PRISM
Financial crime and regulatory responsibility, transformed.
AI-native financial crime and regulatory operations across the institutional lifecycle.
Deep financial-services expertise and AI architecture brought together across the risk, regulatory and performance priorities of regulated institutions.
Domain expertise gives AI context. AI gives domain expertise scale.
AI-native financial crime and regulatory operations across the institutional lifecycle.
AI-native economic intelligence, optimization, governed intervention and outcome measurement.
Connected domain context across entities, networks, behavior, transactions, models and evidence.
Reasoning, proposals, evidence, human gates and controlled execution.
Policy, authority, model risk, provenance, evaluation, monitoring, audit and replay.
Effectiveness, regulatory performance, operational outcomes and continuous feedback.
Move from alert-centric review to connected identity, relationship, behavior and evidence context.
Explainable relationship intelligence across counterparties, accounts, entities and beneficial ownership.
AI can investigate and propose. Evidence, policy, authority and HITL determine what may proceed.
What: proposed regulated action with source-linked evidence.
Why: policy and model contribution decomposed for review.
Authority: proposer ≠ approver. Refusal remains available.
AI, models, humans and actions operate within explicit policy, authority, validation and audit boundaries.
Connect regulatory clocks, governed-action integrity, detection effectiveness, capacity and programme health.
AML/CFT, KYC/CDD, sanctions, RTM, fraud/FRAML and regulatory reporting share a common evidence and control model.
Governance is not a final-stage review. It spans intelligence, agents, models, human authority, consequential actions and measurement.
Revenue, cost, fees, margin, pricing, client, product, market, processor and route economics.
Leakage, anomaly, root cause, forecast, counterfactual, pricing, routing, opportunity and HITL intervention.
Provenance, explainability, commercial authority, policies, thresholds, approvals, monitoring and audit.
Revenue uplift, margin recovery, leakage reduction, pricing realization, forecast vs actual and attribution.
Connect commercial performance across clients, markets, processors, routes and product structures.
Use anomaly detection, root-cause inference, counterfactuals and forecasting to surface the next economic decision.
Prioritize actions, assign ownership, simulate impact and route commercial decisions through human authority.
Track recovered margin, revenue uplift, leakage reduction, pricing realization and intervention attribution.
Not a separate copilot layer. Domain intelligence, models, reasoning, agents, human authority, governance and measurement are designed to work together.
A common platform philosophy with domain and market context applied where regulation, operating models and economics differ.
Book a focused product discussion across PRISM, MargIQ, or both.