Agenda Day 2

The next decade will likely not belong to the loudest technology, but to the organizations that turn data, automation and intelligent systems into trusted, everyday business habits. Across a multiplicity of business functions, CDOs and their C-suite peers will shape how risk, insight and innovation coexist in a compliant, customer-centric enterprise. Peers from across Banking, Insurance and Financial Services industries will explore what the data-driven enterprise of 2030 looks like – and what cultural, architectural and leadership shifts must begin now so you don’t lag behind.

• Explore the operating models, architectures and cultural shifts that separate future data-driven leaders from those left managing yesterday’s dashboards.

• How developed will BFSI organisations be in utilizing and scaling innovative technologies, such as AI, in 2030?

• Hear how the future data team will likely construct its data stack to remain ready for future eventualities to mitigate potential risks.

• Delve into the predictions of peers on how the BFSI enterprise will operate in 2030, and what will likely matter most to boards, regulators and customers.

Frank Bernhard

Chief Data & Analytics Officer
.

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Chetan Desai

Head of Data Governance and Operations
Guardian Life

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Melissa Richards

Chief Data Officer
Renasant Bank

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Gotham Pasupuleti

Head of Data & AI for Core Banking Solutions
FIS Global (Fidelity National Information Services)

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Gain a regulators eye-view of enforcement priorities across model risk management, algorithmic fairness, customer facing transparency and third-party AI accountability, translated into practical operating controls that work across the nation.

• Dive into the most common, and strictest, regulatory hurdles for CDOs including state-specific consumer privacy laws such as CCPA/ Texas HB1401 and how to easily remain compliant.

• Understand the top non-negotiable controls that satisfy 95% of current regulation for CDOs in the BFSI industries.

The first wave of generative AI in BFSI was dominated by enterprise chatbots and poorly organised data, leading to a lot of experiments, but limited value. The next wave is different. In this session, Nick Lachman will focus on agentic AI applied to clearly defined, high impact processes, where inputs, outputs, and value are concrete. He'll share how his team frames use cases, measures value realization and holds executives accountable for capturing those gains. Leave with practical ideas on how to build a roadmap that the C suite will actually support.

Nickolaus Lachman

SVP, Head of AI & Automation
Valley Bank

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Everyone Wants AI, No One Wants the Accountability but how do you Rethink Governance for the Agentic Era? As organisations rush to experiment with generative and agentic AI, many are discovering that their mature datam governance frameworks are not enough. AI introduces a different class of risk, accountability, and lifecycle challenges: it is no longer just about whether the data is good, but whether the entire AI solution continues to behave as intended—five days, five months, or five years after deployment. In this session, unpack the critical differences between data governance and AI governance, and why treating them as the same discipline leads to ownership gaps, blurred accountability, and failed scaling of promising pilots. Drawing on practical experience from building and governing AI solutions in a highly regulated environment, explore:

• Designing governance around evaluation, measurement, and continuous monitoring of AI outcomes

• Where AI governance should sit organisationally – and what happens when "everyone wants the AI but no one wants the accountability"

• Moving beyond pilots by addressing integration, tooling, and siloed experimentation

• Pragmatic steps CDOs can take to evolve from data governance to AI governance that the business can trust

Vinod Shenoy

Executive Director - Conversational AI
Morgan Stanley

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A candid session tracing one CDO's journey across multiple banks, from clashing data strategies and legacy tools to a more mature, human‑centered approach. Rather than focusing on technology alone, it highlights how culture, conflict, and soft skills shape data outcomes. Attendees will gain practical ideas for balancing "demolish and rebuild" vs. "work with what you have," turning detractors into partners, and designing a data roadmap that can evolve as tools, teams, and expectations change.

• Discover the real blockers to data maturity: beyond architecture and tooling into culture, incentives, and competing data strategies.

• Explore how to balance legacy platforms with future‑ready architectures— working with what you have today while quietly preparing for tomorrow's tools.

• Reimagine the CDO's role as a storyteller and coalition‑builder who can turn detractors into long‑term partners and create a resilient, product‑agnostic data roadmap.

Josh Kohr

Chief Data Officer
People's Bank

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The challenge isn't getting leaders excited about AI, it's sustaining belief once the hype fades and the first projects hit real-world constraints. This CDO-CFO duo reveals how to craft experiential narratives blending customer stories, risk scenarios, and revenue projections that hijack attention and demand funding from the wider business.

• Hear how generic tech decks kill buy-in while live demos, and other research-backed storytelling convert sceptical C-suites into data evangelists.

• Master effective storytelling frameworks that can be easily adapted to your organisational structure and buy-in objections.

• Hear how a CFO-CDO have worked together effectively to implement crossfunctional buy-in and secure greater budgets.

Josh Kohr

Chief Data Officer
People's Bank

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