Category: Statistical Analysis

Premier Insights - Statistical Analysis

Cutting Through the Murkiness: Fundamentals of the Comparative Review for Fair Lending

Fair lending concerns are one of the dominant risks lenders face in regard to their business operations. Although larger lenders typically have significant resources in place to mitigate these risks, and there has been an emphasis in the last decade on quantitative methods for fair lending evaluation, there remains a great deal of subjectivity in […]

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Making Sense of COVID-19 Numbers: 5 Keys to Data Interpretation

Making Sense of COVID-19 Numbers: 5 Keys to Data Interpretation

We have discussed in previous posts reliance on data and how technology and the instant access to information has been transformative in society.  Technology and quick access to data continues to expand as does reliance on it.  With such a deluge of various sources, both in terms of raw numbers and “processed” or interpreted information, […]

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Challenges in Fair Lending Analysis, or Why You Don’t Have to Avoid Swimming Pools When Nicolas Cage is Working

The term “Information Age” probably pre-dates many who are reading this post, possibly originating as early as the 1970’s with the proliferation of computer technology.  From the mainframe era, to PC’s, laptops, personal devices and smart phones, technology continues to shape our world at a seemingly ever increasing rate.  This is all augmented by the […]

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CECL, Loan Losses, and the Pandemic

The Current Expected Credit Losses standards (CECL) have once again been delayed for an undetermined period of time due to the Coronavirus Pandemic. Despite CECL implementation being pushed down the road again, forecasting credit losses is again front and center. This stems from the uncertainty created by the Pandemic and the nation’s corresponding response. The […]

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Maintaining Proper Perspective of Statistical Methods for Fair Lending Evaluation

We have discussed previously in various posts some of the challenges of using regression and other statistical methods for fair lending reviews as well as the current emphasis on quantitative methods.   Over the last 10 years, the regulatory and enforcement agencies as well as institutions have been gravitating more and more towards statistical methods when […]

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Unraveling the (Seeming) Complexity of CECL

The new CECL standard is presumably designed to enhance the stability of the financial sector by providing more accurate assessments of loan losses.  It also requires a change from the current estimates of loan losses that are produced by most institutions today to projections or forecasts.

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Exploring Statistical Correlation: Causation and Non-Linearity

What does it mean that two variables are correlated? In this video, we explore the meaning of correlation and remind you that, as the old adage says, correlation does not equal causation. Two variables may appear to be correlated when, in fact, they are unrelated, and the apparent correlation is the result of random chance. [...] Read More

Are My Fair Lending Statistical Regression Results Meaningful?

Your fair-lending regression results indicate a statistically significant disparity… now what? In our last blog post, we discussed the importance of a common-sense approach to statistical analysis. One common error in statistical analysis is to assume that a result is practically meaningful just because a result is statistically different from zero. This in not always […]

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Understanding Statistical Significance

As fair lending analysis becomes increasingly technical, industry practitioners have had to familiarize themselves with the terminology of statistical analysis. Statistical significance is one of the most common and foundational concepts to successfully navigating these new waters. Moreover, it is a concept that, when misunderstood, may result in serious error.

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Understanding What is Not in the Data: A CECL Illustration

In our last post, we discussed the importance of understanding both what is and what is not included in the data for regression analysis. In this post, we further emphasize this point with an illustration relevant to a common CECL methodology – the probability of default/loss given default method (PD/LGD).

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