Integrations
BANKiQ connects into your banking stack, payment rails and wider financial crime ecosystem — CBS, LOS, CRM, NPCI, I4C, DoT-FRI, MNRL, AML systems and external AI/ML models.
See the Integrations map →Detection, decisioning, investigation, intelligence and governance — unified in a single enterprise FRM platform, not a patchwork of point tools.
Every transaction, customer and channel flows through one continuous lifecycle.
Transaction, customer, device, behavioural and external data.
Data enrichment, rules, AI/ML and cognitive scoring.
A real-time engine scores and decisions every event.
Approve, decline, step-up or alert — automatically.
Alerts route into case management and analyst queues.
Audit trails, supervisory controls and regulatory reporting.
Where BANKiQ differentiates from a conventional rules-only FRM platform. Open any capability with the + to see the detail.
Supervised, unsupervised and ensemble models score every event against learned fraud typologies rather than static thresholds. Models are trained on your own historical transaction, dispute and confirmed-fraud data.
Champion/challenger execution, drift monitoring and scheduled retraining keep model performance stable as fraud patterns shift.
Each event receives a single composite score assembled from transaction, behavioural, device, network, beneficiary and historical dimensions.
Reason codes accompany every score, so analysts, supervisors and regulators can see exactly why an event was approved, challenged or blocked.
Per-customer and per-account behavioural baselines cover amount profile, velocity, timing, beneficiary patterns, geography, device posture and session interaction.
This exposes account takeover, social-engineering-driven transfers and mule behaviour that rule thresholds alone cannot separate from legitimate activity.
Events are enriched inline with device fingerprint, SIM and telecom signals, IP and geolocation intelligence, beneficiary history, negative lists and consortium feeds.
Enrichment executes within the real-time budget, with graceful degradation and cached fallbacks.
A no-code DSL lets risk teams author, simulate and version scenarios without a release cycle.
Every change is backtested against historical traffic and moves through maker/checker approval.
Rules, models and enrichment execute in one orchestrated pass, returning approve, decline, step-up or hold within the payment window.
Adaptive strategies shift thresholds by channel, segment, time window and live fraud pressure.
A single operations workspace for analysts, supervisors and auditors.
Alerts are generated with a risk rank, typology tag and full decision context, then auto-routed by channel, value band, customer segment and regulatory sensitivity. Duplicate and related alerts are correlated into a single work item so analysts investigate an entity, not a stream of events.
SLA clocks, ageing views and escalation ladders are enforced per alert class, giving fraud-operations leadership a live picture of backlog, breach risk and analyst throughput against regulatory response windows.
A case consolidates every alert, transaction, customer, device, beneficiary and communication artefact into one investigation workspace, with linked-entity views that expose mule chains and repeat offenders across accounts and channels.
Structured dispositions, evidence attachments, notes and timestamped action logs produce an immutable audit trail suitable for internal audit, law-enforcement referral and regulatory reporting.
Queues are defined by typology, channel, value, skill and shift, with automatic load balancing, follow-the-sun handover and surge capacity rules for incident conditions.
Productivity, dwell-time, hit-rate and false-positive metrics are tracked per queue and per analyst, turning operations tuning into a measurable feedback loop.
Every sensitive action — rule promotion, threshold change, model activation, account block, funds hold or limit override — requires an independent checker, with role-based entitlements enforced down to the action level.
Segregation of duties, four-eyes approval, full before/after change capture and one-click rollback satisfy internal-audit and supervisory expectations.
Detection through governance — one continuous capability rail, for evaluators who need the detail.
Signals from every channel are scored the moment they arrive.
Scores become enforced actions inside the payment window.
Alerts flow into a controlled analyst operating model.
Context and learning feed back into future decisions.
Oversight, evidence and reporting across the full lifecycle.
BANKiQ connects into your banking stack, payment rails and wider financial crime ecosystem — CBS, LOS, CRM, NPCI, I4C, DoT-FRI, MNRL, AML systems and external AI/ML models.
See the Integrations map →Event-driven microservices, API-first integration, Kubernetes-ready deployment and high availability design built for enterprise transaction volumes.
Explore the Architecture →Walk through detection, decisioning, investigation and governance with a fraud risk expert.