How financial services firms can responsibly adopt AI while navigating growing regulatory complexity
How can financial services harness AI’s power while managing an increasingly complex regulatory environment? This was the central question addressed by experts at our recent Elastic Financial Services Summit. Matt Minetola, CIO at Elastic, brought deep FinServ technology expertise, while Bill Wright, senior director of global government affairs at Elastic, offered critical insights on AI regulations and risk governance. They were joined by Thomas Mathew, senior director of industry cloud – Financial Services at Microsoft, who provided perspective on the role of cloud platforms in compliance.
AI adoption is rising — and so are compliance challenges
The challenge is clear: Financial services firms are under pressure to adopt AI swiftly while navigating regulatory requirements that grow more complex by the day. As Wright explained, organizations must comply with new regulations like the EU AI Act, which “takes a risk-based approach to AI and then bans certain practices while setting requirements for high-risk AI systems,” impacting providers and developers globally, regardless of location.
A unified data foundation is the key to AI transformation
McKinsey’s 2024 research, drawing from experience with hundreds of companies, emphasizes that successful AI adoption requires six interconnected capabilities: a business-led digital roadmap, skilled talent, a fit-for-purpose operating model, user-friendly technology, enterprise-wide accessible data, and scalable solutions. All these elements must work in harmony for transformation to succeed.
This comprehensive approach aligns with the webinar’s core message: While financial services organizations are eager to harness AI’s potential, they must first establish a foundation of integrated capabilities. As McKinsey notes, organizations need data that is “continually enriched and easily accessible across the enterprise,” alongside technology that teams can readily use — echoing the speakers’ emphasis on robust governance frameworks and operational adaptability.
The path to responsible AI adoption in financial services isn’t simple, as our summit experts revealed. Consider the regulatory framework — Wright points out that the EU AI Act alone introduces sweeping changes, “taking a risk-based approach to AI” that affects organizations worldwide. The technical hurdles are equally demanding. Minetola highlighted a key FSI concern: managing “scale, performance, and cost” while maintaining consistency across all business units.
Mathew explained that Microsoft sees its cloud platforms as tools to support compliance with AI regulations that use a risk-based approach distributing responsibilities across the AI supply chain’s actors (providers, deployers/operators, and sellers/distributors), with AI systems classified by purpose, autonomy, and complexity. “Upstream regulators like Microsoft, in its capacity as a provider of AI tools, services, and components, must support downstream actors like the enterprise customers we have when they integrate Microsoft services into a high-risk AI system … Microsoft has a shared obligation with various actors as part of that supply chain,” he said.
Customer spotlight: EY
EY partnered with Elastic to deliver responsible, high-performance generative AI solutions for financial services firms. By leveraging the Elasticsearch Relevance Engine (ESRE) and retrieval augmented generation (RAG), EY enabled financial institutions to extract insights from unstructured data like ESG reports and financial documents, increasing accuracy by 10%–15% and delivering results 3x faster than native RAG setups. The solution also helped accelerate development, improve compliance, and scale innovation across teams and data formats. Read the full story.
Elastic and Microsoft: Building the infrastructure for responsible AI
Elastic provides a scalable foundation for financial services firms implementing AI, built on vector databases that can handle both current and future demands. As Minetola explained, this foundation offers “a single platform to be at the heart of your organization’s GenAI activity, creating simple, scalable, open, powerful solutions which are all in one place.” The Elastic Search AI platform combines advanced storage optimization — reducing storage needs by up to 65% — with comprehensive visibility across all data types and sources. This unified approach allows FSIs to maintain regulatory compliance while driving innovation, offering the transparency needed for validation and reporting.
Through our partnership with Microsoft, our joint solution delivers enterprise-wide search, observability, and security, allowing financial services organizations to centrally manage data governance while maintaining the flexibility to adapt to evolving regulations.
Watch the full session: AI and compliance in practice
Responsible AI adoption is achievable with the right architecture, data readiness, and governance in place.
Watch the full session now to hear directly from experts at Elastic and Microsoft on how financial services firms can balance innovation, performance, and compliance at scale.
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