Risk Headlines

US Stock Markets Soar in Q1 2024 - Navigating Potential Risk Ahead - source yahoofinance.com

Key Points:

A strong first quarter for US stock markets, with the S&P 500 and Nasdaq up around 10% year-to-date. The upcoming PCE price index release could influence the Fed's monetary policy and interest rates, which would impact the bank's operations and strategies.

Banks need to remain vigilant in identifying emerging risks, such as potential changes in consumer behavior, industry-specific challenges, or geopolitical events that could impact the economy. Key focus on lending practices, investment strategies, and hedging mechanisms to ensure that banks are well-positioned to navigate potential changes in the interest rate environment.

A.I. Risk / Technology Risk

Scaling Gen AI in Banking: Choosing the Best Operating Model - source mckinsey.com

Key Points:

Banks' Gen AI journeys are highly sensitive to operating model design choices, and those operating models must dynamically adapt based on the maturity of the technology itself and the organization's experience with it. A centrally led operating model works best for gen AI in banking, enabling efficient resource allocation, risk management, and keeping up with the rapidly evolving landscape.

Getting this balance right demands collaboration across the executive team CROs, CTOs, and CLOs play an active role in shaping gen AI operating models to instill 'risk by design' principles early and advocate for the right level of centralized control. It also requires building robust feedback loops and mechanisms to continually adapt operating models to keep pace with the evolution of gen AI and its expanding risk surface area.

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Data Trends 2024 - Organizations Unlocking AI Innovation - source snowflake.com 

Key Points:

AI adoption is accelerating rapidly, driven by advances in tools, platforms, and democratization. Banks must strategically invest in AI capabilities, especially Python skills. Unstructured data holds immense untapped value for banks, but also introduces new risks. The democratization of AI poses risks from inexperienced users.  Housing AI applications and data together in unified, secure platforms can be a key risk management tool, enhancing security and compliance by reducing data movement and exposure.  AI innovation with strong risk management capabilities is vital in mitigating potential downside risk.

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Cyber Leaders Struggle, C-Suite Question Overly Rosy Picture of their Security Programs - source wsj.com 

Key Points:

There are significant challenges in how CISOs communicate cyber risks to executives and boards. With many CISOs painting an overly rosy picture and hesitating to raise concerns, critical vulnerabilities may go unaddressed. Nearly a third of execs feeling CISOs give an overly optimistic view of security and hesitate to raise concerns, there is high potential for critical vulnerabilities to go unreported.

There is a pressing need to elevate and empower the CISO role to match the heightened expectations and importance of cybersecurity today.  Regulators have pushed for stricter oversight, disclosure requirements, and liability for banks' cyber risk management.

Regulatory News - Fines, Losses, & Rules

U.S. Treasury Department- New Report On Managing AI Risks in Financial Services - source treaury.gov

Key Points:

This is an in-depth look at the state of AI adoption in the banking industry, with a focus on the opportunities and challenges it presents.  AI will create a complex new risk landscape. Key risks include rapidly evolving cyber threats, AI-powered fraud, opaque model decision-making, and third-party dependencies. To manage these risks, banks need to enhance their enterprise risk frameworks with AI-specific practices around governance, risk assessment, model controls, third-party oversight and talent development.

• The speed of AI development is outpacing traditional risk management and regulatory frameworks. Banks and regulators will need to rapidly adapt and coordinate to provide appropriate controls and oversight.

• AI may create competitive disparities between large and small institutions based on access to data, talent and technology. This could have broader financial inclusion and systemic risk implications requiring policy attention.

• AI will be a defining feature of the future of banking and proactive adoption, experimentation and risk management will be critical for all institutions.

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OCC Report Q4 2023 Bank Trading Revenue - source occ.gov

Key Points:

The high concentration of derivatives exposure in interest rate products and among a handful of large banks presents both risks and opportunities. Banks must vigilantly manage concentration and counterparty risks while also seeking ways to differentiate themselves and compete effectively. While notional amounts have decreased, derivatives trading remains a significant source of revenue and risk for banks.

• The four largest banks held 87.4% of all derivatives, while the top 25 banks accounted for nearly 100%

• Derivative contracts remained concentrated in interest rate products, totaling $136.3 trillion or 70.8% of total notional amounts

• Banks' trading revenue was $11.6B in Q4 2023, down 11.8% from Q3 but up 20.4% from a year ago

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OCC Discusses Fairness and Compliance Risk Management - source occ.gov

Key Points:

The landscape of consumer banking is evolving at an accelerating pace due to new financial products, digitalization, economic inequality, and societal expectations around fairness and inclusion. This presents significant challenges for banks in managing compliance risks while also pursuing innovation and growth.  

Compliance and risk management will need to become more dynamic, forward-looking, and integrated with frontline business practices. CROs in particular will need to exert more influence on bank strategy to ensure alignment between growth aspirations and the bank's risk appetite and control capabilities.

Risk Data to Geek Out On

” T+1” Settlement Cycle - What Investors Need To Know - source sec.gov

Key Points:

The upcoming shift from a T+2 to a T+1 settlement cycle for most broker-dealer transactions in the U.S., effective May 28, 2024. This change will significantly impact various aspects of trading and settlement operations for financial institutions. 

The shortened settlement cycle aims to reduce counterparty risk but may introduce new operational challenges that banks must carefully navigate to ensure a seamless transition and maintain regulatory compliance. Careful planning, execution, and risk management is key to ensure successful implementation and ongoing compliance.

Key considerations::

1. Customer impact: Clear communication and proactive engagement with clients will be crucial to manage expectations and ensure smooth adoption of the new settlement cycle. 

2. Operational risk: Evaluate current systems, processes, and staff capabilities to identify gaps and vulnerabilities that may be exacerbated by the shorter settlement timeframe. Develop and implement necessary upgrades, enhancements, and training programs to mitigate operational risks.

3. Liquidity risk: Assess the potential impact of T+1 settlement on the bank's liquidity management practices, including funding requirements, collateral management, and intraday liquidity needs. Adjust liquidity risk management frameworks and contingency plans accordingly.

4. Counterparty risk: While the shorter settlement cycle may reduce overall counterparty risk, it is essential to review and strengthen the bank's counterparty risk management practices, including credit assessments, exposure monitoring, and default management protocols.

5. Regulatory compliance: Engage proactively with regulators to demonstrate the bank's preparedness for the T+1 transition and ensure ongoing compliance with all applicable rules and regulations. Monitor regulatory developments and guidance related to the settlement cycle change and adapt the bank's practices as needed.

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Thank you for reading,

Naeem

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