Archive Articles

Solving DeFi’s Capital Problem: A Securities Lending Bridge for Prime Money Market Funds

DeFi can’t scale real-world assets without institutional balance sheets behind it—and today’s stablecoin lending pools are too small. This paper outlines a compliant bridge: a fully paid securities lending structure that brings prime money market fund (MMF) cash into securities lending economics via a closed-loop, four-leg financing trade. In TradFi, sequential T+1/T+2 settlement forces brokers to pre-fund Treasury “box” collateral and absorb settlement and operational risk. On an RWA blockchain, the same legs can settle atomically—either everything happens at once or nothing happens—eliminating box capital and independent leg failure while automating margin and collateral flows. The remaining friction isn’t technical; it’s regulatory clarity around tokenized Treasury delivery (SEC Rule 15c3-3), MMF eligibility and liquidity rules (Rule 2a-7), and accounting/capital treatment (GAAP/SLR). The economics stay the same—the plumbing changes—and the opportunity is most compelling in hard-to-borrow names where intrinsic lending fees exceed financing costs.

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Lily-Pad Thinking

EB: I’m watching a YouTube video on Python:The Documentary | An Origin Story. I have some questions That sounds like a fascinating documentary!...

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Navigating FINRA Rule 4330: A Broker’s Guide to Fully Paid Securities Lending Programs

Navigating the regulatory landscape of fully-paid securities lending (FPL) programs requires broker-dealers to adhere to a framework of rules centered on customer protection and transparency. These programs offer retail investors a way to generate extra income by lending their securities, which brokers then re-lend to other market participants, often to settle trades or facilitate short sales. The rapid expansion of these retail-focused programs has led to increased regulatory oversight.

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Navigating Transparency: AI Analytics and Compliance in Securities Lending

The securities lending market is entering a transformative phase driven by FINRA’s forthcoming SLATE transparency initiative, launching January 2, 2026. This initiative represents a critical pivot from traditionally opaque practices to unprecedented public visibility, reshaping operational standards for securities lending agents, as well as retail brokers managing Fully Paid Lending (FPL) programs.

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From Shadows to Signals: AI and Transparency in Securities Lending Risks

The securities lending market is about to enter a radically transformative phase. Starting January 2, 2026, SEC Rule 10c-1a will mandate daily public reporting of all U.S. securities loan transactions via FINRA’s Securities Lending and Transparency Engine (SLATE). This regulatory initiative, born from Section 984(b) of the Dodd-Frank Act, introduces a new level of transparency with implications far beyond compliance.

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The Curvature of Market Confidence: How AI Interprets Beliefs Before Prices Move

Large language models (LLMs) are no longer just linguistic engines; they are strategic instruments. By mapping latent structures in human and commercial language, the LLM models form non-Euclidean representations of risk, value, and counterparty behavior. This essay explores how generative AI transformer models absorb social and commercial hierarchies, detect adversarial misalignments, and interpret capital flows as dynamic geometries.

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Deep Learning vs. ARIMA: How Generative AI Models can Improve Market Efficiency by Leveraging the Upcoming SLATE Disclosures

Precision forecasting is the key to maximizing revenues and optimizing collateral in the ever-evolving world of global securities finance. Advanced Securities Consulting (ASC) reached a milestone in predictive data analytics when the firm announced the spectacular results of Phase I for its 2024 Deep Learning Proof-of-Concept (POC I) at the IMN Securities Finance Conference on February 4th in Ft. Lauderdale, Florida.

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Traders’ AI-Boosted Edge in Securities Lending: Proof of Concept Insights for ROI Analyses

Our Phase I Proof of Concept (POC) project demonstrates how professional traders, using guidance from Gen AI transformer models, can outperform competitors at those stock loan trading desks using regression models. The Gen AI advantage stems from the ability of AI-powered models to detect complex trends from vast datasets and deliver precise, actionable recommendations in highly volatile market sectors.

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Gen AI: Sharper Edge of Predictions in Equity Finance

Equity finance in the United States operates within a relatively closed market environment, governed by stable regulations with known participants, settlement and collateral profiles. These conditions produce fewer surprises than more open financial systems that depend on multi-currency capital flows or complex macroeconomic linkages.

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“Where is the Target’s Trajectory Now?”

Accurately identifying shifts in trend forecasts is as important for financial executives as for fighter pilots. Traditional regression models may offer simplicity and ease of interpretation but struggle with the complexities of modern financial markets. How can changes in the trendlines for risk and return be spotted quickly enough to take action? Livelihoods often hang in the balance when decision-makers weigh choices.

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Fed Official Outlines Potential Changes to Basel III Endgame Proposal

On September 10, 2024, Michael S. Barr, the Federal Reserve Board Vice Chair for Supervision, delivered a speech at the Brookings Institution outlining potential changes to the Basel III Endgame and G-SIB Surcharge proposals, originally released in July 2023. Barr characterized these changes, developed collaboratively by the Federal Reserve Board (FRB), the Federal Deposit Insurance Corporation (FDIC), and the Office of the Comptroller of the Currency (OCC), as both “broad and material”.

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Banking Leaders set to Control ‘Shadow Exposures’

Shadow banking is history, say banking leaders, a thing of the past. New compliance and risk management systems based on the Securities Finance Transaction Regulation (SFTR) and the industry’s evolving Common Domain Model (CDM) will enable financial service providers to regulate their clients’ exposure to counterparties with far more specificity than ever before possible. Originally accepted as a regulatory imposition, bankers are now viewing the SFTR reports of their loan principals as a platform to help state pension funds and others meet their ESG and tax compliance goals with unprecedented precision — along with proof of funding.

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