Ed Blount/ Modular AI

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Aimlux.ai FinCore platform! Given that it's a modular AI foundation leveraging key IBM ISVs (Equitus, RocketGraph, Wallaroo.ai, and Financle) to drive efficiency on IBM Power 11 for mission-critical applications, the perspective of Ed Blount, the Executive Director for the Center for the Study of Financial Market Evolution (CSFME), would likely be highly focused and positive, with a strong emphasis on governance and risk.

His commentary would revolve around three main themes, which align with his work on AI and regulation in the financial sector:

1. Quantifiable Efficiency and The "Closed System"

Mr. Blount advocates for the use of deep learning (AI) risk models, especially in "closed financial systems" like securities finance, as a test case for reliability and potential exemption from standardized capital rules.

• Positive View: He would likely see the FinCore combination—which includes graph analytics (RocketGraph/Equitus) and MLOps (Wallaroo.ai) optimized for the security and performance of IBM Power 11—as exactly the kind of standardized, verifiable platform needed to bring AI into mission-critical financial applications.

• Operational Improvement: The goal of driving "operational efficiency and quantifiable improvement" directly aligns with his own work on straight-through processing and market efficiency.

2. Auditability and The "Courtroom-Ready" AI

A major theme in his recent commentary is the need to ensure AI models used in finance are auditable to stand up to regulatory and judicial scrutiny.

• Emphasis on Explainability: He has stressed that "black box" AI platforms can create nightmares and that the best models will have an audit trail based on the replication of critical decision parameters.

• FinCore's Fit: The use of Equitus Knowledge Graph Neural Network (KGNN®), which specifically provides context, explainability, and traceability on-premise, would likely be seen as a crucial feature that addresses his concerns about "black box" models. This emphasis on on-premise security and private AI on IBM Power also speaks to the need for data security and control.

3. Supervisory Framework and Standardized Guidelines

Mr. Blount's organization actively proposes the development of a supervisor's examination framework for evaluating relevant AI models.

• A Foundation for Regulation: He would likely view the FinCore's "modular standardized AI foundation" as a necessary step toward industry-wide adoption. Standardized platforms make it easier for regulators to develop consistent examination frameworks.

• Risk Management: He would be interested in how the MLOps capabilities provided by Wallaroo.ai on Power 11 enhance risk management, ensure responsible AI adoption, and potentially contribute to the creation of a robust supervisory framework for these advanced systems.

In summary, he would likely see the aimlux.ai FinCore platform as a sophisticated and necessary development that moves AI in the financial sector away from unvetted "black boxes" and toward auditable, high-performance, and compliant systems running on a secure, optimized platform like IBM Power 11.