Production Implementation
Guide

13-section production deployment manual for CAIBots Fraud Detection Agentic AI. Covers system architecture, integration, agent calibration, regulatory configuration, fraud analyst workflow, SR 11-7 model risk management, and examination readiness. Architecture v2.1.

SECTION 01
Executive Summary

CAIBots Fraud Detection Agentic AI is a production-grade intelligence layer that transforms the fraud investigation workflow at financial institutions operating under Reg E (12 C.F.R. §1005.11) and BSA/AML (31 U.S.C. §5318) obligations. It is not a standalone fraud detection system — it enriches and augments existing platforms (NICE Actimize, Verafin, Fiserv) with five specialized AI agents running in parallel.

Problem Solved

Fraud case investigation currently requires 6+ hours of analyst time per case. Reg E 5-day provisional credit clocks are manually tracked and frequently missed. SAR narratives are written from scratch.

How It Works

5-agent parallel pipeline triggered on every qualifying fraud event. Agents synthesize signals from ML inference, account history, behavioral biometrics, regulatory rules, and case management simultaneously.

Outcome

45-minute analyst review (vs. 6 hours), $0.03 cost per SAR filed (vs. ~$2.50), 100% Reg E clock compliance, and <2 second mule network topology detection.

SECTION 02
Pre-Deployment Readiness Checklist

Complete all items below before beginning Phase 1 of the pilot. Items marked Critical must be resolved before Week 1 kickoff.

Technical Prerequisites
Core Banking API: FIS or Fiserv REST API credentials for account history pull (36-month transaction data). Read-only service account required.
Fraud Platform Webhook: Actimize or Verafin outbound webhook endpoint for case event forwarding. Bidirectional API for case writeback.
Behavioral Biometrics: BioCatch or ThreatMetrix enterprise API key. Session data pipeline from online banking SDK.
Network Connectivity: CAIBots infrastructure (AWS us-east-1) whitelisted in firewall. Outbound HTTPS on port 443.
Data Encryption: TLS 1.3 for all data in transit. AES-256 at rest. KMS key sharing agreement signed.
Anthropic API Key: For Scenario 05 Live AI. api.anthropic.com access from pilot environment.
Compliance Prerequisites
Information Security Review: CAIBots security questionnaire completed by CISO team. SOC 2 Type II report reviewed and accepted.
Vendor Due Diligence: Third-party vendor assessment completed per your institution's TPRM policy.
Model Risk Pre-Review: SR 11-7 conceptual soundness documentation reviewed by model risk team prior to production use.
BSA Officer Briefing: BSA Officer briefed on HITL gate design. Confirms agent cannot auto-file or auto-credit without approval.
Data Processing Agreement: DPA signed covering PII handling, data residency, retention, and deletion requirements.
Fraud Analyst Roles: HITL queue access provisioned for participating fraud analysts. Supervisor approval workflow configured.
SECTION 03
System Architecture Overview

The production deployment follows an 8-layer architecture. CAIBots runs as a managed cloud service (AWS us-east-1 primary, us-west-2 failover). Customer data never leaves the agreed data residency region.

Layer 1
Signal IngestionWire/ACH/Zelle transaction events, credential events, device signals → Apache Kafka topic routing
Layer 2
OrchestratorEvent normalization, fraud type classification (ATO/BEC/Synthetic/Mule), 5-agent dispatch
Layer 3
5 Source ToolsParallel: ML Inference · Account History · Behavioral Biometrics · Regulatory Rules · Case Queue
Layer 4
5 Sub-AgentsParallel: TXN-RISK · ACCT-STATE · BIO-BEHAV · REG-COMP · CASE-MGT
Layer 5
Correlation EngineGraph-based signal fusion, weighted confidence scoring, evidence assembly
Layer 6
LLM ReasoningClaude Sonnet: fraud narrative generation, SAR draft, Reg E determination memo, evidence chain citation
Layer 7 🔒
HITL GateMandatory analyst review queue. 5 hardcoded gates. No regulatory action proceeds without human approval.
Layer 8
Regulatory OutputsSAR via FinCEN BSA E-Filing · CTR · Reg E provisional credit determination · OFAC block report
SECTION 04
Core Banking Integration (FIS / Fiserv)

Account State Analyzer requires a read-only connection to your core banking system to construct the 36-month behavioral baseline. Integration is via REST API with read-only service account. No write access is requested or used.

STEP 1 — API Credentials
Create read-only service account in FIS/Fiserv. Scope: account metadata, transaction history (36 months), beneficiary history, login event log. No PII write permissions.
STEP 2 — Data Retrieval Test
CAIBots pulls 100 test accounts and constructs baseline. Validate completeness: transaction count, date range, payee diversity. Estimated time: 4 hours on first run.
STEP 3 — Incremental Sync
After initial baseline, incremental sync runs every 4 hours via webhook or polling. New transactions appended to account behavioral model. Baseline refresh: rolling 36-month window.
SAMPLE API CALL
GET /accounts/{account_id}/transactions
Headers:
Authorization: Bearer {service_token}
X-Institution-ID: {institution_id}
Params:
from_date: 36 months prior
include_fields: amount, date, payee, channel, geo
Response:
{ "transactions": [...], "account_meta": {...} }
SECTION 05
Behavioral Biometrics SDK Integration

Behavioral Biometrics Agent requires session data from your online banking application. This is the most technically complex integration — estimate 3–4 weeks for SDK instrumentation by your web/mobile team.

BioCatch Enterprise

JavaScript SDK embedded in online banking web app. Mobile SDK for iOS/Android. Session data streamed to BioCatch cloud in real time. BioCatch API returns behavioral risk score per session within 200ms. No PII leaves the SDK layer.

ThreatMetrix (LexisNexis Risk)

Device fingerprinting tag embedded on login page. Returns device ID, IP reputation, proxy/VPN/Tor flags, and device-to-account association history. Integration via REST API with session correlation token. 3-week implementation typical.

Sardine

Sardine SDK adds complementary device and behavioral signals with strong coverage for digital-native fraud patterns (Zelle fraud, ACH manipulation, P2P scams). REST API integration. Most useful for institutions with high P2P/Zelle transaction volume.

SECTION 06
ML Model Deployment (XGBoost + GNN)

Transaction Risk Scorer uses two complementary models. Both are deployed as managed services by CAIBots — the institution does not manage model infrastructure. Institution-specific fine-tuning occurs in Weeks 1–2 using historical fraud labels provided under data processing agreement.

XGBoost Ensemble

Gradient-boosted tree ensemble trained on labeled fraud/non-fraud transactions. Features: transaction amount (raw and percentile rank vs. 36-month baseline), velocity (24h, 7d, 30d windows), time-of-day, day-of-week, payee type, channel, geographic anomaly score.

Training: 90-day rolling window · Weekly retraining · SHAP feature importance logged
Graph Neural Network (GNN)

PyTorch Geometric GraphSAGE model trained on account transaction graph. Nodes: accounts, entities, devices, IPs. Edges: transaction flows, shared device, shared IP, beneficiary relationships. Propagates fraud signals across account neighborhoods. Essential for mule network detection.

Graph size: up to 1M nodes · Inference: <200ms · GNN traversal depth: 3 hops
SECTION 07
Case Management Integration (Actimize / Verafin)

CAIBots integrates with your existing fraud case management system. Analysts continue using Actimize or Verafin as their primary interface. CAIBots enriches each case automatically via webhook and writes the HITL packet back to the case record.

Inbound: Alert Forwarding

Actimize/Verafin fires webhook on qualifying fraud alert. Payload: case_id, account_id, event_type, transaction_details, risk_score (existing). CAIBots orchestrator receives, classifies fraud type, dispatches 5-agent pipeline.

Outbound: HITL Packet Writeback

After 5-agent pipeline completes, CAIBots writes enriched HITL packet back to Actimize/Verafin case via REST API. Analyst sees the HITL packet within their existing UI. No new application to learn.

SECTION 08
Fraud Analyst Workflow Configuration

Fraud analysts work within a restructured workflow. Their expertise shifts from data gathering to evidence review and regulatory decision-making. Expected analyst time per case: 45 minutes vs. previous 6 hours.

0–5 MIN
HITL Packet Review

Open HITL packet in Actimize/Verafin. Review fraud narrative, evidence summary, agent confidence scores, and all regulatory deadlines. Verify fraud type classification is correct.

5–15 MIN
Evidence Verification

Spot-check agent evidence exhibits. Verify BioCatch score matches session notes. Confirm GNN mule topology if applicable. Review Account State deviation chart. Check SAR narrative field completeness.

15–25 MIN
Regulatory Decision

Make Reg E provisional credit determination (mandatory HITL). Review and approve/modify SAR narrative. Authorize wire recall or account freeze if applicable. All decisions timestamped.

25–45 MIN
Filing & Documentation

Submit SAR via FinCEN BSA E-Filing (pre-populated from CASE-MGT agent). Complete CTR if applicable. Document Reg E determination in case record. Case closed in Actimize/Verafin.

SECTION 09
Regulatory Compliance Configuration

The Regulatory Compliance Agent is configured with your institution's specific thresholds, policy elections, and regulatory elections. Configuration is documented and versioned. All changes require sign-off from BSA Officer.

Reg E Configuration

Institution policy election: Reg E coverage scope (consumer accounts, business accounts, specific products). Provisional credit thresholds. Extended investigation period elections (45 days for new accounts). Notification templates pre-populated with institution letterhead.

SAR Configuration

SAR filing thresholds by fraud type. Aggregation lookback window (institution-defined, typically 90 days). SAR continuation eligibility rules. FinCEN BSA E-Filing credentials configured. BSA Officer signature block pre-populated.

CTR Configuration

CTR threshold: $10,000 (statutory, 31 CFR §1010.311). Aggregation logic for multiple same-day cash transactions. CTR exemption registry integrated for exempt persons under 31 CFR §1020.315. FinCEN CTR E-Filing credentials configured.

OFAC Configuration

OFAC SDN list TTL: 1 hour (auto-refresh). Fuzzy name match threshold: configurable (default: 85% similarity). Blocking account designation. OFAC block report template pre-populated. Escalation chain to OFAC compliance officer. Block report filing per 31 CFR §501.603.

SECTION 10
HITL Gate Configuration

All 5 HITL gates are hardcoded at the system level. They cannot be disabled, bypassed, or configured to auto-approve. This is a non-negotiable design constraint. Any configuration request to bypass HITL gates will be declined.

GATE 1
Reg E Provisional Credit Decision

Triggered on every case where REG-COMP determines Reg E coverage. Analyst sees: unauthorized transaction evidence, Reg E eligibility analysis, 5 business-day clock display, approve/deny buttons. Decision logged with timestamp, analyst ID, and rationale field.

GATE 2
SAR Filing Authorization

Triggered when CASE-MGT assembles SAR narrative. Analyst sees: full SAR narrative draft, all FinCEN fields pre-populated, 30-day deadline display, evidence exhibits. Analyst reviews, edits if needed, digitally signs, submits via FinCEN BSA E-Filing. Agent never submits.

GATE 3
Wire Recall Authorization

Triggered on confirmed ATO or BEC with outgoing wire. Time-critical — wire recalls are most effective within 24–48 hours. Analyst sees: wire details, ATO/BEC evidence, recall success probability estimate. Analyst authorizes or denies recall via button with confirmation dialog.

GATE 4
Account Freeze / Closure

Triggered on confirmed mule account or synthetic identity bust-out. Analyst sees: network topology (for mule cases), synthetic identity evidence, fraud loss estimate, customer notification requirements. Analyst authorizes restriction type and notification approach.

GATE 5
OFAC Block Report

Triggered on SDN match confirmed by TXN-RISK agent. 10 business-day filing clock displayed. Analyst sees: match details, blocking documentation, Form TDF-90-22.50 pre-populated. Analyst reviews, submits to OFAC. All actions timestamped for examination.

SECTIONS 11–13
SR 11-7 Model Risk · PII/GDPR · Exam Readiness
Section 11 · SR 11-7

Complete model validation documentation package: conceptual soundness assessment for XGBoost and GNN, backtesting methodology, performance benchmarks, feature importance documentation, ongoing monitoring schedule, and model risk governance framework. Designed for independent validation review.

Section 12 · PII / GDPR

Data architecture: PII never stored in raw form outside secure vault. Tokenization applied at ingestion. Processing purpose limitation documented per GDPR Article 5. Data retention schedule: 7 years for SAR-related data (BSA requirement), 2 years for behavioral data. Right to erasure procedures documented.

Section 13 · Go-Live Checklist

22-item go-live checklist covering: all UAT scenarios passed, BSA Officer signoff on SAR quality, model risk team approval of SR 11-7 package, Information Security final review, fraud analyst training certification, FinCEN BSA E-Filing credentials validated in production, and incident response plan approved.

Ready to Begin Integration?

In the architecture call we walk through your specific stack — FIS vs Fiserv, Actimize vs Verafin, BioCatch vs ThreatMetrix — and produce a custom integration timeline. Pilot begins within 2 weeks.

Schedule Architecture Call → View Architecture Diagram