Stephen Greer | Source | Banking Industry Consultant at SAS
Stephen Greer
Stephen Greer is an Advisory Industry Consultant for North American Financial Services at SAS. He advises financial services clients on how to get the most of their technology investments in advanced data modeling, AI and machine learning, deep learning, and business intelligence. His focus areas included use cases within risk management (balance sheet risk, credit risk, market risk), fraud and financial crime (AML/KYC, Digital ID, payments fraud), and customer intelligence (personalization & engagement, customer decisioning).
Prior to joining SAS, Stephen spent more than a decade in advisory/consulting with banks and vendors of all sizes on projects related to product/corporate strategy, system selection, verticalization, emerging technology, emerging business models, and more. He was formerly a Senior Analyst at Celent.
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SAS
Banking Industry Consultant
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US News | Are Hybrid Bank Accounts Worth It? (30April2025)
"Hybrid" bank accounts combine features of checking and saving accounts, but may come with certain requirements.
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BAI Banking Strategies | Bank performance benchmarking matures as a strategic tool (08April2025)
Tracking peer performance, from branch selection to efficiency ratios and more, can help flag missed opportunities or signal when a course correction is due.
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The Fintech Times | The Impact of AI: A Turning Point for Traditional Back-Office Operations (22Feb2025)
A couple of years after its initial boom, artificial intelligence (AI) still remains a huge buzzword in the fintech industry, as every firm looks at a new way of integrating the tech into its infrastructure to gain a competitive edge.
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Agentic AI: Transforming U.S. Retail Banking Operations
Stephen notes that internal applications of Agentic AI, like "document summarization and sentiment analysis," are more valuable than customer-facing ones. He envisions AI agents autonomously managing finances, transforming banking into holistic financial services. However, challenges like "data security, talent gaps, and regulatory issues" remain significant hurdles. -
Embedded Finance: Traditional Banks' Role and Customer Expectations
Stephen highlights that traditional banks are "critical to the entire embedded finance ecosystem," despite compliance challenges. He asserts embedded finance won't make standalone banking apps obsolete, as banks are trusted for comprehensive services. Stephen notes that embedded finance has shifted customer expectations, pushing traditional banks to innovate and match digital experiences offered by neobanks. -
AI Automation in Banking: Balancing Innovation and Risk
Stephen highlights the critical nature of back-office functions, warning of potential cascading failures in automated systems. He notes AI's role in enhancing process efficiency and fraud detection, while emphasizing the cloud's transformative impact. "Automation can involve more complex integrations," Stephen says, pointing to risks of integration issues.
