Enterprise AI Architect for Treasury · Author · Speaker · Founder, Valorean · Former EY Managing Director · CTP
I work directly with CFOs and Treasury leaders to define the right Enterprise AI architecture for Treasury — combining deep Treasury domain expertise, SAP S/4HANA architecture, and Enterprise AI.
My role is to help you decide what should — and should not — be built, how it should work, where AI creates genuine value, and how it operates within the controls, transparency, and human accountability the profession requires.
The engagement is with you directly — no account team, no bench. Once the architecture is settled, I can work with your internal technical team, with my own, or alongside an integrator you choose.
Your success is measured by the quality of the architecture and the outcome it delivers — not by the size of the implementation team.
On the Treasury Update Podcast
Strategic Treasurer
A conversation on the automation spectrum in treasury — from rules-based processing and analytics to AI assistance and autonomous agentic systems. Practical use cases across cash forecasting, hedge management, fraud detection, payment processing, and reconciliation, alongside the clean data, controls, governance, explainability, and human oversight that make enterprise AI trustworthy in production.
A conversation on five key limitations of enterprise AI in treasury — data quality, pattern-based reasoning without true understanding, difficulty handling novel situations, variable outputs, and limited explainability — and the opportunities and solutions that address them, including AI-assisted data cleanup, anomaly detection, stronger controls, human oversight, and safer agent-based system design.
And available now
A Guide to Agentic Implementation
By Arjun Krishnan, CTP · Foreword by Brad Larson
Enterprise-wide systems have transformed how treasury and finance teams manage cash, risk, payments, and liquidity. Automation executes. Analytics report. And yet, a significant part of their working day is still spent on what the systems cannot quite finish — reconciling exceptions, investigating anomalies, validating forecasts, and converting fragmented signals into decisions.
That is where agentic AI changes the equation — bringing intelligence to the data and decisions that automation alone cannot resolve. Treasury now has access to systems that can reason across data sources, interpret context, prioritize what requires attention, and act within boundaries the treasury professional defines.
Enterprise AI for Treasury is a practitioner's guide to that transformation — written from a business perspective and designed for anyone with a stake in getting this right: the treasurer evaluating AI investments, the CFO trying to separate signal from noise, the analyst curious about how these tools will affect their work, the technology professional exploring treasury applications, and the entrepreneur building a business where cash flow is the lifeblood of growth.
Available in paperback and Kindle
Read the book on AmazonIf something in the podcasts, the book, or the case studies sparked a thought or question — or if you're working through a Treasury transformation, an AI initiative, or an architectural decision and would value an independent perspective — please reach out.
You can connect with me directly at arjun@valorean.ai
Or if you'd rather book a time to talk directly:
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