FNB Names Santosh Sinha and Sundeep Tangirala Senior Vice Presidents to Lead AI and Data Science Strategy

FNB Adds AI and Data Science Directors to Strategy Leadership Team

First National Bank, the largest subsidiary of F.N.B. Corporation (NYSE: FNB), has appointed two senior leaders to accelerate data-driven strategy: Santosh Sinha as Director of AI and Innovation and Sundeep Tangirala as Director of Data Science. Both join as Senior Vice Presidents and report to Chris Chan, Chief Strategy Officer.

"Innovation and digital technology are significant drivers of FNB's growth and superior client experience," said Vincent J. Delie, Jr., Chairman, President and CEO of F.N.B. Corporation and First National Bank. "Our latest hires bring highly specialized expertise to expand the powerful ways that AI, data science and quantitative modeling inform our strategic planning and service delivery."

Why these hires matter for strategy

• AI as a core capability: Sinha will develop and execute the AI strategy with a clear emphasis on ethical and compliant practices, prioritizing high-value use cases and cross-functional delivery.
• Decisioning at scale: Tangirala will oversee strategic decisioning systems and the full lifecycle of regulatory and forecasting models, driving revenue growth, efficiency, and process improvements across Retail and Wholesale Banking, Marketing, Credit, and Risk.
• Direct line to strategy: Reporting to the CSO signals that AI and data science are embedded in enterprise planning, not siloed in IT.

The leaders behind the roles

Santosh Sinha brings a decade of financial services experience, plus a background as a technology startup cofounder and AI researcher for the U.S. government. He holds a BS in computer science and engineering (Patna University, India), an MBA in strategic leadership (Dallas University), and a PhD in data science/AI and business analytics (Capitol Technology University). He also serves on the advisory board for the Journal of Artificial Intelligence and Knowledge Engineering.

Sundeep Tangirala previously served as SVP and Head of Data and Machine Learning Engineering at PNC Bank, with 20+ years in technology and nearly 15 in financial services. He serves on the MS in Quantitative Economics advisory board at the University of Pittsburgh. His credentials include a BE in computer science (Anna University, India), an MS in business IT (Middlesex University, UK), and a Machine Learning Certificate (Cornell University).

What executives can expect next

• Clear AI governance: Expect formal guardrails aligned with leading frameworks such as the NIST AI Risk Management Framework (reference), with defined ownership across model development, validation, monitoring, and issue management.
• Faster cycle time from insight to impact: A tighter loop between data science, product, and compliance to move prioritized use cases into production with measurable results.
• Balanced growth and risk: Investment in decisioning systems that improve conversion, pricing accuracy, credit quality, and fraud detection while meeting regulatory expectations.

Suggested 90-day focus areas for leadership teams

• Prioritize 3-5 high-value use cases (e.g., cross-sell decisioning, credit line management, marketing optimization, loss forecasting) with clear success criteria and owners.
• Stand up an AI/Model Risk Review Council with Product, Risk, Legal, Compliance, and Internal Audit participation.
• Publish an AI policy and model inventory, including explainability, fairness, privacy, and third-party model controls.
• Codify MLOps standards: versioning, monitoring for drift, human-in-the-loop, rollback plans, and post-deployment reviews.
• Tie initiatives to unit economics: cost-to-serve, approval time, loss rate, fee income, and customer lifetime value.

Execution metrics to track

• Model adoption rate in frontline workflows
• Incremental revenue and cost savings per use case
• Cycle time: data-to-decision and model-to-production
• Model stability: drift, bias, overrides, and alert resolution time
• Compliance outcomes: validation findings and remediation SLAs

About F.N.B. Corporation

F.N.B. Corporation (NYSE: FNB) is a diversified financial services company headquartered in Pittsburgh, operating across seven states and Washington, D.C., with nearly $50 billion in assets and approximately 350 banking offices. Its offerings span corporate banking, small business banking, real estate financing, government banking, capital markets, leasing, consumer banking, mortgage and consumer lending, digital banking, and wealth management services through First National Bank of Pennsylvania, founded in 1864.

For teams building capability

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