End-to-End Trade Capture and Settlement Automation at an Asian Tier-1 Bank — 100% STP on Confirmed Trade Tickets
DocuMage + Multi-Agent Orchestrator + Workflow Automator collapsing the trade-capture, enrichment and settlement workflow into a touchless straight-through pipeline.
MindMap OS · installed inside the customer's perimeter by forward deployed engineers · Private Cloud · billed on the result
The challenge
The bank — a top-three commercial-and-investment bank in its market with a substantial wealth-management and treasury operation — was processing trade tickets manually across the front-to-back trade-capture-and-settlement workflow. Trade tickets arrived in five distinct channels: fax from the bank's branch network, email from corporate-banking customers, chat from the institutional-sales desk, scanned post from the back-office mail intake, and structured feeds from the bank's own electronic trading platforms. Each channel was handled by a dedicated operations team, with the result that the same trade-ticket extraction, validation and posting work was being repeated three or four times in slightly different forms.
The operational cost was significant. The front-office trade-capture team spent the bulk of its day on keying activities rather than on the exception-handling and risk-management work that the front-office function genuinely required. The middle-office enrichment team carried a structural backlog of trades awaiting custodian-default lookup, settlement-instruction validation, and counterparty-reference-data confirmation. The back-office settlement-and-reconciliation team was reconciling against a stream of partially-enriched trades and generating manual amendments at scale.
Operational risk was the more pressing concern. Trade-capture errors that flowed downstream to settlement carried material financial exposure — a mis-keyed amount, currency or settlement date on an institutional trade could produce a six-figure-plus loss before reconciliation caught it. The bank's regulator had recently flagged the trade-capture function as an elevated-risk control area in its annual examination.
The approach
MindMap deployed a trade-capture-and-settlement platform composed of DocuMage (Dm) as the document-intelligence layer, Multi-Agent Orchestrator (Mo) as the workflow-orchestration layer, Workflow Automator (Wa) for the legacy-system integration where APIs were not available, and Compliance Engine (Ce) for the trade-validation rules.
Phase one was the channel-consolidation work. We worked with the bank's trade-operations leadership to build a single canonical trade-ticket schema and a per-channel ingestion pipeline that normalises each inbound channel's payload into the canonical schema. The fax channel uses DocuMage with a fine-tuned trade-ticket extraction model. The email channel uses an attachment-aware ingestion path that handles PDF, Excel and inline-text formats. The chat channel uses a structured-extraction prompt over the chat history. The scanned-post channel rejoins the fax pipeline after the central scanning hub. The electronic-trading feeds flow through a direct structured-data path.
Phase two was the enrichment-and-validation layer. Every normalised trade ticket flows through a deterministic enrichment pipeline that pulls custodian defaults, counterparty reference data, settlement-instruction templates, market conventions and tax-treatment rules from the bank's existing reference-data systems. The Compliance Engine validates each trade against the bank's trade-policy library — credit-line availability, regulatory-reporting eligibility, prohibited-counterparty checks, and same-day-settlement constraints — before the trade is released for posting.
Phase three was the posting-and-reporting layer. Validated trades are posted into the bank's core trade-processing engine through an audited API path; trade-confirmation defaults, custodian-and-settlement reporting, and the transactional-reporting feeds for the bank's regulatory and management dashboards are generated automatically. Exception trades route to a unified case-management UI where the operations team resolves the exception with full context — original ticket, enrichment result, validation failure reason, and recommended correction.
The pre-built building blocks
Rather than commission a ground-up build, the engagement leaned on MindMap's pre-built accelerator library — production-tested components that compress what would otherwise be a six-to-nine-month build into weeks.
The architecture
The platform runs inside the bank's private cloud tenant with full in-country data residency. Trade-ticket processing is regional-tenant-isolated to satisfy the bank's cross-border data-handling commitments to its institutional customers.
DocuMage's trade-ticket extraction model has been fine-tuned on roughly 180,000 historical trade tickets from the bank's archive, covering the institutional fax templates, the corporate-banking email formats and the common Excel-attachment patterns. The extraction model produces a structured ticket with per-field confidence scores; fields below the confidence threshold trigger the exception path rather than a posted trade.
Multi-Agent Orchestrator coordinates the enrichment pipeline. Per-trade enrichment tasks run in parallel — custodian lookup, counterparty reference fetch, settlement-instruction retrieval, tax-treatment evaluation — with the orchestrator assembling the enrichment result and handling per-task retries and timeouts. Tasks that fail repeatedly route to the exception path with the failure reason preserved.
Compliance Engine encodes the bank's trade-policy library as deterministic rules. Rules include the bank's internal trade-acceptance criteria (credit-line availability, prohibited-counterparty checks), the regulatory rules (transaction-reporting eligibility, position-limit checks, prohibited-jurisdiction handling) and the operational-risk rules (same-day-settlement feasibility, custodian-cutoff awareness, market-holiday handling). Every rule evaluation is logged with the trade-context and the rule-version that produced the outcome.
Workflow Automator handles the legacy-system integration where the bank's core trade-processing engine and the regulatory-reporting platform did not expose suitable APIs. The RPA workers run inside the bank's private cloud with full audit-trail capture and are progressively being replaced as the underlying systems expose modern APIs.
The platform's audit trail captures every trade-ticket lifecycle event from ingestion through posting, with the originating channel, the enrichment outcomes, the validation rule evaluations and the posting confirmation all preserved against the trade-ticket identifier.
The numbers behind the story
Clean trade tickets — tickets that pass extraction-confidence, enrichment and validation without exception — now flow through the pipeline at 100% straight-through processing, with no human touch between channel ingestion and core-system posting. The bank's trade-capture operations team has been redirected to exception handling and counterparty-relationship work rather than keying.
Trade-capture defects flowing to settlement have fallen substantially. The validation layer catches mis-keyed amounts, mis-matched currencies, and prohibited-counterparty trades before the trade lands in the core, materially reducing the operational-loss exposure from trade-capture errors.
The bank's trade-operations cost per trade has fallen meaningfully across the trade-capture-and-settlement workflow. The middle-office enrichment backlog has been eliminated; the back-office reconciliation team is processing a stream of fully-enriched trades rather than partially-enriched ones; and the front-office team's headcount has been redirected to higher-value risk-management work.
The regulator's follow-up examination of the trade-capture function concluded that the elevated-risk classification had been resolved. The bank's internal-audit team has used the platform's audit trail as a model for other operations-area control-improvement programmes.
“Our trade-capture function was a structural risk our regulator had flagged. MindMap collapsed five inbound channels into a single touchless pipeline, with one hundred per cent straight-through processing on clean tickets and a unified exception-management workflow for everything else. The regulator's follow-up examination cleared the elevated-risk classification. Our trade-operations team is doing trade-operations work now, not keying.”— Chief Operating Officer· Asian Tier-1 Bank
Why MindMap was chosen
The bank had previously evaluated two large global vendors. Both proposed multi-year programmes built around their existing trade-processing platforms that would have required the bank to migrate off its current core. The bank's CTO concluded that the platform-replacement approach was incompatible with the bank's regulatory timeline and its existing IT investment.
MindMap's accelerator-composition approach — bringing DocuMage, Multi-Agent Orchestrator, Compliance Engine and Workflow Automator together around the bank's existing core rather than replacing it — was the structural differentiator. We could demonstrate the same pattern at a comparable Asian bank during the bid, with the proof-of-concept on the bank's actual fax and email trade tickets completed within four weeks.
Our embedded trade-operations expertise on the delivery team (two former trade-operations directors from peer Asian banks and a former custodian-relationship-management lead) was the third factor. The bank's COO felt that the delivery team understood the operational reality of trade-capture in a multi-channel, multi-product, multi-counterparty bank.
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