GARP refreshes Current Issues annually. The 2024-2025 cycle covers AI in capital markets (IMF October 2024 and FSB November 2024), the global drivers of private credit (BIS February 2025), and geopolitical risk transmission (IMF GFSR April 2025 Chapter 2). The exam tests whether you can name the channel, the source paper, and the policy response. Cite the papers when working through practice questions. The readings ARE the curriculum.
The IMF's October 2024 paper on artificial intelligence in capital markets identifies four production use cases.
Trading and execution. Predictive models forecast short-horizon returns and route orders for minimal market impact. ML systems learn from order-book microstructure that humans cannot fully observe. Quantitative funds have used such systems for over a decade; the marginal change is wider deployment by traditional asset managers.
Risk forecasting and stress testing. ML models combine traditional risk factors (rates, credit spreads, FX) with alternative data (news sentiment, satellite imagery, supply-chain feeds) to produce risk forecasts at higher resolution than econometric models alone.
Common mistakes
- Confusing IMF October 2024 with FSB November 2024. The IMF paper covers AI use cases and policy recommendations. The FSB paper covers AI financial stability vulnerabilities. Trap: an exam stem says "per the FSB" and the candidate answers from the IMF use-case framework, the wrong source.
- Treating AI as a single risk class. AI risk varies by use case. A chatbot is low-risk; an autonomous trading agent is high-risk. The IMF and FSB advocate risk-based supervision precisely because risk concentration matters.
- Ignoring the BIS cost-of-equity channel. The BIS regression places half the variance in private-credit growth on the bank-private-credit cost-of-equity gap. Trap: a question gives a list of drivers and the candidate selects "search for yield" alone; the BIS shows multiple drivers, with cost-of-equity differential dominant.
Bottom line
- AI in capital markets (IMF Oct 2024): current uses include trading signals, surveillance, risk forecasting, and customer-facing chatbots; GenAI raises model concentration and data-governance concerns.
- AI financial stability risks (FSB Nov 2024): third-party concentration, market correlations through model homogeneity, cyber risk, fraud, and model/data governance failures.
- AI adoption drivers: supply-side (compute, models, APIs) and demand-side (labor cost, regulation, alpha) jointly explain the post-2017 acceleration.
- Private credit drivers (BIS Feb 2025): bank retrenchment, capital regulation, yield search, and sponsor demand; the cost-of-equity differential explains roughly half the cross-country variance.
Exam shortcut
When the question references "AI" without specifying use cases, default to risk-based supervision as the regulatory answer. When the question asks about private credit drivers, the BIS's cost-of-equity channel is the highest-weight answer. When the question describes a geopolitical shock, identify which of the five IMF channels applies and answer through that channel.
The full lesson (about 3,311 words, 22 min read) adds 2 worked examples, all 6 common mistakes, a self-check, free in the app.
Learning objectives
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