Accounting
Assessing credit losses in financial statement audits: A guide for auditors
Credit losses represent a significant area of focus in financial statement audits. As economic conditions fluctuate and accounting standards evolve, auditors face increasing challenges in evaluating how organizations estimate and report credit losses, and in providing a comprehensive overview of credit loss assessment in financial statement audits.
This article will explore the concept of credit losses, examine relevant regulatory frameworks, discuss vital challenges auditors encounter, and offer best practices for effectively auditing credit loss estimates. In addition, it will also describe key emerging trends and technologies shaping the future of credit loss auditing.
Credit losses occur when a borrower fails to repay a debt according to the initial agreement. These losses are typically reported as allowances for credit losses or loan loss provisions in financial statements. They represent the estimated amount of debt that may not be collected, reflecting the credit risk associated with a company’s financial assets.
For auditors, understanding how companies calculate and report credit losses is crucial. This process often involves complex estimates and judgments, as companies must forecast future economic conditions and borrower behavior. The shift toward more forward-looking models, such as the Current Expected Credit Loss model in the United States, has further increased the complexity of these estimates.
Auditors must evaluate whether these estimates are reasonable and supported by appropriate evidence, ensuring that financial statements accurately reflect the company’s credit risk exposure.
Regulatory framework and standards
Various standards and regulations govern the accounting for credit losses, which have undergone significant changes in recent years. In the United States, the Financial Accounting Standards Board introduced Accounting Standards Update 2016-13, which implemented the CECL model. Internationally, the International Accounting Standards Board
These standards require companies to recognize expected credit losses over the life of a financial asset rather than waiting for a loss event to occur. This forward-looking approach aims to provide financial statement users with more timely and relevant information about credit risk.
Auditors must stay current with these standards and any related interpretations or guidance issued by regulatory bodies. They must also understand how these standards apply to different types of financial assets and industries to effectively audit credit loss estimates.
Critical challenges in auditing credit losses
Auditing credit losses presents several challenges:
- Complexity of models: Credit loss models often involve complex statistical techniques and numerous assumptions. Auditors must assess whether these models are appropriate and whether the assumptions used are reasonable.
- Data quality and availability: The accuracy of credit loss estimates depends heavily on the quality and completeness of historical and current data. Auditors must evaluate the reliability of data sources and the processes used to collect and maintain this information.
- Judgment and estimation uncertainty: Credit loss estimates involve significant judgment, particularly in forecasting future economic conditions. Auditors must evaluate the reasonableness of these judgments and ensure appropriate disclosure of estimation uncertainty.
- Rapidly changing economic conditions: Economic volatility can quickly render historical data and assumptions obsolete. Auditors must consider how companies have incorporated recent economic trends and events into their estimates.
- Internal controls: Assessing the effectiveness of internal controls over the credit loss estimation process is crucial but can be challenging due to the complexity and judgment involved.
- Potential management bias: Given the subjective nature of credit loss estimates, there’s a risk of management bias. Auditors must remain skeptical and alert to potential manipulations of these estimates.
Best practices for auditors
To effectively audit credit losses, auditors should consider the following best practices:
- Develop a thorough understanding: Gain in-depth knowledge of the company’s business model, credit risk management practices and the specific credit loss estimation methodology.
- Assess model appropriateness: Evaluate whether the credit loss model aligns with accounting standards and suits the company’s specific circumstances. When dealing with complex models, consider involving specialists.
- Test key assumptions: Critically evaluate the reasonableness of key assumptions used in the credit loss model. This may involve comparing assumptions to industry benchmarks, historical data, and economic forecasts from reliable sources.
- Perform sensitivity analyses: Assess how changes in key assumptions impact the credit loss estimate to understand the model’s sensitivity and identify potential areas of concern.
- Evaluate data integrity: Test the completeness and accuracy of data used in the credit loss model. This includes both historical data and current information used to inform forward-looking estimates.
- Review disclosures: Ensure financial statement disclosures adequately explain the credit loss estimation process, key assumptions and areas of uncertainty.
- Assess internal controls: Thoroughly evaluate internal controls’ design and operating effectiveness over the credit loss estimation process.
- Consider management bias: When selecting assumptions or data used in the estimation process, remain alert to potential indicators of management bias.
- Document thoroughly: Maintain clear and comprehensive documentation of audit procedures performed, evidence obtained, and conclusions regarding credit loss estimates’ reasonableness.
- Stay updated: Continuously monitor changes in accounting standards, regulatory guidance, and industry practices related to credit loss estimation and auditing.
Emerging trends and technologies
The field of credit loss auditing is evolving rapidly, driven by technological advancements and changing regulatory landscapes. Emerging trends include:
- Increased use of artificial intelligence and machine learning in credit loss modeling;
- Greater emphasis on real-time data analysis and continuous auditing techniques;
- Enhanced data analytics tools for identifying patterns and anomalies in large datasets;
- Growing focus on climate-related risks and their potential impact on credit losses; and,
- Increased regulatory scrutiny of credit loss estimates, particularly during economic uncertainty.
The impact of AI on auditing credit losses
Artificial intelligence is revolutionizing how credit losses are estimated and audited. Its ability to quickly process vast amounts of data and identify complex patterns is particularly valuable in this field.
Here are some key areas where AI is making a significant impact:
1. Enhanced pattern recognition. AI algorithms can analyze historical data to identify subtle patterns indicating increased credit risk. For example, an AI system might detect that customers who make frequent small purchases followed by large purchases are more likely to default. This pattern might need to be more nuanced for traditional analysis methods to catch.
Example: An auditor reviewing a bank’s credit loss estimates could use AI to analyze the transaction patterns of thousands of credit card holders. The AI might identify a correlation between certain spending behaviors and the likelihood of default that the bank’s model hasn’t accounted for, prompting the auditor to question the completeness of the bank’s risk assessment.
2. Improved forecasting. AI models can incorporate a broader range of variables and data sources to improve the accuracy of credit loss forecasts. This includes nontraditional data such as social media posts, online behavior, or macroeconomic indicators.
Example: When auditing a mortgage lender’s expected credit losses, an AI system could analyze not just traditional factors like credit scores and income but also incorporate data on local real estate trends, employment statistics, and even climate change projections for coastal properties. The auditor could assess whether the lender’s forecasting model is sufficiently comprehensive.
3. Real-time risk assessment. AI systems can continuously update risk assessments as new data becomes available, allowing for more dynamic credit loss estimates.
Example: An auditor reviewing a company’s accounts receivable might use an AI tool that continuously monitors customer payment behaviors, news about customer companies, and industry trends. This could help the auditor assess whether the company’s credit loss allowances are updated frequently enough to reflect current risks.
4. Anomaly detection. AI can quickly identify unusual patterns or transactions that might indicate errors in credit loss calculations or potential fraud.
Example: When auditing an extensive portfolio of loans, an AI system could flag individual loans or groups with risk characteristics that don’t align with their assigned risk ratings. This could help auditors focus on areas where the credit loss estimates might need to be more accurate.
5. Automation of routine tasks. AI can automate many routine aspects of auditing credit losses, such as data gathering, reconciliations, and basic calculations. This allows auditors to focus more on complex judgments and risk assessments.
Example: An AI system could automatically gather loan data, calculate expected loss rates based on historical performance, and compare these to the client’s estimates. The auditor could then focus on evaluating the reasonableness of any differences and assessing the qualitative factors that might justify them.
6. Enhanced scenario analysis. AI can rapidly run multiple complex economic scenarios to stress-test credit loss models, providing auditors with a more comprehensive view of potential risks.
Example: When auditing a bank’s loan loss provisions, an AI system could quickly generate and analyze hundreds of potential economic scenarios, considering factors like interest rates, unemployment and GDP growth. This could help the auditor assess whether the bank’s scenario analysis is sufficiently robust and comprehensive.
While AI offers significant benefits, it’s important to note that it also introduces new challenges for auditors. These include ensuring the reliability and appropriateness of AI models, understanding the “black box” nature of some AI algorithms, and maintaining professional skepticism when working with AI-generated insights. Auditors must develop new skills to effectively leverage AI tools while still applying their professional judgment to the audit process.
Auditors should stay informed about these trends and consider how they might impact their audit approaches and methodologies.
Final word
Auditing credit losses remains a complex and challenging task. By staying informed, applying best practices, and leveraging emerging technologies, auditors can enhance the effectiveness and efficiency of their work, ultimately contributing to the reliability and transparency of financial reporting.
Over the last few years, AI has gone from being a novelty to a mission-critical business strategy for many accountants. Innovative, forward-thinking firms are using these tools to streamline manual tasks, ensure compliance and provide the best possible service to their clients. According to the 2025 Intuit QuickBooks
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However, AI adoption is at varying levels across the industry. While nearly every firm has begun experimenting with basic AI tools, many remain in a sandbox phase, hesitant to move toward full-scale integration due to perceived complexity or costs.No matter where you may fall on the integration spectrum, the fact remains: AI is rapidly reshaping the accounting industry. If you’ve delayed AI adoption in your business, you’ll want to create a focused plan to catch up.
Time is of the essence, but don’t sacrifice strategy for speed
Firms that are ready to take the leap from casual use to deep integration may find themselves in need of accelerated adoption, but speed should not come at the cost of strategy. Identify tangible, practical ways that easy-to-use tools can impact your business through automation. Having a strong strategic focus allows firms to implement workflow changes to streamline manual tasks, ensure compliance and provide excellent service to your clients.
To begin your AI journey, here is a four-step plan that firms can use to transition from experimentation to execution, in a safe, practical manner:
Step 1: Kick off your first AI project
As is the case with many things, getting started is often the most challenging step. While enthusiasm is high, uncertainty with implementation risks can cause hesitation. The key is to lower risk by embracing AI and implementing an intentional, phased approach. Begin by weaving AI tools into high-impact, low-risk tasks, such as summarizing meeting notes, drafting client or firm-wide memos, or translating complex concepts into easy-to-understand ideas. Monitor results carefully and, if these initial attempts need adjustment, be prepared to pivot to the next use case until you can clearly demonstrate that AI systems are delivering a measurable impact on your operations. From there, you can learn from early experiences, adapt strategy, and scale appropriately to complete more complex projects.
Step 2: Dig into your AI toolkit
The marketplace is crowded with AI-powered tools that promise to do everything from enhancing your workflows to improving the customer experience. It can be hard to know which ones are worth investing your time and money. Find a trusted source like a respected peer, or leverage your professional network to help discuss the tools that may be the best fit for achieving your business goals. You can also look within the tools you’re already using to see if they offer AI-powered features, which can help ease into the transition. Additionally, look for free high-quality education to upskill your team. For example, Anthropic offers a Claude AI University that provides excellent foundational resources for moving beyond basic prompts.
Step 3: Review an AI security checklist
An important element in AI implementation is security. With AI tools needing access to firm and client data to function, it leads to questions of how the data will be protected. This makes the right AI and cybersecurity strategy critical. Firms must proactively ensure that client data remains protected from today’s increasingly sophisticated threats by embracing an established cybersecurity framework such as
Step 4: Openly discuss AI usage with your clients
Once you’ve established the best way to use AI tools that meet your firm’s needs, you’ll want to communicate all of the advantages afforded by these tools to your clients. Make sure you highlight the benefits and simultaneously ensure you are addressing any potential concerns. It’s also important to get explicit consent from all clients if you’re sharing their information with the third-party tools you may use. While this might seem like an extra step, it will go a long way toward fostering a greater level of transparency and deepen trust between you and your clients.
Don’t get left behind
Adopting AI does not have to be intimidating, expensive or overly complex. Think of it as a strategic business move that will not only keep you competitive, but will potentially free you up to focus on keeping clients happy and growing your practice. By strategically focusing on these best practices, identifying AI use cases in a phased approach, evaluating the right tools for your business, ensuring client information is secure and clearly communicating your AI strategy, you’ll be AI-ready in no time.
The Financial Accounting Standards Board met this week to discuss its projects on accounting for transfers of cryptocurrency assets and enhancing the disclosures around certain digital assets, such as stablecoins.
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During Wednesday’s meeting, FASB’s board made certain tentative decisions, according to a
At a future meeting, the board plans to consider clarifying the derecognition guidance for crypto transfer arrangements to assess whether the control of a crypto asset has been transferred.
FASB also began deliberations on the
The board decided to provide illustrative examples in Topic 230, Statement of Cash Flows, to clarify whether certain digital assets such as stablecoins can meet the definition of cash equivalents. It also decided to include the following concepts in the illustrative examples:
- Interpretive explanations that link to the current cash equivalents definition;
- The amount and composition of reserve assets; and,
- The nature of qualifying on-demand, contractual cash redemption rights directly with the issuer.
FASB plans to clarify that an entity should consider compliance with relevant laws and regulations when it’s creating a policy concerning which assets that satisfy the Master Glossary definition of the term “cash equivalents“ will be treated as cash equivalents.
“I agree with the staff suggestion to look at examples,” said FASB vice chair Hillary Salo. “From my perspective, I think that is going to help level the playing field. People have been making reasonable judgments. I agree with that. And I think that this is really going to help show those goalposts or guardrails of what types of stablecoins would be in the scope of cash equivalents, and which ones would not be in the scope of cash equivalents. I certainly appreciate that approach, and I think it has the least potential impact of unintended consequences, because I do agree with my fellow board members that we shouldn’t be changing the definition of cash equivalents, and it’s a high bar to get into the cash equivalent definition.”
“I’m definitely supportive of not changing the definition of cash equivalents,” said FASB chair Richard Jones. “I believe that’s settled GAAP in a way, and we’re not really seeing a call to change it for broader issues. I am supportive of the example-based approach. The challenge with examples, though, is everybody’s going to want their exact pattern, but that’s not what we’re doing.”
The examples will explain the rationale for how digital assets such as stablecoins do or do not qualify as cash equivalents and give a roadmap for other types of digital assets with varying fact patterns to be able to apply.
“We really don’t want to be as a board facing a situation where something was a cash equivalent and then no longer is at a later date,” said Jones. “That’s not good for anyone, so keeping it as a high bar with certain rigid criteria, I think, is fine.”
Stablecoins are supposed to be pegged to fiat currencies such as U.S. dollars and thus provide more stability to investors. “In my view, while a stablecoin may meet the accounting definition established for cash equivalents, not every one of those stablecoins in the cash equivalent classification represents the same level of risk,” said FASB member Joyce Joseph.
She noted that the capital markets recognize the distinctions and have established a Stablecoin Stability Assessment Framework to evaluate a stablecoin’s ability to maintain its peg to a fiat currency. Such assessments look at the legal and regulatory framework associated with the stablecoin, and provide investors with information that could enable them to do forward-looking assessments about the stability of the stablecoin.
“However, for an investor to consider and utilize such information for a company analysis the financial statement disclosures would need to include information about the stablecoin itself,” Joseph added. “In outreach, the staff learned that investors supported classifying certain stablecoins as cash equivalents when transparent information is available about the entities at which the reserve assets are held. Therefore, in my view, taking all of this into consideration a relevant and informative company disclosure would include providing investors with the name of the stablecoin and the amount of the stablecoin that is classified as a cash equivalent, so investors can independently assess the liquidity risks more meaningfully and more comprehensively by utilizing broader information that is available in the capital markets and its emerging information.”
Such information could include the issuer, reserves, governance and management, she noted, so investors would get a more holistic look at the risks that holding the stablecoin would entail for a given company.
The board decided to require all entities to disclose the significant classes and related amounts of cash equivalents on an annual basis for each period that a statement of financial position is presented.
Entities should apply the amendments related to the classification of certain digital assets as cash equivalents on a modified prospective basis as of the beginning of the annual reporting period in the year of adoption.
FASB decided that entities should apply the amendments related to the disclosure of the significant classes and amounts of cash equivalents on a prospective basis as of the date of the most recent statement of financial position presented in the period of adoption.
The board will allow early adoption in both interim and annual reporting periods in which financial statements have not been issued or made available for issuance.
FASB also decided to permit entities to adopt the amendments to be illustrated in the examples related to the classification of certain digital assets as cash equivalents without the need to perform a preferability assessment as described in Topic 250, Accounting Changes and Error Corrections.
The board directed the staff to draft a proposed accounting standards update to be voted on by written ballot. The proposed update will have a 90-day comment period.
Senators introduced several pieces of tax-related legislation this week, including measures aimed at improving customer service at the Internal Revenue Service, cracking down on tax evasion and curbing the carried interest tax break, in addition to efforts in the House to repeal the Corporate Transparency Act.
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Senators Bill Cassidy, R-Louisiana, and Mark Warner, D-Virginia, teamed up on introducing a bipartisan bill, the
The bill would establish a dashboard to inform taxpayers of backlogs and wait times; expand electronic access to information and refunds; expand callback technology and online accounts; and inform individuals facing economic hardship about collection alternatives.
“Taxpayers deserve a simple, stress-free experience when dealing with the IRS,” Cassidy said in a statement Wednesday. “This bill makes the process quicker and easier for taxpayers to get the information they need.”
He also mentioned the bill during a
“I’m happy to meet with the team … and do all I can to make it as good as you want it to be,” said Bisignano.
“My bill would equip the IRS with the legislative mandate to create an online dashboard so that taxpayers can monitor average call wait time and budget time accordingly,” said Cassidy. He noted that the bill would allow a callback for taxpayers that might need to wait longer than five minutes to speak to a representative, and establish a program to identify and support taxpayers struggling to make ends meet by providing information about alternative payment methods, such as installments, partial payments and offers in compromise.
“I know people are kind of desperate and don’t know where to turn for cash, so I think this could really ease anxiety,” he added. “This legislation is bipartisan and is likely to pass this Congress.”
Cassidy and Warner
“Taxpayers shouldn’t have to jump through hoops to get basic answers from the IRS — and in the last year, those challenges have only gotten worse,” Warner said in a statement. “I am glad to reintroduce this bipartisan legislation on Tax Day to ease some of this frustration by increasing clear communication and making IRS resources more readily available.”
Stop CHEATERS Act
Also on Tax Day, a group of Senate Democrats and an independent who usually caucuses with Democrats teamed up to introduce the Stop Corporations and High Earners from Avoiding Taxes and Enforce the Rules Strictly (Stop CHEATERS) Act.
Senate Finance Committee ranking member Ron Wyden, D-Oregon, joined with Senators Angus King, I-Maine, Elizabeth Warren, D-Massachusetts, Tim Kaine, D-Virginia, and Sheldon Whitehouse, D-Rhode Island. The bill would provide additional funding for the IRS to strengthen and expand tax collection services and systems and crack down on tax cheating by the wealthy.
“Wealthy tax cheats and scofflaw corporations are stealing billions and billions from the American people by refusing to pay what they legally owe, and far too many of them are getting a free pass because Republicans gutted the enforcement capacity of the IRS,” Wyden said in a statement. “A rich tax cheat who shelters mountains of cash among a web of shell companies and passthroughs is likelier to be struck by lightning than face an IRS audit, and Republicans want to keep it that way. This bill is about making sure the IRS has the resources it needs to go after wealthy tax cheats while improving customer service for the vast majority of American taxpayers who follow the law every year.”
Earlier this week. Wyden also
The Stop CHEATERS Act would provide the IRS with additional funding for tax enforcement focused upon high-income tax evasion, technology operations support, systems modernization, and taxpayer services like free tax-payer assistance.
“As Congress seeks ways to fund much-needed policy priorities and address our growing national debt, there is one common sense solution that should have unanimous bipartisan support: let’s enforce the tax laws already on the books,” said King in a statement. “Our legislation will make sure the IRS has the resources it needs to confront the gap between taxes owed and taxes paid – while ensuring that our tax enforcement professionals are focused on the high-income earners who account for the most tax evasion. This is a serious problem with an easy solution; let’s pass this legislation and make sure every American pays what they owe in taxes.”
Carried interest
Wyden, King and Whitehouse also teamed up on another bill Thursday to close the carried interest tax break for hedge fund managers that
Carried interest is a form of compensation received by a fund manager in exchange for investment management services, according to a
Under the bill, the
“Our tax code is rigged to favor ultra-wealthy investors who know how to game the system to dodge paying a fair share, and there is no better example of how it works in practice than the carried interest loophole,” Wyden said in a statement. “For several decades now we’ve had a tax system that rewards the accumulation of wealth by the rich while punishing middle-class wage earners, and the effect of that system has been the strangulation of prosperity and opportunity for everybody but the ultra-wealthy. There are a lot of problems to fix to restore fairness and common sense to our tax code, and closing the carried interest loophole is a great place to start.”
Repealing Corporate Transparency Act
The House Financial Services Committee is also planning to markup a bill next Tuesday that would fully repeal the Corporate Transparency Act, which has already been significantly
If enacted, the repeal would eliminate beneficial ownership reporting requirements, removing a transparency measure designed to help law enforcement and national security officials identify who is behind U.S. companies.
“This repeal would turn the United States back into one of the easiest places in the world to set up anonymous shell companies, something Congress worked for years to fix,” said Erica Hanichak, deputy director of the FACT Coalition, in a statement. “These entities are routinely used to facilitate corruption, financial crime, and abuse. Rolling back the CTA doesn’t just weaken transparency, it signals to bad actors around the world that the U.S. is once again open for illicit business.”
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