OmniBank Agents Architecture (v1.1): An AI Agent Operating System for Regulated Banking

This white paper presents OmniBank Agents, an AI Agent Operating System (AOS) for regulated banking. The architecture separates probabilistic reasoning from deterministic execution by introducing a centralized Orchestrator (control plane), departmental Manager Agents (policy-grounded reasoning with constrained retrieval), and Tool Agents (permissioned API execution). The system is designed for bank-grade governance: approval gating, policy-as-code checks, PII/PCI handling, scoped retrieval, immutable audit logs, and model risk management. The paper details the component responsibilities, work-order boundary, event-driven substrate (Kafka), data systems (PostgreSQL, vector store, object storage), threat model, workflow case studies (KYC, fraud, AML, lending), and an evaluation approach focused on both model quality and control effectiveness.Brand: AIinovateHub, (LinkedIn newsletter: AI Vanguard).Related video: https://www.youtube.com/watch?v=nMdX96puPxM

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-29
DOI
https://doi.org/10.5281/zenodo.18423409
Primary Topic
Multi-Agent Systems and Negotiation
Type
article
Field-Weighted Citation Impact
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article

OmniBank Agents Architecture (v1.1): An AI Agent Operating System for Regulated Banking

ganesh prasad bhandari
Zenodo (CERN European Organization for Nuclear Research)
Multi-Agent Systems and Negotiation
article

OmniBank Agents Architecture (v1.1): An AI Agent Operating System for Regulated Banking

ganesh prasad bhandari
article en

Abstract

This white paper presents OmniBank Agents, an AI Agent Operating System (AOS) for regulated banking. The architecture separates probabilistic reasoning from deterministic execution by introducing a centralized Orchestrator (control plane), departmental Manager Agents (policy-grounded reasoning with constrained retrieval), and Tool Agents (permissioned API execution). The system is designed for bank-grade governance: approval gating, policy-as-code checks, PII/PCI handling, scoped retrieval, immutable audit logs, and model risk management. The paper details the component responsibilities, work-order boundary, event-driven substrate (Kafka), data systems (PostgreSQL, vector store, object storage), threat model, workflow case studies (KYC, fraud, AML, lending), and an evaluation approach focused on both model quality and control effectiveness.Brand: AIinovateHub, (LinkedIn newsletter: AI Vanguard).Related video: https://www.youtube.com/watch?v=nMdX96puPxM

Zenodo (CERN European Organization for Nuclear Research)
Clark University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 73%
Multi-Agent Systems and Negotiation
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