AI adoption, regulatory expectations, and the future of data governance.
The industry is moving toward AI-driven risk models, yet adoption remains uneven. What are the key blockers?
The use cases for AI are easy to identify. Data scientists are experimenting with models, and skills and experience are improving. However, the two key blockers are: how to orchestrate the data for use by the models—where it comes from and where it goes—and the quality of the data being inputted into the models.
Data governance frameworks are under intense regulatory scrutiny. Where do you see firms falling short, and what should they do differently?
The European Risk Management Council has identified cyber risk and operational risk as the most concerning risk types. These are often poorly integrated into data management practices, leading regulators to question whether data governance frameworks are truly joined up to provide holistic risk management.
With the increasing complexity of regulatory compliance, how can firms future-proof their data management strategies?
A firm’s data management strategy must be adaptable to ongoing regulatory changes. To manage this efficiently and effectively, all components of a data management strategy need to be in place: traceability, data quality management, data definitions, and data governance. Having these in place reduces the overall cost of future compliance.
Many institutions struggle with fragmented data sources impacting model accuracy. What are the practical steps to overcome this?
The first step is to discover the data within source systems—essentially, understanding the metadata. Then, organisations should place this data into a modelling and analytics environment where it can be prepared for use. With cloud computing tools, a separate environment may not even be necessary. Additionally, businesses should be prepared to share analytical datasets with risk reporting and finance teams, as they rely on the same data.
Looking ahead, what shifts in data risk and compliance do you expect to dominate boardroom discussions in the next 12-18 months?
A key topic will be how to gain a holistic view of risk, integrating operational risk and cyber risk alongside other risk types. Another major discussion point will be how these various risks interconnect—after all, we live in an increasingly complex world.
What’s an underappreciated aspect of data management that risk leaders should prioritise?
By establishing joined-up data management practices, organisations can build greater trust in their data, reducing the need to create yet another copy of the same data for a different purpose. This significantly lowers the total cost of data management across the business.
What are you most looking forward to in your role at Jaywing?
I’m looking forward to harnessing the immense talent and experience of Jaywingers to tackle complex client challenges and unlock significant value for them.
Final thoughts
Satya Nadella, CEO of Microsoft, once said, ‘Every company is a software company…’ and every bank is now a data management company as well. Data is at the heart of every decision, every compliance effort, and every risk model. Good data management affects everything positively—ensuring accuracy, reducing costs, and creating trust in decision-making. Poor data management, on the other hand, leads to inefficiencies, regulatory challenges, and unnecessary duplication of effort.
Firms that take a joined-up approach to data governance, integrating cyber and operational risk alongside financial risk, will be better positioned to meet regulatory demands and improve efficiency. It’s not just about satisfying regulators. Firms should aim to make data work harder for the business and reduce the total cost of managing it.
Want to connect with Jeremy? Reach out to him on LinkedIn or see how Jaywing can help strengthen your data management here.
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