Investment Analytics
Investment Dashboard
One workflow for equity research, portfolio stress and audit-ready reporting.
Generate committee-ready research packs and stress reports in minutes. Every number is deterministic and replayable. AI helps write the text, never the numbers.
Private pilot access · no investment advice · production results proven on client data
Overview · institutional equity research · portfolio stress
Equity research, stress testing and reporting in one controlled workflow.
Investment Dashboard turns a portfolio or single-name request into a committee-ready research pack, stress report and evidence trail.
It runs beside Aladdin, Bloomberg, Murex, MSCI or internal engines as an independent second opinion. No rip-and-replace.
Research in minutes, not days
Full single-name research packs: valuation, peers, risk drivers and what would break the thesis – in one repeatable template.
Stress your whole book
Scenario, liquidity and capital-impact views for large portfolios, powered by a deterministic risk engine.
Reports auditors accept
Every output carries its sources, version and replay instructions. An external reviewer can reproduce any number.
Works beside your stack
No rip-and-replace. Runs alongside Aladdin, Bloomberg, Murex or your internal engines as an independent second opinion.
Use in practice · four controlled surfaces
Apply Investment Dashboard across four core areas.
Short, repeatable outputs for teams that need usable reports, not another black box.
Research system
Structured research packs for equities and cross-asset exposures. Valuation, peer comparison, business drivers and risk factors – the same template every time, so committees compare like with like.
Reporting and documentation
Export HTML or watermarked PDF with classification headers and a full source trail. Built for internal committees and external reviewers alike.
Stress testing
Portfolio stress, scenario analysis and liquidity pressure with four honest states: PASS, WARN, FAIL, INCONCLUSIVE. No soft green ticks.
Controls framework
Deterministic outputs map directly to model-risk documentation: identification, data governance, methodology, limitations and audit trail. Regulator-conversation ready.
Evidence boundary · claim discipline
Built for diligence, not marketing.
Numbers are deterministic and replayable. AI writes narrative only. No investment advice, no alpha claims – production results are proven on your data, during your pilot.
Request access · private pilot workflow
Review the module on your data, under your controls.
Typical pilot path: agree a portfolio fixture, run the dashboard on your data, compare outputs with existing systems, and deliver a short evidence pack for committee review.
This page is not an offer of securities, investment advice, broker-dealer activity, or a claim of third-party certification. Exact integration details and full evidence bundles are released under NDA.