This episode focuses on common compliance problems under Regulation E, which governs electronic fund transfers and is designed to protect consumers using electronic channels such as ATMs, debit cards, online banking, and phone-initiated transfers. As electronic usage and fraud increase, regulators are finding frequent violations—especially around how financial institutions handle error resolution and consumer liability. A key issue is the improper application of liability limits when consumers report unauthorized transactions, particularly misunderstanding the 60-day rule tied to periodic statements, which can expose consumers to unlimited liability for later transactions if they delay reporting. Another major concern is failures in the provisional credit process—institutions often delay investigations beyond allowed timeframes without issuing timely provisional credit (including interest), despite clear requirements to begin investigations promptly and credit the consumer if more time is needed. The takeaway is that financial institutions must have clear, accurate procedures and well-trained staff to ensure timely investigations, proper liability determinations, and full compliance with Regulation E’s consumer protections.

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This podcast highlights sweeping changes proposed for Section 1071 Rule that would dramatically shrink the volume of reportable small business lending and the number of institutions required to report in comparison to the lenders reporting under the CRA Rule. The most significant shift is redefining a “small business” from $5 million to $1 million in gross annual revenue, a change that would eliminate nearly half of currently reported (compared to CRA reporters) small business loans, which is magnified even further when combined with the proposal to exclude renewals (unless the loan amount increases).

The Section 1071 Rule's reporting threshold for "covered" lenders would jump from 100 to 1,000 small business originations in each of the prior two calendar years. Under the current CRA Rule about 700 lenders are required to report. In comparison, under the proposed Section 1071 Rule only about 80 of those lenders have enough loan volume to be required to report under that Rule. In fact, among those potential Section 1071 lenders, the top10 would generate more than 91% of the reported small business lending activity under Section 1071. The Section 1071 proposal would also drop agricultural loans from being reported and eliminate dozens of discretionary data points, greatly reducing transparency and regulatory insight. With such far-reaching implications, the presenters urge stakeholders to actively comment before the December 15, 2025 deadline rather than remain passive. Brought to you by GeoDataVision and M&M Consulting

This podcast explains how statistical significance is used in redlining allegations based on disparate impact, despite potential deemphasis under the Trump Administration, as regulators may shift accusations from disparate impact to disparate treatment while still relying on statistical analysis. The hosts clarify that statistical significance measures the probability that a bank's below-average performance in majority-minority census tracts occurred by chance rather than discriminatory practices, using a 5% significance threshold, and that larger banks with more loan volume must perform closer to market averages to avoid being flagged (ranging from 5% for 100 applications to 9.5% for 10,000 applications when the market average is 10%). However, the analysis emphasizes that statistically significant results can be misleading due to "lurking" or "confounding" variables, particularly when regulators use unrealistic market definitions (UREMAs) that include areas where banks lack branches or competitive presence, or when peer comparisons inappropriately mix different institution types like banks and mortgage companies—situations that have resulted in the majority of actual peer banks failing the statistical test, demonstrating the data was fundamentally skewed and making the statistical significance analysis unreliable.

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