Sally Bashuan is the Executive Director and Head of Global Data Governance, at Federated Hermes where Sally has built the data office and changed the narrative around data across the organisation to achieve cultural change, increased data literacy and raised the data maturity across the organisation. Laying a solid foundation for sustainable and scalable growth.
We sat down with Sally in this exclusive interview and asked her the following questions ahead of Chief Data and Analytics Officers (CDAO) FSI UK 2025.
Register now for CDAO FSI UK 2025 to hear directly from Sally Bashuan and other leading professionals about the cutting-edge of data analytics transformation.
Which trend associated with data and/or analytics are you most interested in or passionate about? And why do you think this is so relevant today?
I am most interested in the trend of data democratisation within organisations and how making data accessible to all employees, regardless of their technical expertise, fosters a data-driven culture.
I believe this is highly relevant today because it empowers employees at all levels to make informed decisions, drives innovation, and enhances overall business agility. By breaking down data silos and promoting a culture of data literacy, organisations can better respond to market changes, improve customer experiences, and maintain a competitive edge in the rapidly evolving financial services industry.
I am also very interested to see what comes next for data governance frameworks when bringing AI into the equation. How the role of data governance evolves and what it means for practitioners.
What are the top 3 trends you think will take AI, Data or Analytics to the next level in 2025/2026, and why?
1) We will no doubt see an increase in the use of AI to manage larger amounts of data within the investment management space. The diversity of data coming into the picture will increase the need for the investment managers to dissect and drill down on the implications for their portfolios, which will create the demand for leveraging Generative AI.
It will ultimately become a differentiator for improved performance. Optimising portfolios and increase personalisation will be just the start. Active management will be taken to a whole new level when generative AI identifies previously unseen connections and drivers to improve performance. The ability to walk the tightrope of regulation, explainability and innovation, will be key to asset managers who are looking to be industry leaders but ultimately for any asset manager to remain relevant.
2) The use of alternative and ESG data - Alternative data sets such as satellite imagery or digital consumption data, are appearing all the time and maturing to be more reliable in terms of the high standards that the financial services industry needs to be able to utilise it. There are minimum quality standards and availability requirements to ensure consistency for these data sets to be utilised, (or at least the challenges need to be transparent and understood throughout the data sets lifecycle so that SLA's and contractual requirements are not breached). Despite the push back on ESG, sustainability and the improvement of returns through understanding the impact of economic, social and governance factors become clearer with the more data that is collected.
Decisions can be better informed and the connection of the data to the financial returns becomes clearer. Whilst there are initial challenges with the maturity of new data and the difference in the skills required to analyse it, the use of alternative data to add depth and context to existing financial information is undeniable. It enriches market analysis as long as it is integrated and provides the opportunity for better returns.
3) Automation will continue to drive operational efficiencies, with increased visibility of its outcomes. Entry-level jobs are already being impacted by both traditional automation and AI, fundamentally changing career paths in financial services and altering the skill mix required. New roles will demand higher levels of data and ethics skills, and no role will be exempt from understanding data fundamentals. Data and technology teams will be reshaped as revenue-focused individuals seek greater control over data as an enabler of their roles. They will be less contentment with imposed rules without being part of the conversation. The evolving requirements for entry-level employees will necessitate dialogue with schools and universities to ensure relevant skills are taught, maintaining a talent pipeline suited to the industry's challenges. Existing employees will need to stay informed about developments in their areas and engage in training to adapt to the changing environment.
What are the top 3 challenges that the industry will face in 2026, and why?
1) Data quality and management - Ensuring data is fit for purpose remains a persistent concern for executives. When performance declines, the focus often shifts to data quality, although correlation does not always imply causation. The executive's desire to resolve data issues will likely intensify, especially with AI opportunities requiring high-quality, well-managed data. Challenges will include managing expectations—defining what constitutes good data, establishing foundational frameworks tailored to the organisation, balancing governance with innovation, and investing adequately in infrastructure and processes to maintain data integrity and consistency. Enterprise data management must be an ongoing, iterative program aligned with the company's aspirations, rather than a one-time project.
2) Regulatory, Ethical and Transparency issues - The principle of "just because we can, doesn't mean we should" is crucial in the context of AI and data usage. While AI offers significant benefits, it can also lead to unintended consequences from well-intentioned decisions. Having spent 12 years as a Financial Crime Investigator, I understand that not all negative outcomes stem from malice. Regulators expect organisations to embed ethical considerations to prevent unintended impacts on clients and company integrity. Transparency in models, decisions, and data usage is essential. Competitive pressures can blur ethical lines, so clear guidelines on company standards and expectations, along with robust oversight and governance, are necessary to ensure regulatory compliance and maintain trust among staff and clients.
3) The Skills Gap - The skill set required in financial services is evolving, with a growing need for all roles to have a foundational understanding of data. This includes recognising the potential uses and limitations of data to drive innovation in products and services. The push for enhanced data skills, even in companies where data remains centralised away from revenue-generating roles, is fuelled by rising expectations from all stakeholders. Companies with superior data infrastructures are attracting top talent, as individuals understand the significant impact on their performance.
An organisation's data literacy program must be adaptable and multifaceted to ensure data education is accessible to everyone. As data becomes a core competency across all roles, existing staff will need to retrain and upskill to stay relevant as their roles evolve. Although there is a shortage of professionals with AI and data science skills in the finance industry, not all data roles are the same. Some requirements stem from a greater awareness of enterprise-level data and company expectations on data usage to avoid negatively impacting colleagues. Additionally, ethical considerations are crucial. Significant training of in-house staff is necessary to bridge the gap, and collaboration with universities is essential to develop the right courses and training for the new era of data and AI in financial services.
How do you think the role of data has evolved?
The role of data has transitioned from a disparate, back-office function to a central focus for many organisations. They recognise that neglecting data can hinder business operations and create a competitive disadvantage. Consequently, most companies are now adopting an enterprise-wide perspective rather than being content with data isolated in local silos. This shift is driving cultural and skill changes within organisations as they consciously develop enterprise strategies and invest in their data infrastructure. While the debate between centralised and federated data models continues, frameworks, ethics, and standards are increasingly being managed centrally in most companies.
With the move towards AI capabilities becoming a reality for many companies, it is also sparking interest in optimising data to leverage these benefits. While many companies are cautiously observing whether AI is merely hype or has practical applications, this scrutiny is benefiting data foundation work by attracting more focus and funding for data initiatives.
What are you looking forward to/contributing towards at CDAO FSI UK?
At CDAO FSI UK, I am looking forward to engaging in discussions around data innovation and sharing best practices with industry peers. This event provides a unique opportunity to understand where the financial services industry stands in terms of their data strategies and to learn from the successes and challenges faced by others. I am excited to contribute by sharing insights from our own data initiatives, discussing the latest trends in data management, and exploring collaborative approaches to enhance data capabilities across the sector. By participating in this forum, I aim to foster a culture of continuous improvement and innovation in data practices, ultimately driving better outcomes for our organisations and the industry as a whole.
In summary, the trajectory of the financial services sector is being shaped by an increasingly complex landscape of data management, automation, evolving skill requirements, and heightened regulatory and ethical expectations. The industry’s ability to thrive hinges on a clear commitment to robust data governance, investment in advanced technologies, and the cultivation of a workforce equipped for analytical and ethical challenges. As ESG and alternative data become ever more central to market analysis and value creation, organisations must ensure data is not only rigorously managed but also meaningfully integrated into strategic decision-making. Success will demand collaborative industry efforts—across enterprises, academia, and regulators—to close skills gaps, set high standards for operational transparency, and foster a culture of continuous learning and innovation. By embedding these principles, financial institutions will not only meet future challenges but also unlock new opportunities for sustainable growth and competitive differentiation.
Sally Bashuan’s leadership at Federated Hermes proves the power of cultural transformation in data. By championing data literacy, democratisation, and smart governance, she’s building the blueprint for sustainable growth and industry resilience. How is your organisation adapting to today’s data-driven landscape?
Register now for CDAO FSI UK 2025 to hear from all our expert speakers in-person, on 9th September at the Hilton London Tower Bridge!
