System

A bespoke capital-markets data model, industry-anchored (ISDA, ISO 20022, FpML conventions) and shaped by 20+ years of front-to-back banking experience. 1,019 type definitions, 42 ISO 20022 message types, and 14 FpML schemas, each parseable, queryable, and validatable at runtime. Source feeds from S&P Global, internal ledgers, and counterparty channels are mapped to typed payloads on ingest, with field-level lineage tracked from origin through every transformation. The Schema Editor (extend / wrap patterns) lets domain experts model real bank-specific extensions on top of the canonical core without forking.

Two classes of specialist agent, coordinated by a multi-agent orchestrator. ETL agents build the CDM-typed Operational Data Store: CDM-native modelling, validation, and ingestion with field-level lineage. Operations agents run the workflows on top of it, one set per business unit (front office, risk & analytics, operations, compliance, treasury / finance). The agents run on Anthropic’s Claude via the Claude Agent SDK; the orchestrator owns routing, payload typing, retry, and audit, and nothing in the design binds it to one model. Each agent generates candidate implementations against the loaded schemas; a senior capital-markets expert selects, edits, and signs off. Every prompt, context, correction, and resulting code change lands in the directorial archive for replay and audit.

• 01
  Trade lifecycle automation

  Match firm-vs-counterparty confirmations on economic terms; surface exceptions with field-level diffs. Electronic confirmation via MarkitWire and DTCC CTM; affirmation T+0, confirmation T+1/T+2. Aging analysis with SLA breach alerts.

• 02
  Risk reporting generation

  Score each trade against per-regime field-completeness rules (EMIR Refit, MiFID II, ASIC, CFTC 43/45, SFTR, Dodd-Frank — six regulatory regimes). Generate the report payload in the regime’s prescribed format. Scheduled daily/T+1 runs into the submission queue with one-click trade-repository submission.

• 03
  Portfolio analytics pipeline

  Aggregate live positions; attribute P&L; detect anomalies in trade quality and counterparty data. KPI tiles, trend charts (7d / 30d / 90d), and anomaly feed with severity and recommended action. Drill-down into anomaly detection, data quality, and pattern mining.

• 04
  Financial data ingestion workflow

  Map source fields (S&P Global, internal ledgers, counterparty feeds) to ISDA CDM types. Validate against CDM, ISO 20022, and FpML schemas. Per-counterparty data-quality scoring with longitudinal trend; field-level lineage from origin to operational data store.

Azure-native. Claude (Anthropic) as the agent runtime, Postgres for the operational data store, Container Apps for the service mesh, Microsoft Entra ID for identity. APRA CPS 234-aligned operational-controls baseline. The reference implementation is marketplace-bound: deployable into your Azure tenant, licensed as a reference platform, or operated under managed-service terms. Everything is inspectable, extendable, and externally testable today. No demoware.

Reference system described as a working architecture (not screenshots or UI gallery).

27 themes across 112 pages span 6 operational surfaces: the Operational Data Store (schemas, validators, lineage, entity intelligence) plus 5 business units (Front Office, Risk & Analytics, Operations, Compliance, Treasury / Finance). Every surface is reachable, browsable, and verifiable in a running system rather than a screenshot gallery. A deeper briefing on core services, agent clusters, deployment topology, and operational evidence is available under MNDA.