Platform — Riftbeacon

The Problem

Rule-based monitoring was not designed for how digital banks operate

Compliance and risk teams at digital banks — typically Chief Compliance Officers and BSA/AML Officers at challenger banks with $50 million to $2 billion in deposits — are legally required to file Suspicious Activity Reports and maintain BSA compliance. The tools available to them are built for a different kind of bank.

Existing rule-based transaction monitoring systems were designed for the transaction patterns and customer profiles of traditional banks. When deployed at neobanks serving gig workers, digital-first small businesses, or underbanked populations, the same static dollar thresholds generate alert volumes that no small compliance team can realistically investigate. Up to 95% of those alerts are false positives.

The result is a compliance program that operates in triage mode. Analysts spend most of their time closing alerts that should never have fired, and the real risk signals buried in the noise receive the same cursory review as the obvious false positives. FinCEN enforcement actions against digital banks tripled between 2022 and 2024 — not because neobanks are less diligent than traditional banks, but because the tools they use were not built for their risk profile.

95% False-positive alert rate in legacy rule-based transaction monitoring systems at digital banks

800–2,000 Alerts per BSA analyst per month at a typical neobank with a growing customer base

3× Increase in FinCEN enforcement actions against digital banks between 2022 and 2024

Abstract data pipeline visualization showing entity relationship graph nodes and data streams

Input

Connect your core banking data

Bank transaction data arrives via REST API or SFTP batch. Supported sources include FIS Modern Banking Platform, Mambu, and Temenos core banking exports, plus wire and ACH logs, customer KYC attributes from Sardine or Alloy, and historical SAR filing records. The initial integration is typically completed in two to four weeks with a dedicated implementation engineer. No code changes are required to your core platform; Riftbeacon reads the standard export formats your system already produces.

Processing

Graph analysis and adaptive ML scoring

Riftbeacon's ML scoring engine ingests raw transaction streams and applies graph-based entity relationship analysis to identify structuring, layering, and integration patterns across customer networks. The graph layer sees what row-based rules cannot: accounts that share a device, a residential address, or a pattern of round-dollar transfers on the same day are evaluated as a connected cluster, not as isolated events. Behavioral baselines are updated daily so alert thresholds adapt to each bank's actual risk profile rather than vendor defaults. A gig-economy payroll product has different structuring signals than a business checking account — the platform calibrates separately for each customer segment.

Output

Prioritized queue with SAR drafts

Compliance teams receive a prioritized alert queue ranked by risk score, with auto-generated SAR narrative drafts, entity relationship maps, and supporting transaction timelines attached to each escalated alert. Output is delivered to the team's existing case management system — NICE Actimize or a comparable platform — or via Riftbeacon's web dashboard. The SAR narrative draft assembles the relevant evidence into the structured format FinCEN examiners expect, so analysts review and edit rather than write from scratch. Preparation time drops from three to four hours per SAR to under thirty minutes.

Graph-Based Entity Resolution

Connect accounts, devices, and counterparties across your customer network

Riftbeacon maps hidden relationships across accounts, beneficial owners, and transaction counterparties using graph analysis. Funds flowing through multiple hops, accounts sharing devices or addresses, and shell-entity structures that look clean in isolation become visible as connected risk clusters — giving your team the full picture before the SAR deadline. The graph layer is updated in near-real time as new transactions arrive, so relationship connections are current when an analyst reviews an alert, not frozen at the time of ingestion.

Abstract entity relationship graph with amber threads connecting risk clusters

Adaptive Threshold Engine

Risk thresholds that learn your bank's transaction behavior, not the vendor's

Legacy monitoring tools ship with static dollar thresholds built for the average bank. Riftbeacon baselines each customer segment's normal behavior separately — a gig-economy payroll product will have different structuring signals than a business checking account — so alerts fire when something is genuinely anomalous for that population, not just above an arbitrary cutoff. Thresholds are recalibrated automatically on a daily cycle and can be overridden manually by the compliance team with a documented rationale that becomes part of the immutable audit trail.

Layered amber baseline curves representing adaptive risk thresholds

SAR Narrative Drafting

Auto-generate FinCEN-compliant SAR narrative drafts from alert evidence

For every escalated alert, Riftbeacon assembles the relevant transaction timeline, entity relationships, and behavioral context into a structured SAR narrative draft. Compliance analysts review and edit rather than write from scratch — cutting SAR preparation time from 3–4 hours to under 30 minutes per filing while maintaining the specificity FinCEN examiners expect. The drafting model is tuned on the FinCEN SAR narrative guidance and the FFIEC BSA/AML examination manual, not on generic text. Analysts retain full editorial control; the draft is a starting point, not a final document.

Abstract document composition forming a narrative report

Real-Time Wire Screening

OFAC and sanctions screening on every outbound wire with sub-second latency

Payment operations cannot wait for batch-overnight screening. Riftbeacon screens outbound wire and ACH instructions against consolidated sanctions lists in real time, returning a pass/hold/review decision within 200 milliseconds. False-positive hold rates are kept below 0.3% through fuzzy matching and alias resolution trained on FinCEN reference data. The screening API integrates directly into your payment origination workflow — holds are surfaced immediately to the payments operations team with the specific match reason and confidence score attached.

Real-time amber pulse waves screening transaction flow

Regulatory Alert Summary

Automated digest of FinCEN guidance, FFIEC updates, and enforcement actions

BSA/AML regulations shift frequently and compliance teams cannot afford to miss a FinCEN advisory or an enforcement action that reveals an emerging risk typology. Riftbeacon aggregates new guidance and enforcement actions into a weekly structured digest, mapped to which of your monitoring rules or customer segments each regulatory update affects. The digest distinguishes between guidance that requires an immediate rule change, guidance that warrants a policy review, and informational items — so the compliance team can prioritize their response rather than reading full regulatory releases for every item.

Tiered alert hierarchy with severity-coded amber bands

Compliance Audit Trail

Immutable log of every alert decision, analyst action, and system change

When a bank examiner asks why an alert was closed or how a rule was calibrated, every action taken in Riftbeacon is logged with timestamp, user identity, and decision rationale. Audit logs are immutable, exportable in examiner-ready format, and retained per your BSA recordkeeping obligation — so preparation for exams takes hours, not weeks. Rule calibration changes include the analyst who made the change, the data that supported it, and the date of effect. Threshold overrides are logged separately from automated recalibration so an examiner can distinguish human judgment from model output.

Chronological audit trail with sequential markers on amber thread

Best fit

Digital banks and neobanks with active compliance obligations

The primary customer is a Chief Compliance Officer or BSA/AML Officer at a digital bank or neobank in the United States. The compliance team typically has between three and fifteen analysts managing a customer base of 50,000 to 500,000 accounts, with deposits between $50 million and $2 billion.

Riftbeacon is most valuable at series A through series C fintech companies with an active banking charter or a BaaS partnership that creates direct BSA/AML obligations. The specific pressure point we address is the combination of a growing alert volume, a small investigation team, and a SAR filing obligation with enforceable deadlines.

If your bank is in this position — compliance team is small relative to your customer growth rate, your legacy monitoring system generates more alerts than your analysts can investigate in depth, and you have had at least one exam cycle where examiner feedback touched on alert disposition quality — Riftbeacon is designed specifically for that situation.

Who this platform is not designed for

Riftbeacon is not the right tool for every institution that has AML compliance obligations. Three categories of organizations fall outside our current scope:

Not for

Community banks and credit unions with primarily in-person customer relationships and transaction profiles that do not match the digital-first patterns the ML models are calibrated on
Large Tier 1 banks with existing enterprise transaction monitoring contracts at scale — the integration and customization requirements are beyond our current implementation capacity
Cryptocurrency exchanges and digital asset platforms, which operate under a different regulatory regime with materially different transaction patterns, counterparty risks, and compliance frameworks than bank-chartered entities

If you are outside these categories and believe Riftbeacon may still be relevant, contact us. We evaluate edge cases individually.

The BSA/AML platform built for digital banks