?? This Week in GRC: Jumbo Rate Cuts

Welcome to Issue 77 of This Week in GRC, MBK Search's weekly digest of the news and views in the world of governance, risk, and compliance.

?? This Week's Opening Bell

For the first time in four years, the Federal Reserve reduced interest rates, announcing a chunky cut of 50 basis points.

It's the sort of move usually rolled out during a crisis, but the American economy remains strong. Inflation is trending down. Markets are up.

Happy days, right?

“Probably the least appealing part of rate cuts for consumers is that high-yield savings accounts, CDs, and money-market funds won’t be as attractive anymore,” says Melissa Caro, founder of My Retirement Network in New York. “These have been a great way to keep your cash accessible while still earning a decent return over the last couple of years, but with rates dropping, the yields on these products will follow."

With increased lending activity comes increased credit risk, and with that greater regulatory scrutiny. And who said anything about things staying quiet until after November, hmm?

?? This Week's Issue

?? Rates go down, risk goes up

?? Tyson Foods gets pinged for greenwashing

?? How to remove bias when training your AI model

?? This Week's GRC Headlines

Danske Bank Settles French Probe into Estonia Money-Laundering

Danske Bank, the largest bank in Denmark, has agreed to pay €6.33 million (approximately $7 million) in a settlement with French authorities over its failure to prevent money laundering at its former branch in Estonia.

The settlement with France's national financial prosecutor marks the end of the last outstanding inquiry by any authority into the Danske Estonia branch's handling of nonresident accounts, according to Danske Bank Senior General Counsel Niels Heering.

In 2018, Danske disclosed that more than $230 billion had flowed from Russia and other former Soviet states through its Estonia branch, admitting that many transactions were likely illicit. This revelation led to years of scrutiny of the bank's compliance program and corporate governance.

Danske Bank had previously agreed to pay $2 billion in a settlement with U.S. and Danish authorities in 2022 over the Estonia branch issues, admitting to anti-money-laundering-related violations. However, France conducted its judicial investigation, which began in 2015.

French authorities found that Danske knew providing banking services in Estonia for nonresidents was a high-risk business but had a "passive and complacent attitude" toward its financial crime controls. The settlement with French authorities concludes their investigation into the bank.

Tyson Foods Faces Lawsuit Over Alleged Greenwashing

Tyson Foods, the meat company responsible for about 20% of the meat sold in the U.S., has been sued by the Environmental Working Group for alleged greenwashing.

The lawsuit, filed in Washington, D.C., challenges Tyson Foods' claims of reaching net-zero emissions by 2050 and its plans for "climate-smart" beef. It argues that these statements are misleading because the company lacks concrete plans to achieve these goals.

Earthjustice, the plaintiff's environmental law firm, contends that greenwashing claims target well-meaning consumers who want to make climate-friendly purchases and that false or misleading statements prevent them from making informed decisions.

Tyson Foods, which generates 36% of its sales from beef and 65% of its total emissions, is the second major meat company sued for greenwashing in the U.S. this year, following a similar lawsuit against JBS by the New York Attorney General.

While Tyson Foods has emissions reduction targets validated by the Science-Based Targets initiative for 2030, the nonprofit still needs to approve net-zero targets submitted by the company. The plaintiffs seek an injunction forcing Tyson Foods to either retract its climate messaging or publish an actionable plan to substantiate its claims.

Boeing Furloughs White-Collar Employees Amid Union Strike

Boeing is furloughing tens of thousands of white-collar employees to cut costs and avoid a credit-rating downgrade amid a strike by its largest union, the 33,000-member machinists union.

Chief Executive Kelly Ortberg announced in a memo that affected employees will be furloughed for one week out of every four for the walkout, which has halted production of the 737 and other jets.

According to analyst estimates, the strike began after the union rejected a labor deal offering 25% wage increases over four years, could cost Boeing $500 million a week. If the strike persists, credit-rating firms Moody’s and Fitch have warned of potential downgrades.

A union representing some 17,000 Boeing engineers, Speea, claims that its contract prohibits furloughs and requires payouts to idled workers during layoffs. Federal law also mandates 60 days’ notice for large-scale layoffs, with some exceptions.

Negotiations between Boeing and the machinists union restarted Tuesday with help from a federal mediator, but the union expressed frustration with the company’s unwillingness to address essential issues like wages and pensions. The strike highlights the ongoing tension between the company and its unionized workforce.

?? This Week's GRC Hot Takes

1) The FT offers an in-depth look at The Fed's decision to cut interest rates.

2) Matt Kelly at Radical Compliance has a fascinating deep-dive into Wells Fargo's enforcement issues.

3) Are we underestimating political risk in the energy market?

4) Is company culture worth factoring into an internal audit? Yes, but remember it's a proxy.

?? This Week's GRC Podcast

Here's a question for risk managers in financial services: What's your AI plan? And we don't mean, "Are you using AI?" but rather, "What's your plan for if it goes wrong?" Two little letters have dominated the conversation in the US banking sector, but are we having the right conversations? And how can we avoid finding out too late?

In the first episode of Talking Risks, brought to you by MBK Search, de Risk Partners, and Hadrius, host Michael Oliver, Managing Partner de Risk Partners and former Global Head of Compliance Testing for Financial Crimes and Automation Ravi de Silva, will speak with former Director of FinCEN and former CCO for the Financial Crimes Unit at Citibank Kenneth A. Blanco.

Subscribe to Talking Risks here

?? What MBK Search is Talking About

Understanding Bias in AI: A Financial Compliance Perspective

Artificial intelligence (AI) is transforming the financial services industry, but as with any powerful technology, it comes with significant risks. One of AI’s most critical challenges is the risk of bias—unintended discrimination that can affect everything from loan approvals to fraud detection. This bias damages customer trust and can lead to serious regulatory violations.

Here’s how financial institutions need to approach AI bias from a compliance perspective and what they can do to mitigate the risks.

What Is AI Bias, and Why Does It Matter in Finance?

AI bias occurs when an algorithm produces unfair or unequal outcomes due to the data it was trained on or how it was designed. Financial institutions increasingly use AI for tasks like credit scoring, fraud detection, and customer profiling. But if these AI systems are trained on biased data or their decision-making processes are not carefully monitored, they can unintentionally discriminate against certain groups.

For example, suppose an AI system used for loan approvals has been trained on historical data where specific demographics were systematically denied loans. In that case, this pattern of discrimination may continue, even without human intervention. This poses not only ethical concerns but also legal risks. Kenneth Blanco, former COO for Financial Crimes at Citibank, highlighted that “unintended bias… the ones that hurt people, the ones that discriminate, the ones that violate the law, those are the things that oftentimes people don’t realize are introduced”.

How Bias Affects Financial Institutions

AI bias can lead to violations of regulatory standards, such as anti-discrimination laws. In the U.S., for example, the Equal Credit Opportunity Act (ECOA) prohibits lenders from discriminating against applicants based on race, gender, or age. Similarly, the Fair Lending Act ensures that individuals and groups are not unfairly treated in housing-related financial transactions.

If AI systems unintentionally introduce bias, financial institutions could face fines, lawsuits, and reputational damage. This is why regulators are increasingly scrutinizing AI algorithms for signs of discrimination. The risk is particularly high in credit scoring and loan approvals, where biased outcomes can severely impact consumers’ financial lives.

The Role of Data in AI Bias

One of the main culprits behind AI bias is the data used to train the algorithms. Financial institutions often rely on historical data, which can reflect past inequalities or systemic discrimination. For instance, if certain communities were previously underbanked or faced discriminatory lending practices, AI systems trained on this data may perpetuate those patterns.

Blanco warned that institutions must understand “the quality of the data, the source of the data, the amount of the data” to ensure their AI systems aren’t inheriting or amplifying bias. Cleaning, balancing, and regularly auditing datasets is essential for minimizing the risk of biased outcomes. Institutions should also be cautious of underrepresentation in their data, as small sample sizes for certain demographics can lead to skewed results.

How Regulators Are Responding

Regulators are becoming more attuned to the risks of AI bias, and financial institutions are feeling the pressure to ensure their systems are fair and transparent. The European Union’s AI Act, which came into effect in August 2024, imposes stringent rules on high-risk AI systems like those used in financial services. One of the key aspects of this legislation is the focus on preventing discrimination by ensuring transparency and human oversight of AI decisions.

In the U.S., the Consumer Financial Protection Bureau (CFPB) has also raised concerns about using AI in financial services. Regulators are urging companies to adopt explainable AI—models that can provide clear, understandable reasons for each decision.

This helps ensure compliance with laws like ECOA and prevents hidden biases from affecting critical decisions.

Mitigating Bias: Best Practices for Financial Institutions

Financial institutions can take several steps to minimize AI bias and ensure compliance with regulations:

Diverse Teams: Assemble diverse AI development teams to reduce the risk of blind spots in data selection and algorithm design. Having people from various backgrounds involved in creating and reviewing AI models can help catch biases before they become systemic. Bias Testing: Regularly audit AI systems for biased outcomes. Financial institutions should adopt frameworks to test for discrimination based on gender, race, or other protected characteristics. Ongoing monitoring is essential to catching biases early.

Explainability: Focus on using explainable AI models. Financial institutions can meet regulatory requirements and build customer trust by ensuring that AI decisions can be easily understood and explained.

Data Governance: Improve data governance practices. Ensuring that datasets are representative, clean, and balanced is one of the most effective ways to reduce the likelihood of bias. Regularly updating data sources can prevent the AI system from relying on outdated or biased information.

By focusing on diverse teams, transparency, explainability, and robust data governance, financial institutions can reduce the risk of bias in their AI systems and ensure they are fair and compliant with regulatory standards. Ultimately, embracing these best practices will help institutions harness the power of AI without falling into the traps of unintended discrimination.

At MBK Search, we help firms find world-class talent to build champion teams across regulated markets. Let's start building — visit our website to find out how. www.mbksearch.com