THE FUTURE OF APPLIED AI
in Finance and Banking
New York | December 11, 2025
Sasibhushan Rao Chanthati
AVP Sr. Software Engineer at T. Rowe Price
Sasibhushan Rao Chanthati is a recognized technology leader specializing in ServiceNow platform development for digital enterprise automation. As a Senior Software Engineer and AVP at T. Rowe Price Associates, he plays a pivotal role in designing, developing and delivering business process management solutions across Investment Operations, Governance, Risk, and Compliance (GRC), and intelligent automation within high-stakes financial environments. His work enables scalable, secure, and regulation-aligned digital workflows at one of the most prestigious asset management firms in the United States.
He leads large-scale design, integration, and development efforts, translating complex functional requirements into robust technical solutions. His responsibilities include creating technical specifications, designing scalable architectures, estimating project efforts, and developing solutions using technologies such as ServiceNow, Amazon Web Services (AWS), Python, Artificial Intelligence (AI), and Machine Learning (ML). Mr. Chanthati supports end-to-end system lifecycles, including diagnosing and resolving complex issues, ensuring system stability, and liaising with vendors. He remains actively engaged with emerging technologies and industry standards to ensure continuous innovation and adaptability across enterprise platforms. His contributions reflect a deep understanding of both theoretical and applied software engineering principles, positioning him as a thought leader in enterprise digital transformation.
Mr. Chanthati is a highly regarded technologist in Large Language Models (LLMs) and enterprise AI, with a strong record of original contributions in Generative AI (GenAI), financial risk modeling, cybersecurity, and burnout detection. He has authored four technical books and over ten peer-reviewed research articles published across different reputed journals. His applied AI research, particularly in Large Language Models LLMs-based fraud detection and MongoDB Atlas–powered burnout diagnostics, demonstrates real-world impact across industry verticals.
Mr. Chanthati has been featured as an invited speaker at the prestigious Data Science Salon (DSS) NYC, hosted by S&P Global, where he led discussions on building scalable and secure GenAI systems in banking and capital markets. He has also presented his research at AIR 2025 (Artificial Intelligence & Robotics), a Springer/Scopus-indexed conference, and at the 6th World Conference on Artificial Intelligence: Advances and Applications (WCAIAA 2025), a Springer/Scopus-indexed conference, further cementing his recognition as a thought leader in applied AI and enterprise transformation.
He holds esteemed memberships as a Member of IEEE, IET, BCS and ISACA, and is a Fellow of the Royal Society of Arts (RSA). He serves as a mentor through ACP to U.S. military veterans training them in IT careers and has acted as an award judge for the Business Intelligence Group (BIA) in evaluating excellence in innovation and technology.
Watch in-person: May 15 @ 2:20 – 3:05PM ET
Panel: Building & Scaling Gen AI in Financial Services: From Prototype to Production
Generative AI is reshaping how financial institutions approach innovation—from customer engagement and automation to risk modeling and developer productivity. But moving Gen AI from concept to production in a highly regulated, high-stakes industry is no easy task.
This panel brings together engineering leaders and Gen AI practitioners from S&P Global, T. Rowe Price, Capital One, and American Express to explore how they are:
- Embedding Gen AI into production systems across financial workflows
- Tackling infrastructure and latency challenges for real-time applications
- Addressing security, model governance, and explainability
- Balancing experimentation with enterprise-scale deployment
- Integrating LLMs, RAG pipelines, and internal copilots into existing platforms
Attendees will gain first-hand insight into what it takes to build trustworthy, scalable, and performant Gen AI systems in a world where innovation must meet compliance.