In modern financial institutions, quantitative models underpin trading, risk measurement, capital allocation, and regulatory reporting. These systems influence decisions that affect not only individual firms but also market stability and financial resilience. As models have become more complex, incorporating advanced analytics, automation, and artificial intelligence, the need for independent oversight and governance has grown correspondingly critical. Within this context, Puneet Redu has emerged as a specialist in the governance and independent evaluation of high-impact financial models, progressing from an independent price verification role early in his career to a Vice President role within the audit and risk governance function of a global investment bank.
Puneet’s early work focused on the independent verification of complex financial instruments under volatile market conditions, requiring precise valuation judgment and rigorous challenge of front-office assumptions. This foundation developed into what is now his specialization: the independent audit, review, and governance assessment of quantitative models used for market risk, credit exposure, stress testing, and regulatory capital. In his current role, he evaluates not only the mathematical correctness of models, but also their conceptual design, data dependencies, implementation integrity, performance stability, and fitness for purpose, criteria that are central to regulatory expectations such as the Federal Reserve’s SR 11-7 guidance and the Basel Committee’s principles on model risk and risk data aggregation.
What distinguishes the expert’s work is the integration of advanced quantitative analysis with formal governance, audit, and regulatory standards, a combination typically found only among a small subset of senior professionals within independent risk and control functions. His approach treats model risk not as a narrow technical issue, but as a form of systemic risk that can propagate across institutions if left unchecked. As he has noted, financial disruptions more often arise from over-reliance on opaque or poorly governed models than from deliberate misconduct. Accordingly, his work emphasizes explainability, traceability of data and assumptions, alignment with intended use, and clear accountability for model outputs.
Over the course of his career, Puneet has combined hands-on quantitative model validation with independent model risk audit and governance. During his earlier tenure in global consulting and advisory roles, he directly validated high-impact models, including market risk, counterparty credit risk, and stress testing models, assessing their conceptual soundness, data quality, implementation accuracy, and performance behavior. He later transitioned into independent audit and governance assessment roles, where he has played a leading role in the review of quantitative models and modeling frameworks supporting pricing, risk measurement, capital planning, and stress testing at large financial institutions. While confidentiality obligations limit the disclosure of specific systems or clients, his work consistently strengthens institutional controls over quantitative models that directly affect financial reporting, capital adequacy, and risk management decisions.
Among his key contributions are audit initiatives that assessed and strengthened alignment between model risk and governance practices and enterprise risk frameworks, improving audit readiness and regulatory responsiveness, as well as the identification and remediation of model governance and data quality weaknesses through independent oversight. He has also supported the assessment of Basel-aligned stress considerations within independent model risk audit, contributing to the robustness of capital models under extreme but plausible market conditions.
Puneet’s progression from technical specialist to Vice President reflects the increasing institutional reliance on professionals who can bridge quantitative complexity with governance and regulatory judgment. As financial institutions expand their use of advanced analytics and AI, roles such as his, combining technical depth with independent challenge and systemic risk awareness, remain uncommon and highly specialized, and are increasingly central to effective risk management and regulatory confidence.