AML Investigations Platform

AML Investigations Are Drowning in False Positives, Manual Data Gathering, and Fragmented Information.

Bandhan Technologies’ AML investigations platform combines Agentic RAG-driven intelligence with multi-entity relationship graph analytics, giving investigators the fastest path from alert to decision and the most complete view of financial crime networks.

AML Teams Are Overwhelmed.
And Under-equipped.

US financial institutions collectively file over 3 million SARs annually, with an estimated 90% false-positive rate for transaction monitoring alerts. Each investigation requires analysts to manually access 8 to 12 disparate systems, aggregate information from structured and unstructured sources, and build relationship maps by hand.

The result is average investigation cycle times of 15 to 25 days, compliance fatigue, and regulatory risk caused by inconsistent investigation quality.

What Is the AML
Investigations Platform?

The AML Investigations Platform is an AI-powered investigation acceleration tool that combines Agentic RAG (Retrieval-Augmented Generation) with embedded multi-entity relationship graph intelligence, enabling investigators to rapidly surface, connect, and act on financial crime signals across all available data sources.

Core Capabilities

Agentic RAG Investigation Engine

AI agents autonomously search and synthesize information from internal transaction databases, customer records, document repositories, and external news feeds to build a comprehensive investigation brief.

Multi-Entity Relationship Graph

A knowledge graph that maps relationships between customers, accounts, transactions, counterparties, beneficial owners, and external entities, revealing hidden network connections that linear analysis misses.

Optimal Investigation Path Guidance

Graph algorithms that identify the shortest investigative path to determine SAR-filing necessity, reducing analyst time on task.

Multi-Modal Information Mining

Ingests and analyzes structured data such as transactions, semi-structured data such as KYC documents, and unstructured data such as news, sanctions lists, and adverse media, all in a unified analysis layer.

SAR Drafting
Automation

AI-generated SAR narrative drafts based on investigation findings, reviewed and edited by the analyst, not written from scratch.

Incremental
Intelligence

As new information arrives post-investigation, the system flags relevant updates and assesses their impact on prior SAR decisions.

Business Impact

30 to 40%

reduction in investigation cycle time

25 to 30%

improvement in SAR quality scores

80%

more cases handled per analyst per month

60 to 70%

reduction in manual data-gathering time per case

Technical Architecture

Step 1

Step 2

Step 3

Step 4

Step 5

Agentic Orchestration Layer

Autonomous AI agents coordinate multi-source data retrieval, synthesis, and investigation workflow management.

Graph
Database

A purpose-built financial crime knowledge graph with entity resolution and relationship inference capabilities.

RAG Pipeline

A retrieval-augmented generation layer that synthesizes findings from 50 or more internal and external data sources.

Explainable AI

Every finding and recommendation comes with a confidence score and evidence chain, audit-ready and examiner-defensible.

Compliance Workflow Integration

Integrates with leading case management platforms including NICE Actimize, Oracle FCCM, and Fiserv for seamless investigator workflow.