A tier-one investment bank needed to reconcile every cash movement within a major legal entity to satisfy liquidity and regulatory mandates. The existing manual process meant overnight spreadsheets, slow exception handling, and limited transparency. cloudlogic.dev led a greenfield build of a matching engine that automated reconciliation, surfaced exceptions instantly, and provided the audit trail regulators demanded.
Where we started
Liquidity, treasury, and back-office teams relied on end-of-day reports stitched together across multiple systems. Reconciliation accuracy depended on human intervention, and visibility into mismatches often arrived days late. The bank wanted an engineered platform that could ingest every cash event, match it in near real-time, and store a tamper-proof lineage for regulators—all without disrupting downstream systems.
- No single source of truth for cash movements across trading, settlement, and payments systems.
- Manual exception handling and overnight batches created regulatory exposure.
- Technology leadership needed to decide between commercial software and a bespoke build.
- Performance and data volumes required careful evaluation of database and big-data technologies.
What we did
- Designed the matching engine blueprint: Led architecture, data modeling, and event flow design so every cash movement could be correlated across upstream and downstream systems.
- Ran the RFI/RFP and technology evaluation: Compared RainStor (Hadoop), Informatica, MongoDB, Cassandra, Apache Spark, MarkLogic, Oracle, and in-memory options like Coherence to balance latency, storage, and cost.
- Delivered iterative builds with a lean squad: Directed a five-person development team, pairing and mentoring across locations, and using TDD with JUnit/TestNG to keep quality high.
- Productionised the platform: Prototyped the initial version, orchestrated the first deployment, and tuned performance using JVisualVM and YourKit.
- Embedded knowledge and governance: Created a Confluence knowledge base, aligned Jira/TeamCity workflows, and worked with project managers, business analysts, and architects on migration planning.
Impact
- Automated reconciliation for every cash movement in the legal entity, providing complete transparency for liquidity reporting.
- Enabled near real-time exception detection, allowing operations to remediate issues during the trading day.
- Informed the bank’s build decision with hard data from technology evaluations, reducing procurement risk.
- Established modern engineering practices (pairing, CI/CD, TDD) in a traditionally waterfall environment.
How the bank works today
The matching engine continues to serve as the backbone for the bank’s liquidity controls, feeding downstream risk and regulatory systems with clean, reconciled data. The engineering patterns—event-driven architecture, automated testing, and continuous delivery—became templates for subsequent back-office modernization programmes, and the knowledge base still anchors onboarding for new developers.