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Here’s what you need to know as your business or nonprofit entity prepares to transition to CECL

The Financial Accounting Standards Board (FASB) issued Accounting Standard Codification 326, commonly referred to as the current expected credit loss (CECL) model, in 2016. CECL initially took effect in December 2019 for large, public U.S. Securities and Exchange Commission (SEC) filer institutions. It became effective for smaller reporting companies and nonpublic companies for fiscal years beginning after December 15, 2022, including interim periods within those fiscal years. 

While the standard transformed how banks, credit unions and other lenders, account for credit losses, it also impacted all other business entities holding receivable balances from customers and other assets by requiring them to consider not only historical and current conditions but also adjust for reasonable and supportable forecasts. This change impacts how most entities estimate reserves for various types of assets, including accounts receivable, contract assets, debt securities, and even cash and cash equivalents. Implementing CECL presents businesses and nonprofit entities with both challenges and opportunities to improve credit risk management practices.    

What is CECL?  

The old model was described as an incurred loss model, under which institutions recognized credit losses only after they occurred based on specific events, such as bankruptcy. CECL provides a way for lenders to estimate and set aside money for potential future credit losses over the entire contractual lifetime of a loan. Under CECL, entitles are required to establish allowances for lifetime expected losses upon origination.  

CECL applies to any entity issuing credit under United States Generally Accepted Accounting Principles (GAAP) accounting standards. This includes banks, savings institutions, credit unions, holding companies, forprofit businesses and nonprofit entities. 

Understanding the impact on loss reserves and practices  

Early CECL adopters reported higher upfront loss reserve requirements. In many cases, the lifetime loss allowance calculation significantly impacted balance sheets. However, the standard also acknowledges that entities should consider undue cost and effort when determining the most meaningful analysis and application of ASC 326, allowing some flexibility in the implementation process. 

Beyond allowance impacts, CECL prompted wider operational changes. It has altered how allowances and core finance-risk processes have been managed. Modeling future credit losses requires much deeper, more granular analysis than incurred-loss methods. 

Under ASC 326, assets with similar risk characteristics are pooled together. Factors like debt type, aging buckets, geography, borrower’s business cycle and repayment structure are considered when forming risk pools. Risk pools may not require further disaggregation if a similar credit loss allowance is calculated compared to the scenario of full disaggregation.   

Siloed activities like finance and credit risk management must now integrate and collaborate cohesively to meet these new standards 

These sweeping changes also necessitated other improvements in risk data management, demanding more advanced analytic platforms capable of accurately forecasting credit losses. As a result, businesses must now enhance their data analytics capabilities. It’s necessary to analyze large volumes of diverse data such as historical write-offs, loan performance data over various periods and the separation of balances by risk pools. Additionally, maintaining supportable documentation, such as collateral, is crucial where needed to help ensure the accuracy and reliability of these forecasts. 

As businesses work to meet these requirements, there’s an increasing need for AI-driven tools that can assist with data analysis. These tools are becoming more reliable and can help manage and interpret vast datasets, identify patterns and forecast risks, making them invaluable for CECL compliance. AI is particularly useful in automating mundane tasks, improving risk identification and ensuring compliance by offering insights that traditional methods might lack.  

4 Key challenges of CECL implementation   

For many financial institutions, adopting CECL represented a heavy lift. As other businesses and nonprofit entities look to implement CECL, they many encounter similar challenges, such as:  

1. Methodology shifts  

Revamping processes and overhauling decades-old practices may pose challenges in where there were previously not strong internal controls surrounding credit monitoring and oversight for credit risk management. Transitioning from the incurred model to expectedloss accounting calls for a change in methodology.  

2. Data demands  

Calculating lifetime expected losses may require substantially more data than previous methods, particularly for assets that will be held or realized over longer periods of time. Organizations now need data such as risk drivers and macroeconomic scenarios, which may not have historically been captured in their models or tracked. They may also struggle to consolidate and refine data spread across systems.  

3. Lifetime loss modeling  

CECL relies on strong quantitative models to accurately predict lifetime losses in different scenarios. Developing, testing and deploying these complex credit models can be challenging. 

4. Disclosure and governance  

CECL requires solid data and clear reasons for loss estimates and adjustments. This transparency demands rigorous model governance and documentation. As a result, it may initially be a struggle to establish clear auditable trails.  

Financial institutions and other businesses had to work hard to overcome these challenges. Gaps in talent, technology and preparation led to delays for some entities. However, learning from global International Financial Reporting Standard (IFRS) 9 precedents helped smooth domestic implementations.  

IFRS 9 lessons for CECL    

The rest of the world transitioned to expected credit loss standards earlier under IFRS 9. U.S. businesses and nonprofit entities can learn from their international counterparts’ experiences with CECL implementation:  

Planning makes perfect  

Effective project planning and integrated program management may help streamline CECL adoption. Many IFRS 9 institutions underestimated how much work was required upfront. This caused delays which had to be resolved via costly staffing increases.    

Data-driven decisions  

Gathering data and strengthening governance early is crucial. IFRS 9 data issues like fragmented sources, missing values and opaque lineage hampered some firms. Transparent and auditable data resulted in better modeling decisions.  

Pragmatic over perfect 

Deploying sophisticated loss models initially proved overly ambitious for some IFRS 9 firms. A phased, iterative approach using simpler methods achieved compliance and allowed for improvements over time.     

Governance is paramount  

Proper controls over the credit loss process are essential. Some IFRS 9 institutions focused on modeling first and sometimes had to implement proper data and assumption governance retroactively. Robust, end-to-end governance enables efficiency, justification and auditability.  

Recommendations and best practices  

Building on global IFRS 9 precedents, the following practices contribute to a smooth CECL transition:          

  • Integrated architecture: Solutions with open, adaptable designs accommodate evolving standards interpretations best. Centralized model inventory, enterprise data platforms, automated workflows and transparent reporting reduce friction.
  • Phased, iterative rollout: Start by establishing basic processes using simple methodologies. This is not the time for perfectionism; simpler early methods can be improved gradually as standards become clearer.     
  • Computational efficiency: CECL’s lifetime loss calculations take more computational power than prior methods. Reviewing and optimizing model execution environments maximizes performance and cost-effectiveness. 
  • Risk data management: Sound data governance, lineage tracking and using multiple internal-external sources are crucial. Systematic data risk assessments help focus efforts effectively
  • Comprehensive governance: Collaborative, auditable processes spanning data, models, assumptions and outputs enhance transparency and control. Version management, sandbox analytics and role-based reviews strengthen reliability. 

These practices may seem daunting; however, leveraging them enables more dynamic risk management over the long term. CECL presents an opportunity to modernize methods comprehensively.     

How firms like BPM promote CECL compliance   

Navigating CECL alone can be challenging. Partnering with a specialized firm like BPM makes implementation easier with tailored guidance including: 

  • Systematic consulting on all program aspects, including optimal workstreams, resource allocation, data strategies and technology enablement roadmaps. [Learn about BPM’s Risk Assurance and Advisory Services here.]  
  • Constructing robust CECL-compliant accounting models that prioritize compliance, practicalities and enable iterative refinements of current accounting methodologies.
  • Integrating model, data and reporting for easy setup, customization and deployment of tailored CECL platforms.          
  • Establishing processes for data lineage, assumptions management, risk-based analytics and audit trails.       
  • Providing production and regulatory support, periodic model validation and continuous improvement services 

BPM can help with CECL  

CECL represents a shift in the accounting for credit risk for any businesses extending credit. While challenging, it provides opportunities for your organization to transform credit risk management. With methodical planning, data enhancements, modeling and sound governance, it’s possible to attain CECL compliance.   

BPM specializes in guiding businesses and nonprofit entities through this transition. Our team offers personalized Technical Accounting Solutions that go beyond compliance, helping you optimize your practices and leverage the latest technologies, including AI tools, toward your long-term success. To learn how we can partner with you to navigate CECL smoothly and effectively, contact us today. 

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Will Tanem

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