Investment Dashboard.

Multi-step analytical pipeline — built to clear external validation, not to look good in a screenshot.

Investment Dashboard is the institutional equity-research and stress-testing module of the SAA Alliance Sovereign Risk Infrastructure. It operates as a multi-step analytical pipeline built for buy-side asset managers, sell-side single-name research desks, bank risk and model-risk-management (MRM) teams, regulators and external auditors, and sovereign / municipal / supranational scenario owners. The platform produces comprehensive, auditable, byte-replayable investment research and stress reports.

At the core is the Report Engine V2 — per-ticker institutional HTML report (~1.5 MB per asset) with CFA-mandated sections: Investment Thesis · multi-model valuation (DCF + DDM + RIM + multiples + blended) · scenario analysis (Base / Bull / Bear with probability weights) · sensitivity tornado · peer reconciliation · risk decomposition · SWOT. A Buy-Side Executive Summary generator runs under a strict JSON schema ({thesis, why[3], invalidator}), schema-validator, deterministic fallback, and a retry-loop — with an explicit list of blocked sell-side cliches. A business-model-aware SWOT classifies the issuer into a model archetype (consumer hardware / enterprise software / internet services / semiconductors / biotech / financials) before generating the four quadrants. A CFA QA hard-fail gate with four mandatory rules (required sections, valuation reconciliation, three-statement integrity, evidence-ledger coverage) blocks publication if any rule fails.

The Stress Testing Gold Standard v2 module produces institutional stress reports with 13 sections, 7 appendices, and 10 numeric-integrity rules, gated by a 3-layer QA pipeline (schema conformance → critical-section presence → cross-section consistency — waterfall vs MC ≤ 1.0%, factor sums = 100%, champion-challenger |Δ| bounds, capital-floor breach detection, reverse-stress LCR ≥ 30 days, variation-from-prior, Level-3 IPV trigger). 12 institutional blocks ship on every stress report — reverse stress test, 9-quarter capital trajectory, champion-challenger, OOS performance, model-risk capital add-on, liquidity stress, op-risk + cyber resilience, climate stress (NGFS Phase IV + PCAF), reproducibility manifest, n-of-m sign-off chain, 6-quadrant conclusions, and 20+ pre-empted regulator / Big-4 reviewer questions.

Every report carries an append-only SHA-256 audit chain, a reproducibility manifest (Git SHA + container digest + RNG seed + input SHA-256 + replay command) that allows byte-identical replay by an external validator, and a distribution audit log (recipient, IP, PDF SHA-256, classification, timestamp). PDFs ship watermarked with visible classification (CONFIDENTIAL / INTERNAL) and invisible audit metadata. The platform is multi-tenant with per-tenant data root and explicit region tag — ready for hosting at the institutional client under GDPR data-residency constraints. All outputs export to the ARIN 22-agent council for unified cross-domain verdict generation; sub-second math is delegated to the ARIN22 deterministic kernel (US-registered name; class-routed, CRN-anchored at the 99.9 tail) when required — kernel correctness validates on commodity ARM CPU at ~99 µs single kernel call, constant from D = 4 synthetic to D = 200 on real portfolios with no degradation; GPU is for batch scale. No GPU lock-in.

~1.5 MB per asset. HTML + watermarked institutional PDF.

Per-ticker buy-side research report with 14 independently generated, scored, and auditable CFA-mandated sections. Each section is gated by the CFA QA engine before assembly; failure of any hard-fail rule blocks publication.

Eight capability surfaces. One CFA-gated pipeline.

Engine inventory — owned math, Git-SHA stamped, GPU handoff to ARIN22.

Performance reporting at CFA Institute / GIPS standard.

Survivorship-bias mitigation through point-in-time universe; OOS evaluation through walk-forward windows; risk-adjusted attribution through Fama-French 5-factor + Carhart Momentum with Newey-West HAC standard errors; capacity bounded by market-impact analysis.

No green ticks. Structural refusal on any failure.

Institutional stress reports built to clear external regulator / auditor walkthrough on first review. The Gold Standard v2 template is the authoritative reference: 13 sections, 7 appendices, 10 numeric integrity rules. A machine-readable JSON Schema (draft 2020-12) with 17 top-level required fields backs the structural contract. The publication gate runs in three QA layers; failure on any layer returns a structured rejection — no green ticks, no soft warnings.

Real, not green-tick. Structural mechanism, not self-attestation.

The Federal Reserve / OCC / FDIC SR 26-2 framework is implemented as six verifiable pillars — each backed by structural mechanism, not by self-attestation. Honest Failure Guards refuse to emit green ticks if lineage / parity / chain integrity is not confirmed. Materiality Assessment (risk × exposure × purpose) tiers each model to HIGH / MEDIUM / LOW and sets validation cadence accordingly.

Every artefact byte-reproducible by an external validator.

Every report, stress test, evidence pack is reproducible byte-for-byte by an external validator. Four layered mechanisms make this possible: snapshot store with SHA-256 manifest, cross-provider parity check, immutable hash-chained audit log, and append-only distribution audit chain.

Embedded hosting at the institutional client. Isolation is structural.

Designed for embedded hosting at the institutional client under strict data-residency constraints. Every API request resolves a TenantContext; data lives under a per-tenant root path; region tag travels with every artefact for GDPR / regional compliance traceability.

Trial · Standard · Institutional — three commercial tiers.

Public API surface designed for trial, standard, and institutional tiers, with explicit rate limits, SLA, watermarking, and distribution audit. Full integration spec released under standard NDA.

Exact endpoint paths, auth scopes, rate limits, and retention configuration are operational detail and released under standard integration NDA — not disclosed publicly.

Seven AI surfaces. All schema-validated.

• RAG for Peer Comparison — Retrieval-Augmented Generation using NVIDIA NIM for intelligent peer selection and contextual comparison narratives beyond simple metric tables
• DCF Reasoning — LLM-powered explanation of DCF assumptions, sensitivity-analysis interpretation, and scenario narrative generation under a strict schema validator
• AI Report Generator — Automated executive-summary writing with institutional tone, key-risk callouts, and actionable conclusions — under the buy-side schema validator with deterministic fallback
• Translations — NIM-powered institutional-grade report translation (EN ↔ RU) maintaining financial-terminology precision and disclosure faithfulness
• Signal Extraction — Natural-language processing of news articles and earnings transcripts for actionable signal identification, with provenance to source citation
• Portfolio Optimisation — constrained mean-variance optimisation with efficient-frontier visualisation and risk-budget constraints
• Price Predictor & Sentiment — ML-based short-term price-trajectory modelling and multi-source sentiment aggregation, with explicit confidence bands

WSGI + async · polyglot persistence · JWT + bearer · containerised.

Each framework points to the structural mechanism that produces the evidence.

Sixteen regulatory frameworks crosswalked to the explicit system mechanism that implements them. No green-tick attestation: each cell points to the structural mechanism (engine, gate, ledger, manifest) that produces the evidence.

The QA gate is mandatory. No publication path bypasses it.

End-to-end architecture in six layers. The QA / Validation Gate sits between the service layer and the core engines — every artefact passes through it before reaching distribution. No publication path bypasses the gate.

SRE discipline. Five SLOs. Pluggable sinks. Public SLO dashboard.

Production operations are run at SRE discipline: five service-level objectives with error-budget burn-rate alerts, pluggable sinks (log / PagerDuty), a published SLO dashboard, granular health probes per component, complete runbook coverage, and CI / CD that ends with a smoke /health check after each deploy.

This platform is for institutional research, model-risk-management, and educational purposes. Analytical outputs, reports, scores, stress results, and AI-generated content are not investment advice. All investment, hedging, and capital-allocation decisions must be based on the institutional user’s own independent analysis, internal model-risk and compliance review, and consultation with qualified financial, legal, and regulatory advisors. Past performance is not indicative of future results. Reports designated data-pending, BLOCKED_HARD_FAIL, or DEGRADED_ALLOWED must not be relied on for institutional decision-making until cleared through the standard QA gate.

Module 05 of 07.

Investment Dashboard is Module 05 of 07 in the Sovereign Risk Infrastructure. The six sister modules: ARIN (Module 01 — central 22-agent decision council), Global Risk Intelligence (Module 02 — physical-financial digital twins), News Analytics (Module 03 — narrative intelligence), Risk Analyzer (Module 04 — portfolio VaR / CVaR with the ARIN22 deterministic kernel), Digital Assets Analytics (Module 06 — AA-D rating model), and KOKON (Module 07 — control plane, governance, and agent calibration). When sub-second risk math is required, modules call the ARIN22 deterministic kernel (0.298 ms per closed-form revaluation, 1,008-job sampler-independence validated on 8×H100). See the full Platform overview.