ARCSys Technologies

ARCSys provides this quarterly webinar to support the quarterly review of economic and employment forecasts to be utilized in CECL models. We will discuss the economic environment and specific forecasts of economic and employment indicators. The webinar will also provide numerous public economic forecasts from various organizations to help you determine the correct directions of your forecast for variables you are utilizing in your CECL model.

$50

1. Define key indicators that impact economic forecasts and CECL modeling
2. Evaluate changes in economic indicator data over time
3. Determine the general direction of public forecasts by applying economic indicator data

For years, financial institutions have struggled with the "double counting" effect under CECL, where acquiring non-PCD (Purchased Credit Deteriorated) loans required an immediate "Day 1" provision expense -- even though credit risk was already priced into the fair value of the loan. In November 2025, FASB issued ASU 2025-08 finally addressing this issue by expanding the "gross-up" approach to a new category of assets: Purchased Seasoned Loans (PSLs). This webinar provides a comprehensive deep dive into the new standard. We will move beyond the theory to discuss practical implementation strategies. We will explore how to identify "season" loans, the mechanics of the gross-up approach (formerly reserved for PCD assets), and the strategic impact this will have on M&A and loan portfolio acquisitions.

Free for No CPE, $25 for CPE

1. Differentiate legacy Non-PCD from new Purchased Financial Asset (PFA) accounting to eliminate the "Day 1 double count" of credit losses.
2. Review seasoning criteria (90-day rule, lack of acquirer involvement) to correctly classify acquired loans as eligible PSLs or new originations.
3. Identify the "gross-up" method to calculate initial amortized cost and record Day 1 journal entries for seasoned loans.
4. Assess operational and strategic implications of early (2026) vs. mandatory (2027) adoption, including data and policy updates.
5. Quantify the new standard's financial statement impact on post-acquisition earnings, capital, and yield via case studies.
6. Evaluate the optional accounting policy election for subsequent measurement to determine if aggregating purchased and originated loans outweighs a one-time provision true-up.

Model validation frequently exposes significant deficiencies in an institution's Current Expected Credit Loss (CECL) framework. All too often, these critical findings stem from a single root cause: the "Black Box" problem, where management cannot access or explain the granular details of their model's inner workings. This one-hour session targets the four most impactful areas where examiners raise red flags: Data Integrity, Qualitative Adjustments (Q-Factors), Methodology, and Governance. We will move beyond the theoretical requirements to provide actionable, best-practice solutions for resolving these challenges. Attendees will discover how to transition from opaque spreadsheets to a defensible, audit-ready posture. We will also demonstrate how a robust, integrated technology solution—such as the ARCSys platform—can automate these best practices, providing the necessary audit trail, data granularity, and analytical rigor required to satisfy regulatory scrutiny and drive confidence in your ACL.

Free for No CPE, $25 for CPE

1. Diagnose the root causes of the most frequent CECL validation findings, specifically focusing on the risks associated with data opacity and unsupported Qualitative Adjustments (Q-Factors).
2. Construct an audit-ready defense for data integrity by implementing best practices for reconciliation and lineage documentation that directly resolve data findings
3. Substantiate forward-looking forecasts and Q-Factor adjustments with reasonable and supportable evidence to ensure the model’s conceptual soundness is visible to examiners.
4. Justify critical methodological assumptions—such as Probability of Default (PD) and Loss Given Default (LGD)—using documentation techniques that mitigate findings related to model mechanics.

This webinar provides a comprehensive review of Automated Valuation Model (AVM) frameworks designed to analyze the relationship between Appraisal Amounts, Loan-to-Value (LTV) ratios, and market indices such as the national or state Freddie Mac HPI. We will explore how to apply various statistical models to both Residential and Commercial Real Estate portfolios to forecast average housing prices over a 2-year horizon. The session will review the methodology of two distinct statistical approaches: the Ordinary Least Squares (OLS) Linear Regression model and the Explainable Boosting Machine (EBM). Attendees will learn how to train these models on historical loan-level data to predict future valuations under varying economic stress scenarios. Finally, we will review comparative statistical evidence—such as R-squared and RMSE—to identify the optimal model for minimizing prediction error and maximizing transparency across different asset classes.

Free for No CPE, $25 for CPE

1. Compare Linear Regression (OLS) and Explainable Boosting Machines (EBM) predictive power, noting EBM's "Glassbox" process for finding complex relationships between economic indices and appraisal values.
2. Analyze 2-year appraisal and LTV ratio projections, distinguishing the results from the statistical models under simulated economic downturns.
3. Review evaluation metrics such as R-squared and RMSE to evaluate model performance and variance captured across diverse real estate markets.
4. Stress test portfolios by analyzing LTV and appraisal sensitivity to simulated index changes of 10%, 20%, 30%, and 40%.
5. Validate model selection using geographic analyses with National and State-level indices to forecast values across regions.

ARCSys provides this quarterly webinar to support the quarterly review of economic and employment forecasts to be utilized in CECL models. We will discuss the economic environment and specific forecasts of economic and employment indicators. The webinar will also provide numerous public economic forecasts from various organizations to help you determine the correct directions of your forecast for variables you are utilizing in your CECL model.

Free for No CPE, $25 for CPE

1. Define key indicators that impact economic forecasts and CECL modeling
2. Evaluate changes in economic indicator data over time
3. Determine the general direction of public forecasts by applying economic indicator data

Are prepayments a mystery affecting your CECL and ALM practices? This CPE-accredited webinar unlocks the secrets to optimized risk management by empowering you to demystify prepayment behavior through an analysis of key drivers like interest rates, economic conditions, and borrower demographics. Attendees will explore historical trends to forecast future scenarios with confidence while grasping the crucial role prepayments play in CECL’s expected loss calculations and reserve assumptions. Beyond compliance, you will learn to leverage these insights for ALM by integrating prepayment data to optimize capital allocation, liquidity management, and strategic risk planning. Don't miss this opportunity to ensure your practices are prepayment-resilient and gain a competitive edge—register today to solve the prepayment puzzle

Free for No CPE, $25 for CPE

1. Analyze the key drivers of prepayment behavior, including interest rates, economic conditions, and borrower demographics, to better understand their influence on portfolio performance.
2. Forecast future prepayment scenarios by evaluating different prepayment types and historical trends to enhance predictive confidence.
3. Assess the critical impact of prepayment assumptions on CECL expected loss calculations and reserve volatility.
4. Implement mitigation strategies to reduce the impact of prepayment volatility on credit loss models.
5. Integrate granular prepayment data into Asset Liability Management (ALM) models to optimize capital allocation and liquidity planning.
6. Develop proactive risk management strategies that leverage prepayment insights to identify both risks and opportunities within the balance sheet.

ARCSys provides this quarterly webinar to support the quarterly review of economic and employment forecasts to be utilized in CECL models. We will discuss the economic environment and specific forecasts of economic and employment indicators. The webinar will also provide numerous public economic forecasts from various organizations to help you determine the correct directions of your forecast for variables you are utilizing in your CECL model.

Free for No CPE, $25 for CPE

1. Define key indicators that impact economic forecasts and CECL modeling
2. Evaluate changes in economic indicator data over time
3. Determine the general direction of public forecasts by applying economic indicator data