Regulatory requirements are intensifying and diversifying. Firms need to monitor an expanding set of rules, geographic limits, sector exposures, ESG mandates, concentration thresholds, across increasingly complex portfolios. Manual compliance checks can't keep pace, and the cost of getting it wrong is rising.
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Compliance
Show exactly why a check passed. Eight months later. Pre-trade, post-trade, and continuous monitoring powered by live data and AI. Rules are deterministic. Agents do the work around them.
The Industry Challenge
How FINBOURNE helps
Every rule gives the same answer every time. Nothing probabilistic sits between a limit and a breach. AI handles the operational work around the rules: the control checks agent raises exceptions, the portfolio health agent runs diagnostics across a book, and a compliance officer can ask which portfolios breach a single-issuer limit and trace the answer back to the rule that produced it.
Centralised compliance control
Manage firm-wide and entity-specific rules from a single library running on live position data. Test a rule change against production data before it goes live, without a separate environment and without disturbing what your team is working on.
Pre-trade and post-trade coverage
Evaluate compliance rules as part of pre-trade workflows or post-trade through scheduled and ad-hoc processes. Catch breaches before they happen or detect them immediately after.
Show exactly why a check passed
The question that arrives eight months later is why a check passed at the time. FINBOURNE can rebuild it: the rule as it was configured that day, the positions as they stood, the reference data before it was restated, and the result that followed. Drill into the calculation itself rather than the outcome alone.
ESG and responsible investment mandates
Bring ESG ratings and sustainability data in from multiple providers and write mandate rules against any of it, the same way you would against a credit rating or a sector code. Restricted exposures surface through the same breach workflow as everything else.
Features
01Compliance monitoring
Pre-trade and post-trade evaluation on live positions. Compliance dashboards and external reporting. AI agents for diagnostics and rule-based exception handling.
02Compliance rules
Rule libraries and individually customised rules, with access to all data attributes stored in FINBOURNE. Rules against models and benchmarks: test exposure against a model portfolio or a benchmark weight, so limits defined as deviations from a benchmark are tested against the benchmark, not as absolute values.
03Breach management
Breaches are raised, assigned, investigated, escalated and signed off in a workflow you configure. Drill from a breach into the calculation that produced it. Override rules require four-eyes approval, configurable rule by rule, with a documented reason on the permanent audit record.
04External integrations
Externally performed checks display and are managed alongside native rules, in one view, so oversight does not fragment while you transition. Move rules across when it suits you.
AI
Compliance is one of the strongest use cases for AI in investment management. FINBOURNE's compliance agents run continuously on live position data, not batch exports, detecting breaches, routing exceptions, and generating reports. Because they operate through the financial operating layer, every action is governed, auditable, and explainable.
Portfolio health agent ESG agent Control checks agent and moreReady to see FINBOURNE in action?
Questions we hear from compliance teams
How do I prove why a compliance check passed at the time, not just that it did, when a regulator asks eight months later?
FINBOURNE reconstructs the check as it was: the rule as configured on that date, the positions as they stood, the reference data before any restatement, and the result that followed. The calculation itself is reproduced, not just the outcome.
How are firms running pre-trade and post-trade compliance against the same position data without maintaining separate systems?
Compliance rules evaluate against the same position and instrument data used by the IBOR. Pre-trade checks run as part of the order workflow; post-trade checks run on schedule or ad hoc. No separate compliance data store.
What does it look like to test a rule change against production data before it goes live?
A new or amended rule can be tested against live production data without deploying it into the active rule set. You see what would have breached, without disturbing what your team is working on.
How are firms enforcing ESG mandates through the same compliance workflow as concentration limits and geographic restrictions?
ESG ratings and sustainability data from multiple providers are ingested and treated as rule attributes, the same way as a credit rating or sector code. Mandate rules are written against them, and restricted exposures surface through the same breach workflow.
How do I drill from a breach into the calculation that produced it, rather than just the outcome?
Each breach links to the rule, the positions it evaluated, the reference data it used, and the arithmetic that produced the result. Drill-through goes to the calculation, not a summary.
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