In this article, the author introduces a governed AI decision architecture that helps FP&A teams generate options, test them against policy, and produce auditable evidence packs for executive decision-making.
Tom Byrne
Tom has spent over 40 years in Finance in several roles. He is passionate about applying the latest techniques to the FP&A process.
He is retired but undertakes some quant work for Worldquant and other interesting projects as requested.
Tom is a qualified accountant, an experienced performance management systems architect, a business intelligence and business modelling architect, a pre-sales consultant, an internal management consultant, a finance manager, an internal audit manager, a systems manager and more recently, has worked as a test manager at a transformational project for a major multinational company.
He is used to working closely with clients to get the best out of performance management software. Tom has experience in accounting and financial management, corporate finance, machine learning, Economic Value Added, Activity Based Costing, Enterprise Performance Management, statistical forecasting methods, management accounting and quantitative finance.
Specialities: Business strategy reporting, finance management, internal audit management, performance management, management accounting, ABM, EVA, operational research, business modelling, systems design and implementation, Cognos reporting tools and Framework Manager, Infor dEPM, Microsoft Analysis Services, MDX, SQL, VBA, MPC, Essbase, JIRA, PowerBI, Python, quantitative finance and machine learning, especially Scikit-Learn.
Tom has degrees in Maths and Philosophy and Operational Research and Management. He is a qualified accountant and quantitative analyst with certifications in TOGAF from The Open Group and in Machine Learning from WorldQuant University. He also has the Infor 'Black Belt' Solutions Architect certification.
Author's Articles
In this article, the author demonstrates how AI can become a governed strategic collaborator in FP&A by combining operating-environment sensing with controlled model evolution under explicit human approval gates.
In this article, the author explains how AI in FP&A can evolve from automation to a governed strategic partner, if decision rights, governance artefacts, and accountability are deliberately designed.
In this article, the author describes the Systems Thinking approach and shows how it impacted FP&A and Management, referring to his experience in the automotive industry.
+
Subscribe to
FP&A Trends Digest
We will regularly update you on the latest trends and developments in FP&A. Take the opportunity to have articles written by finance thought leaders delivered directly to your inbox; watch compelling webinars; connect with like-minded professionals; and become a part of our global community.