Diving Deeper

Consumer Loan Defaults: Should Banks Continue to Hold Elevated Reserves?

Allowing for loan losses during COVID: Banks prepared for delinquencies during COVID uncertainty, but the expected wave of losses has not come. Will it?

Allowing for loan losses during COVID: Banks prepared for delinquencies during COVID uncertainty, but the expected wave of losses has not come. Will it? As states locked down, retail businesses were shuttered, and office workers who still had jobs learned to work from their kitchen tables via Zoom, credit analysts in the banking sector rushed to project the swell of consumer defaults on the horizon that would be driven by the COVID-19 pandemic. The reality is that, nine months later, chargeoff rates are stable and delinquency rates are down more than 15%. If the anticipated defaults never materialize, the result would...

Building an Efficient and Compliant CCAR Modeling System

Robust coding practices and streamlining the process and reduces delays and errors in model development and implementation for critical CCAR stress testing execution.

  Case Study: Robust coding practices and streamlining the process reduced delays and errors in model development and implementation for critical CCAR stress testing execution.   Complex and unreliable code, manual processes, and extensive back-and-forth with development teams made it difficult for a Top 20 bank to implement models required for the Comprehensive Capital Analysis and Review (CCAR), a federal stress-testing exercise. The existing environment resulted in delays, data issues and model revisions that put the bank at risk for non-compliance in submitting on time. Facing multiple pain points with that process, the bank tapped into our expertise and experience...

Productionizing Allowance: An Engineering Approach to an Analytical Process

Bringing production quality methods and controls to the quarterly impairment allowance created a fully compliant allowance process that reduced cycle time and resource needs by 80%.

Case Study: Bringing production quality methods and controls to the quarterly impairment allowance created a fully compliant allowance process that reduced cycle time and resource needs by 80%. Several analyst teams at a Top 10 bank spent four weeks each quarter estimating the company's consumer loan impairment allowance, which represents capital to be set aside for expected losses on the bank's $100 billion loan portfolio. Manual, spreadsheet-based processes were labor-intensive and error prone, leading to delays and reduced confidence in the results. With these issues contributing to audit findings and potentially tens of millions of dollars in excess allowance, the...

Automation of Monitoring in Field Operations and Calculating Incentives

Automation delivers higher accuracy and speed in $60 million in annual incentive payouts to telecommunication field technicians.

Case Study: Automation delivers higher accuracy and speed in $60 million in annual incentive payouts to telecommunication field technicians. Cumbersome manual processes caused errors and delays in distributing $5 million in monthly incentives at a major telecommunications firm, leaving operations field managers and technicians disappointed in an exchange that was intended to drive engagement and morale. Every month, four teams worked with multiple disparate spreadsheet tools to pull data and calculate incentives, an unwieldy and risky approach that took more than 45 days to process payments. Recognizing the need to streamline and improve this critical function, the firm turned to...

Implementing CECL Part 2: Turning CECL Compliance into a Competitive Advantage

This post is the second in a two-part series on CECL. Part 1 explains the rationale for CECL and its implications on financial allowance practices.

NOTE: This post is the second in a two-part series on CECL. Click here for Part 1, which explains the rationale for CECL and its implications on financial allowance practices. As financial institutions prepare for the 2020 and 2023 implementation of CECL guidance regulations, most institutions have the same hurdles to overcome. We view these hurdles as strategic opportunities for the institutions that put the time and energy into understanding and developing the best solutions. Institutions are required to develop forward-looking approaches based on the materiality of their portfolios. While they might be able to rely on simple approaches for...

Implementing CECL Part I: Impacts for Institutions Big and Small

Implementing CECL: How changes to modeling and accounting processes bring change to financial services.

Implementing CECL: How changes to modeling and accounting processes bring change to financial services. The new Current Expected Credit Loss (CECL) standard could have substantial and far-reaching impacts to the bottom line for many banks, but, outside of the accounting community, many financial services leaders don’t fully understand its implications. Financial institutions that approach this new challenge as a business opportunity will find that CECL mitigates existing loan accounting headaches, giving them better insight into their portfolio. Done the right way, the strategic implementation of CECL has the potential to become not only a compliance success, but a competitive advantage....

Don’t Blame Polls: Know the Data Science to Analyze Results

Understanding polling and election modeling: How the behind data science and models that were seemingly off-target in 2016 are different in 2020.

Understanding polling and election modeling: How the behind data science and models that were seemingly off-target in 2016 are different in 2020. With less than a week until Election Day, key polls are pointing in the Democrats’ direction. Former Vice President Joe Biden leads in nearly every key battleground state, and pollsters and pundits say his victory is likely. For many Democrats, however, it feels like repeat territory, a PTSD of sorts from 2016, recalling pundits describing the race as “Hillary’s to lose” and assigning high chances to her victory. But by late Election Night, Donald Trump had claimed the...

Responsible Machine Learning: Three Rules of Thumb for World-Class Monitoring

Highly regulated industries can better leverage machine learning tools (and create trust in their findings) by developing monitoring systems that are holistic, insightful and actionable.

Summary Solution: Highly regulated industries can better leverage machine learning tools (and create trust in their findings) by developing monitoring systems that are holistic, insightful and actionable. Over the past decade, we’ve seen an explosion in the field of machine learning. Tech giants, online retailers, and social media platforms all have adopted machine learning strategies to evaluate data in ways that human beings and traditional modeling frameworks cannot. These new machine learning models provide a better fit for non-linear relationships, uncover unique insights and are better equipped to pick up on the nuances of a shifting environment. It’s no surprise,...

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The Process Behind Process Automation

From EUCs to structured, automated data, we walk you through the process, best practices and change management to ensure you’re leveraging analysts’ skillsets to the fullest.

Since its introduction in September 1987, Excel has been the go-to resource in an analyst’s toolkit due to its versatility and capacity to quickly translate complex formulas into illustrative tables and charts. Over the ensuing years, a typical financial services analyst would build elaborate, interwoven spreadsheets, simple models, assumptions and calculations, all in Excel, creating end-user computing (EUC) applications. And while these EUCs built the foundation for modern automation, generally speaking, they lacked traceability or documentation, making model adjustments challenging and presenting serious challenges for governance, risk and regulatory compliance functions.