Using AI Effectively in Financial Modeling Modeler Responsibility from Problem Definition to Decision Support
Year: 2026
Type: article
Abstract: Artificial intelligence can accelerate financial modeling, but it does not relieve the modeler of responsibility for the model or its conclusions. The central challenge is to use AI effectively without surrendering ownership of the model's purpose, structure, assumptions, logic, and evidence. This article presents the FRAME → DESIGN → BUILD → VERIFY framework as a practical approach to that challenge. FRAME defines the decision, intended user, scope, sources, and required outputs. DESIGN establishes the architecture, economic drivers, assumptions, scenarios, and controls. BUILD implements approved logic in manageable sections that can be understood and tested. VERIFY applies three distinct levels of review: technical verification, financial verification, and decision verification. The framework adds to established modeling practice by defining appropriate AI roles at each stage, identifying evidence of human ownership, and separating technical verification, financial verification, and decision verification. It applies to professional practice and finance education and is illustrated through private wealth management, capital budgeting, and financial forecasting. The modeler remains responsible for the integrity and defensibility of the analysis within the modeler's assigned role, while the decision-maker remains accountable for the decision. The framework does not certify accuracy or replace independent validation, organizational policy, or professional judgment.
DOI: 10.33423/by2k1729
Author: Bridget Lyons
Institution: Sacred Heart University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7225580852