Indian Bank
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🧩 Case Study 1
SWIFT Query Automation for a Leading Indian Bank
🏢 Client
A major private-sector bank in India, engaged in global cross-border payments and remittance operations.
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Project Overview
The client’s remittance operations team received high volumes of SWIFT-based transaction queries from overseas financial institutions. Manual classification and handling of these messages, distributed across multiple systems and internal teams, led to delays, compliance risks, and delivery fatigue. Datalumen Consulting helped scope, design, and deliver an AI-enabled automation solution — SwiftBot — tailored to the bank’s specific operational landscape.
💡 Business Challenge
- Manual routing and decision-making for SWIFT queries (status checks, recalls, acknowledgments)
- Fragmented process across multiple teams and systems, with complex business rules
- Lack of SLA-based tracking and automated follow-ups
- Dependency on individual operator judgment for resolution flow
⚙️ Our Solution
- AI-Enabled Classification: Automated tagging of incoming SWIFT messages and emails using a custom rules engine
- Workflow Automation: Logic-based routing to internal systems and request triggers based on message type and keyword detection
- Scheduled Follow-up Logic: Implemented T+X (e.g., T+7, T+15) follow-up automation for aging queries
- Outbound Communication Handling: Automated response emails and outbound messages aligned with the operational logic
- Automated Reporting: Stakeholder reports scheduled at fixed intervals, providing high-level query and resolution visibility
📊 Business Impact
- Drastically reduced manual involvement in day-to-day remittance query handling
- Improved end-to-end consistency and compliance with internal SLA policies
- Enabled operational scalability without proportionate increase in headcount
- Increased transparency and stakeholder trust through automated reporting and audit trails
👤 Our Role
- Led the initiative as Presales and Delivery Consultant throughout the engagement
- Interfaced with the client to understand operational gaps and draft business requirements (BRD)
- Defined solution architecture and coordinated development around internal system constraints
- Assembled and onboarded the delivery team, including automation developers and business analysts
- Facilitated end-to-end lifecycle execution — from resource planning and UAT coordination to stakeholder sign-off and delivery closure
- Played a strategic role in ensuring delivery alignment with business expectations while managing communications across all involved teams
- Handled coordination between technical developers and the AI/classification logic team
- Supported commercial structuring and post-delivery reporting frameworks