be appropriate to the nature , size , complexity , and scope of each furnisher ’ s activities . Furnishers must consider and incorporate , as appropriate , the guidelines of Appendix E to Regulation V when developing their policies and procedures . These guidelines address key business functions , such as record retention , training , third-party oversight , and receipt of feedback from CRCs and others contributing to a furnisher ’ s ability to ensure the accuracy and integrity of the data furnished to CRCs . Examiners identified the following violations of the Regulation V requirement for reasonable written policies and procedures :
• Furnishers ’ policies and procedures had failed to specify how particular data fields , such as the date of first delinquency , should be populated when furnishing information about credit card accounts .
• Credit card furnishers ’ policies and procedures failed to provide for the retention of records for a reasonable period of time to substantiate the accuracy of consumer information furnished to CRCs .
• Furnishers had failed to perform account level analyses to determine which accounts should be reported in bankruptcy status after a consumer informs the furnisher of a bankruptcy filing .
• Auto loan furnishers had failed to incorporate content relating to the specific activities in which the furnishers engaged . For example , furnishers lacked
procedures for furnishing accurate information in connection with leased automobiles returned to dealerships .
• Deposit furnishers had no written policies or procedures for furnishing deposit account information to specialty CRCs .
• Furnishers , in developing their policies and procedures , did not consider and incorporate the guidelines in Appendix E to Regulation V with respect to conducting reasonable investigations of consumer disputes relating to furnished deposit account information .
Financial institutions will now also be tasked with providing ample documentation of any machine learning processes they employ , including things like algorithms , demographic information inputted , demographic research , areas of service , customer information , and any research or analysis related to marketing or advertising . Although machine learning is still new , financial institutions will be responsible for accurate , honest and timely reporting of their programs to encourage transparency and allow any potential discriminatory processes to come to light for evaluation .
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