Insights into Effectiveness through Data Science

A Quick Overview of Modern AI for Lenders

Our latest white paper offers a snapshot at the current state of AI usage in lending, with a specific focus on regulatory alignment. Authors Aaron McGuire and Syed Raza PhD. aim to address key questions and topics including nuances in Large Language Models (LLMs), the intersection of automated decisioning and AI, and the potential risks of AI in transactions servicing. 

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New Credit Card Late Fee Regulation – Strategy and Unit Economics Impact

In the latest of a series of moves to reduce ”junk fees” from banking products, the CFPB has announced new regulation to reduce credit card late fees to a maximum of $8, without higher late fee safe harbor amounts for subsequent violations. While this regulation will only apply to card issuers with greater than 1 million credit cards at this time, this regulation will lead to large reductions in approval rates, especially for subprime borrowers, and reduce the profitability of existing card portfolios. In this white paper, we analyzed the proposed regulation by looking at (1) Historical precedent and the current landscape of late fees in the U.S., (2) a case study simulating the impact of proposals on a subprime credit card portfolio, and (3) a walk through of the impacts this regulation will have on the back book.

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Student Loan Deferrals

In our latest white paper we examine the resumption of Student Loan repayments, explore insights from Equifax Ignite data on performance expectations, and discuss how lenders can best prepare. 

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Credit Risk Quarterly – Q3 2023

Check out our latest Credit Risk insights from Q3 2023! This quarter we discuss headwinds and tailwinds affecting the US consumer credit risk industry across all different asset classes, including our thoughts on rising delinquencies with increased interest rate environments, and our expectations with the resumption of student loan payments.

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Credit Risk Quarterly- Q2 2023

Check out our latest Credit Risk insights from Q2 2023. This quarter we focus on the headwinds and tailwinds affecting the US consumer credit risk as a whole, as well as discuss recent trends across Credit Cards, Personal Loans/Mortgages, Auto Loans, and Student Loans.

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Recoveries Strategy Refresh

During the pandemic, consumer stimulus led to lower credit losses and therefore less of a strategic focus on Recoveries. As the U.S. enters a more challenging macro-economic environment characterized by inflation, interest rate increases, and resulting pressure on consumers, we are seeing losses increase back to pre-pandemic levels and even worse for some segments. Now is a perfect time to revisit Recoveries and refresh your strategic and operational approach. This paper will explore how the industry has evolved since the last economic downturn, provide an updated view of winning strategies, and highlight what is at stake for your organization.

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The Small Business Data Revolution: Reshaping Lending Decisions

Over the past decade, the Small Business (SMB) lending field has seen an explosion of innovation, with groundbreaking advancements in data sources, API technology, machine learning, digital onboarding, and instant decisioning. Initially driven by larger banks, these innovations have now been embraced and implemented at scale by fintech companies. In this article, we want to take you on a journey of how the SMB lending category has transformed over time, explore the emerging ecosystem of new technologies and data sources, and discuss how executives at banks, lending institutions, and payments companies can rapidly improve upon their current SMB offerings.

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Credit Risk Quarterly- Q1 2023 in Review

Check out our latest Credit Risk insights from Q1 2023, focusing on trends across various asset classes, noticeable decreases in risk levels among subprime and low-income consumers, and continued risk score warping.

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Building a Well-Managed Collections Function

As delinquencies and Collections efforts increase across the industry, our latest white paper provides a roadmap for where the difficulties and pain points lie. We start with a framework for the root causes of complexity within Collections, provide a variety of examples, and suggest a set of important first steps to make Collections a more well- managed part of the lending lifecycle.

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A Comparison of Modeling Preprocessing Techniques

Our latest white paper compares the performance of various data processing methods in terms of predictive performance for structured data. This paper also seeks to identify and recommend preprocessing methodologies for tree-based binary classification models, with a focus on eXtreme Gradient Boost-ing (XGBoost) models.

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