The Office of the Comptroller of the Currency assessed a $25 million civil monetary penalty against Citibank for violations of the Fair Housing Act. The OCC determined that the bank lacked proper control over the Relationship Loan Pricing program-- designed to provide eligible mortgage loan customers either a credit to closing costs or an interest rate reduction. As a result of these control weaknesses, some bank borrowers did not receive the Relationship Loan Pricing benefit for which they were eligible and were adversely affected on the basis of their race, color, national origin, or sex, violating the Fair Housing Act, according to the Consent Order from the OCC. The bank has initiated and largely completed a plan to reimburse all customers who did not receive the appropriate RLP benefit, including those customers affected by these violations, and is taking other appropriate corrective action to prevent future violations. The bank will reimburse 24,000 customers a $1,000 each in addition to the civil monetary penalty. [adbutler zone_id="326324"] [adbutler zone_id="326327"]

According to the Consent Order, in August 2011, the bank piloted a Relationship Loan Pricing program and in February 2012, implemented it across its customer base. Under the program, qualified customers could receive a credit for closing costs or an interest-rate reduction.

Citibank failed to ensure effective risk management and internal controls, including inadequate periodic reviews, over the Relationship Loan Pricing program, including:

• From August 2011 to April 2015, Citibank failed to provide adequate training to loan officers regarding how to offer Relationship Loan Pricing to customers.
• In addition, between August 2011 to November 2014, written guidelines did not explicitly instruct loan officers to offer Relationship Loan Pricing to all eligible customers and the bank didn’t require loan officers to document the basis for the customer’s rejection.
• Also, between August 2011 to January 2015, Citibank didn’t require loan officers to inform customers of all discount programs for which they might qualify.
• As a result of ineffective risk management and control weaknesses, some bank borrowers didn’t receive the Relationship Loan Pricing benefit for which they were eligible and were adversely affected on the basis of their race, color, national origin or sex. After determining in 2014 that some customers hadn’t received the correct Loan Pricing benefit, Citibank self-reported its findings to the OCC in 2015.

 

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KS StateBank has licensed the Total Expert Marketing Operating System to centralize marketing efforts and streamline the customer experience.

It provides the capability for originators to track interactions with customers, prospects and partners. KS StateBank has branches in Kansas and Arizona.

[caption id="attachment_11110" align="alignright" width="329"] Valencia: APIs and integrations allowed the bank to personalize customer engagement and marketing.[/caption]

“We needed a more robust solution to equip our teams with cohesive, on-demand marketing materials that met strict compliance requirements and allowed them to expand their co-marketing business,” said Jan Valencia, residential-mortgage systems project manager at KS StateBank. “It was critical to find a solution to automate the delivery of hyper-relevant messaging throughout the customer lifecycle. The open application-programming interface and integrations allowed us to maintain our current technology stack and empowered the flow of data, so we can personalize our customer engagement and marketing efforts.”

 

 

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The technology will empower the KS StateBank relationship managers to foster deeper relationships with their customers, prospects and co-marketing partners through the deployment of personalized, automated messaging, at scale. By leveraging consumer data paired with intelligent automation, they will be able to deliver the right message to the right person at the right time.

“We’ve seen a huge push in the financial services industry to personalize the customer experience and maximize the lifetime value of existing customers,” said Sue Woodard, chief customer officer at Total Expert. “We are thrilled to empower KS StateBank relationship managers to be the trusted advisor their customers turn to time and time again, cultivating customers for life.”

 

 

 

 

 

 

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ZestFinance, a developer of artificial intelligence software for consumer credit, launched ZAML Fair, a new  tool designed to reduce bias and discrimination in lending.

Several mortgage lenders have already tested the ZAML Fair algorithm, and based on those results, ZAML Fair would eliminate 70 percent of the gap in mortgage approval rates between Hispanic and white borrowers, according to the company. Also, ZAML would cut the even larger gap between black and white borrowers by more than 40 percent. And that is just by using the technology to tune up traditional credit models. This would put more than 172,000 minority families into new homes.

"The way lenders take bias out of their models today is by simply tossing out offending credit signals. That leaves a lot of performance on the table," said Douglas Merrill, founder and CEO of ZestFinance. "Banks

[caption id="attachment_11100" align="alignleft" width="299"] Douglas Merrill, CEO of ZestFinance[/caption]

shouldn't have to choose between fairness and accuracy, and ZAML Fair helps them optimize for both."

ZAML Fair is a new algorithm that lenders can use to tune models for maximum fairness by automatically reducing the impact of discriminatory credit data. ZAML Fair uses the transparency tools built into ZAML to rank credit signals by how much they lead to biased outcomes and then produces a new model with maximum fairness and accuracy.

ZAML Fair carefully reduces the influence of factors that drive disparity, including some common credit signals such as income and the traditional credit score. Lenders get a series of better models they can choose from at a fraction of the time and effort required by legacy techniques. ZestFinance was founded in 2009 by Merrill, a former CIO of Google, and a team of former Google employees.

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