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$3 Billion Wake-Up Call Shaking the Banking World; AI's Multiple Elements

Hello everyone! Welcome back to the Risk Queue. This week is all about AI and a large fine!

-Enjoy, Naeem, CEO & Founder - Risk On Q

PICKS:

  1. AI - AI’s many perspectives to consider

  2. Fines - AML Cripples Bank

Risk Headlines

Key Points:

TD Bank pleads guilty and agreed to pay over $3 billion in penalties, the OCC cited "significant, longstanding, systemic breakdowns" in TD's transaction monitoring program, allowing hundreds of millions in suspicious transactions. The results in a loss of regulatory trust and increase operational costs and scrutiny.  This also reveals critical weaknesses in risk management, compliance capabilities, and a lack of a strong risk culture.

The OCC imposed an asset cap, preventing TD's retail business from growing above its current asset level in the U.S.  The bank plans to reduce its $434 billion U.S. asset portfolio by 10%, including selling some jumbo mortgages and auto-dealer loans, to create lending capacity within the asset cap.  This restriction will significantly hamper the bank's growth strategy and competitive position in the U.S. market.

CEO Bharat Masrani announced he is stepping down, signaling a major shake-up in top management in response to these issues.  TD shares were down more than 5% on the news.  

This is a significant financial hit that will impact the bank's bottom line and potentially affect shareholder value for many years, with billions in revenue loss at Wells Fargo due to similar risk and compliance events. If you are a firm looking to commit to risk excellence and create value from risk management lets talk. 

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Key Points:

The Q3 earnings reports for major US banks are expected to reveal a challenging environment characterized by shrinking margins and declining profits across the board. JPMorgan Chase, Wells Fargo, Bank of America, Citigroup, and Goldman Sachs are all expected to report significant drops in earnings per share, ranging from 8% to 35%. This industry-wide trend suggests systemic challenges rather than institution-specific issues.

While traditional banking activities are under pressure due to rising deposit costs and weak loan demand, diversified revenue streams from investment banking and trading are providing some relief.

A.I. Risk / Technology Risk

Key Points:

GenAI is dramatically enhancing financial research capabilities, allowing analysts to generate insights with unprecedented speed and efficiency. For example, Moody's has developed a GenAI-powered research assistant that can analyze multiple documents and provide concise summaries in seconds, reducing the time to write comprehensive credit summaries by over 60%.

For risk assessment, GenAI enhances early-warning systems and portfolio analysis, while in KYC and AML processes, it streamlines information gathering and investigative tasks. Successful implementation requires careful consideration of operating models, risk management frameworks, data strategies, and ethical considerations. 

While the potential is enormous, challenges remain in balancing efficiency gains with implementation efforts, ensuring output quality, and developing comprehensive validation frameworks for GenAI model outputs in this highly regulated industry

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Key Points:

The IEEE-USA AI Governance Maturity Model represents a significant step towards operationalizing responsible AI practices within organizations. By bridging the gap between high-level principles and concrete actions, it addresses the pressing need for practical tools in AI governance.

The model's flexibility and comprehensiveness reflect the complex, multifaceted nature of AI risks and responsibilities, while its alignment with the NIST framework ensures its relevance and credibility. This approach not only facilitates internal improvement but also promotes transparency and accountability in the broader AI ecosystem.

Regulatory News - Fines, Losses, & Rules

Key Points:

SEC Chair Gary Gensler talks about Artificial Intelligence, fraud and the securities laws. As we integrate AI into our financial operations, it's crucial to understand that while AI provides new capabilities, it doesn't change our fundamental legal and ethical responsibilities. We must be vigilant in implementing robust guardrails for our AI systems to prevent both intentional and unintentional harm. The SEC's historical stance on fraud is likely to be applied equally to AI-facilitated misconduct. As such, we need to ensure our AI deployments are not only efficient and innovative but also compliant with existing securities laws and ethical standards.

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Key Points:

The audit landscape is evolving rapidly with the integration of AI, presenting both opportunities and challenges. While companies expect audit firms to leverage advanced technologies for improved efficiency, they still highly value human expertise and professional skepticism.

There's a growing awareness of potential AI-related risks in the medium term, necessitating proactive risk management strategies. As organizations increasingly involve their internal audit functions in AI research and implementation, there's a clear trend towards a hybrid approach that combines technological innovation with traditional audit skills.

Risk Data to Geek Out On

Key Points:

Deloitte's article on reputation risk management in banking provides a comprehensive overview of current best practices and areas for improvement. The analysis is particularly relevant given the increasing scrutiny banks face from regulators, customers, and other stakeholders.

The article emphasizes the need for a strong but flexible reputation risk management framework. Such a framework should not only identify and mitigate risks but also actively challenge business decision-making and strategy. This suggests a shift from viewing reputation risk management as a defensive measure to seeing it as a strategic tool that can inform and shape business operations.

Deloitte identifies several key areas where banks can improve their reputation risk management:

  1. Governance and Strategy: Banks should embed clear 'pillars of reputation' that define what the organization wants to be known for. This provides a clear benchmark against which potential risks can be assessed.

  2. Structure and Organization: While the specific location of the reputation risk function (e.g., risk, compliance, or corporate affairs) is less important than its outcomes, a clear operating model with defined roles and responsibilities is crucial.

  3. Culture and Leadership: Incorporating external perspectives into risk assessments is vital. This 'outside-in' view helps organizations better understand and respond to stakeholder perceptions.

  4. Identification and Assessment: Banks need to balance monitoring minor reputational issues ('barnacles') with scanning for major threats ('icebergs'). This requires a combination of detailed monitoring and big-picture thinking.

  5. Escalation and Decision-Making: Processes must keep pace with the fast-moving banking environment. Agile, technology-enabled solutions can help streamline decision-making without sacrificing thoroughness.

  6. Measurement and Reporting: Reporting should provide actionable insights rather than just summarizing events. A holistic view incorporating various data points is necessary to effectively track reputation risk.

The article also notes the potential for increased regulatory focus on reputation risk. While current formal regulations are limited, the growing scrutiny of banks and the politicization of banking issues may lead to new rules and guidelines.

Overall, Deloitte's analysis suggests that effective reputation risk management in banking is becoming increasingly sophisticated and integrated into broader business operations. Banks that can develop proactive, flexible, and insight-driven approaches to reputation risk are likely to be better positioned to navigate the complex challenges ahead.

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Thank you for reading,

Naeem

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