Engineering the next phase of finance
Sasibhushan Rao (Sasi) Chanthati, AVP and Senior IEEE at T. Rowe Price, has built a career at the intersection of finance and technology. He has authored papers, earned U.S. copyrights, and published books, but his day-to-day work focuses on creating secure, scalable systems that can adapt to continuous change.
“Continuous improvement and continuous development are required,” Chanthati said. “Business rules, regulations, and technology updates change daily.”
Generative AI and the rise of small language models
Chanthati highlighted how generative AI and specialized small language models are reshaping financial services. Large models are powerful, but small models trained on narrow domains such as fraud detection deliver precision and security.
“Small language models mean training on a specific business process,” he said. “For example, a bank may train only on credit card fraud scenarios, keeping customer information masked while delivering highly accurate results.”
That combination of accuracy, speed, and privacy makes them a major trend in financial AI adoption.
Security layers and trust
In financial services, trust is foundational. Chanthati stressed that enterprise adoption of AI requires layered security. From Microsoft Copilot to ServiceNow, every deployment must include VPN restrictions, identity access management, and multi-layered controls.
“It goes with very huge security layers and access management,” he explained. “It’s not a small thing.”
Caution in adoption
While optimistic, Chanthati urged caution.
“One should not be dependent on it,” he said of large language models. “That may give you some wrong outputs also. Without knowing the subject, if we are using it, that may route it totally into a wrong direction.”
For him, AI is a tool that augments but does not replace human expertise.
Mentorship and peer review
Chanthati is also deeply committed to mentorship. He reviews papers for IEEE, guides veterans transitioning to IT careers, and recently began mentoring PhD students in Kazakhstan.
“The common advice I give,” he said, “is to make sure proof of concepts are clear and that results are demonstrated, even if not 100 percent correct.”
Why this matters for our community
Chanthati’s philosophy, which combines continuous improvement, security, mentoring, and cautious adoption of AI, aligns with what Winners’ Circle recognizes in innovation. His focus on specialized models, layered security, and responsibility reflects the future of financial technology.
Learn more about him on his Judge Profile.