Fragile glass model of a skyscraper on financial spreadsheets symbolizing model risk.

Model Risk and XVAs: Are Banks Underestimating Their True Exposure?

Elliot Brynn in Business & Economy December 2025 • 4 min read.

"A deep dive into how model inaccuracies impact valuation adjustments and capital reserves in financial institutions, revealing a potential need for more conservative risk management."

In the complex world of finance, banks rely on models to make critical decisions, from pricing derivatives to managing risk. But what happens when these models are wrong? Model risk, the potential for inaccuracies in these tools, can have a significant impact on a bank's financial health, particularly when it comes to valuation adjustments (XVAs).

A new research paper is shedding light on this often-underestimated threat. The paper revisits the concept of hedging valuation adjustment (HVA), originally designed to address dynamic hedging frictions like transaction costs. The authors argue that HVA should also account for model risk, ensuring that banks hold adequate reserves to cover potential losses stemming from inaccurate models.

The stakes are high, especially in the wake of financial crises that have exposed the weaknesses in risk management frameworks. As regulatory bodies increase scrutiny and capital requirements, banks need to take a closer look at how model risk is impacting their XVAs and overall capital reserves. Ignoring this critical factor could lead to underestimation of risk and potential financial instability.

Understanding Cross Valuation Adjustments (XVAs)

Fragile glass model of a skyscraper on financial spreadsheets symbolizing model risk.

Cross Valuation Adjustments (XVAs) are a suite of calculations that banks use to account for various risks associated with financial transactions. These adjustments ensure that the true economic value of a deal is reflected on the balance sheet, considering factors like counterparty credit risk, funding costs, and capital requirements. Major components of XVAs include:

To fully grasp the essence of model risk, it's important to know the major components of XVAs. In this case, it's good to understand CVA, FVA, and KVA. These components form the building blocks for understanding the arguments for model risk.

Credit Valuation Adjustment (CVA): This adjusts for the potential loss due to a counterparty's default. It considers the probability of default and the expected exposure to the counterparty.
Funding Valuation Adjustment (FVA): This reflects the cost of funding uncollateralized trades. It accounts for the difference between the interest earned on assets and the interest paid on liabilities.
Capital Valuation Adjustment (KVA): This represents the cost of holding capital against potential future losses. It acknowledges the economic impact of regulatory capital requirements.

XVAs are complex and require careful aggregation across different levels of a financial institution. CVA can be calculated at the individual client level, while FVA and KVA need to be assessed at the portfolio level, encompassing all positions and risk factors.

The Path Forward: Banning Bad Models

The research suggests a bold solution: instead of trying to manage model risk through complex reserves and adjustments, banks should focus on improving the quality of their models in the first place. According to research, poorly designed models, when adjusted for, require far more capital than properly designed models. Additionally, risk-adjusting poorly designed models can be very computationally exhaustive, so it makes the most sense to ban these models. While this may require more upfront investment in sophisticated modeling techniques, the long-term benefits of reduced risk and greater financial stability outweigh the costs. By prioritizing accuracy and reliability, banks can reduce their exposure to model risk and build a more resilient financial system.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2205.11834,

Title: Handling Model Risk With Xvas

Subject: q-fin.pr math.pr q-fin.cp

Authors: Cyril Bénézet, Stéphane Crépey

Published: 24-05-2022

Everything You Need To Know

What are Valuation Adjustments (XVAs) and why are they important for banks?

Valuation Adjustments, or XVAs, are a suite of calculations used by banks to account for various risks associated with financial transactions. They ensure that the true economic value of a deal is reflected on the balance sheet, considering factors like counterparty credit risk (CVA), funding costs (FVA), and capital requirements (KVA). XVAs are important because they help banks accurately assess the risks they are taking and hold adequate capital reserves to cushion against potential losses. Failing to accurately account for these adjustments can lead to an underestimation of risk and potential financial instability.

Can you explain the components of XVAs, such as CVA, FVA, and KVA?

Certainly. Credit Valuation Adjustment (CVA) adjusts for the potential loss due to a counterparty's default. It considers the probability of default and the expected exposure to the counterparty. Funding Valuation Adjustment (FVA) reflects the cost of funding uncollateralized trades, accounting for the difference between the interest earned on assets and the interest paid on liabilities. Capital Valuation Adjustment (KVA) represents the cost of holding capital against potential future losses, acknowledging the economic impact of regulatory capital requirements. These components are essential for a comprehensive understanding of the various risks banks face.

How does 'model risk' impact the accuracy of XVAs, and why is this a concern for financial institutions?

Model risk, which refers to the potential for inaccuracies in the models used by banks, can significantly impact the accuracy of XVAs. If models are flawed, the calculated adjustments might underestimate the true risks, leading to insufficient capital reserves. This is a major concern because it could leave financial institutions vulnerable to unexpected losses, particularly in times of market volatility. Addressing model risk within XVAs is crucial for ensuring the financial health and stability of banks.

What does the research suggest about managing model risk, and what are the potential benefits of prioritizing better model design?

The research suggests that instead of trying to manage model risk through complex reserves and adjustments, banks should focus on improving the quality of their models. Poorly designed models, even when adjusted for, require far more capital and computational effort than properly designed ones. Prioritizing better model design can reduce a bank's exposure to model risk, decrease the need for extensive capital reserves, and lead to greater financial stability. While it may require more upfront investment, the long-term benefits of accuracy and reliability outweigh the costs.

How can banks improve their approach to HVA (Hedging Valuation Adjustment) to better account for model risk?

Banks should expand the scope of Hedging Valuation Adjustment (HVA) to explicitly account for model risk, ensuring that they hold adequate reserves to cover potential losses stemming from inaccurate models. Originally, HVA was designed to address dynamic hedging frictions like transaction costs. By incorporating model risk, banks can better prepare for unexpected losses due to model deficiencies, leading to more conservative risk management. Additionally, banks should focus on improving model quality to reduce the need for extensive adjustments.