Intelligent Trade Reconciliation

Modernize Trade Reconciliation and Break Management: Capital markets operations teams reconcile high volumes of trades across counterparties, custodians, and internal systems, where mismatches, missing fields, and anomalies drive costly breaks and manual investigation. This professional services offering delivers an intelligent multi-agent solution that automates matching, validation, and root-cause analysis across the reconciliation lifecycle—while keeping operations and control teams in charge of high-impact and exception cases. The result is faster break resolution, more accurate booking, and a transparent, audit-ready record for every reconciliation decision

Intelligent Multi-Agent Framework: A coordinated set of specialized AI agents handles each stage of reconciliation—tiered trade matching that progresses from exact to tolerance-based to model-assisted logic, contextual assembly of break data, root-cause classification with confidence scoring, and action execution governed by defined autonomy tiers. Under a central orchestration layer, the agents share context, retrieve supporting data through hybrid search, and route low-confidence or high-impact breaks to human reviewers, so automation and expert judgment work together. Each classification and recommended action carries confidence scoring and explainable reasoning, giving operations and control teams a clear view of how every conclusion was reached.

Business Capabilities: Match trades across sources using tiered logic spanning exact, tolerance-based, and model-assisted matching Validate captured trade details against reference data, policies, and historical patterns Detect mismatches, missing fields, and anomalies before trades are finalized Assemble contextual break packages to accelerate investigation Classify break root causes with confidence scoring Recommend and execute corrective actions based on configurable autonomy tiers Route low-confidence or high-impact breaks to human-in-the-loop review Maintain audit-ready records and decision traceability across the reconciliation lifecycle

AWS-Native Architecture: Built on AWS, the solution uses Amazon Bedrock for foundation-model reasoning and Amazon Bedrock Guardrails for responsible AI policy enforcement, AWS Lambda for serverless processing, and AWS Step Functions to orchestrate multi-agent workflows. Amazon Athena queries large trade and reference datasets for matching and validation, and Amazon OpenSearch Service powers the hybrid search used to retrieve supporting break context. Amazon Simple Storage Service (Amazon S3) provides secure storage for trade and reference data, while AWS Identity and Access Management (IAM) and AWS Key Management Service (AWS KMS) enforce least-privilege access and encryption of sensitive financial data. AWS CloudTrail, Amazon CloudWatch, AWS Config, AWS Security Hub, and AWS Control Tower deliver audit logging, observability, continuous compliance monitoring, and multi-account governance. The architecture is modular, event-driven, and designed for enterprise-grade resilience.