Implementation of robust input/output validation mechanisms in financial calculation engines

Posted: Dec 06, 2025

• Ella Robinson
• Emily Clark
• Emily Johnson

Abstract

Financial calculation engines represent critical infrastructure in modern financial systems, responsible for computing valuations, risk metrics, trading decisions, and regulatory compliance calculations. The integrity of these calculations directly impacts financial stability, regulatory compliance, and organizational profitability. Traditional validation approaches in financial systems have primarily employed basic syntactic validation and range checking, which prove insufficient against sophisticated financial attacks and subtle calculation anomalies. The increasing complexity of financial instruments, coupled with the rise of algorithmic trading and real-time risk management, demands more sophisticated validation mechanisms that can operate within the stringent performance constraints of financial systems. This research addresses the fundamental limitations of current financial calculation validation by proposing a comprehensive framework that integrates multiple validation techniques throughout the calculation lifecycle. Unlike traditional approaches that treat validation as discrete pre-processing and post-processing steps, our methodology embeds validation as an intrinsic component of the calculation process. This paradigm shift enables detection of anomalies that manifest only during intermediate calculation stages or through complex interactions between multiple calculation components. The novelty of our approach lies in three key aspects: the integration of formal verification methods with runtime monitoring, the application of cross-validation techniques across temporal and logical dimensions, and the development of validation mechanisms that adapt to evolving financial patterns. By treating validation as a continuous process rather than discrete checks, our framework can detect sophisticated attacks that bypass traditional validation layers while maintaining the computational efficiency required by high-frequency financial systems.