A large UK financial services firm processes 50,000–70,000 customer emails and documents monthly across claims, onboarding, compliance, and account management. Manual triage, document validation, and data re-entry consumed significant staff capacity. Within the first year of deployment, BNXT's digital worker platform returned 1.2 million hours to the business - calculated from system-logged activity across email handling, document validation, and data re-entry tasks - and cut customer inquiry response time by 60%.
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Faster Response Time
Hours Saved
Inbound Emails
Incoming email and document volumes were processed entirely by staff with no automation between intake and action:
Industry: Financial Services / Operations Automation
Services: Artificial intelligence Services
Region: United Kingdom
BNXT's AI services team deployed digital workers combining generative AI, automation, and NLP to handle the full intake-to-action workflow - without manual handoffs at each stage.
Email Classification and Triage
Inbound emails are read, classified by intent - claims queries, onboarding requests, compliance submissions, and account management - and routed automatically. Priority scoring runs at classification, so urgent items surface without manual flagging. Standard responses for common inquiry types are drafted automatically and queued for send or staff review depending on complexity.
Document Validation
Incoming documents are validated against completeness and format requirements using Azure Document Intelligence. Pre-deployment, manual validation carried an error rate of approximately 12–15%. Automated checking against fixed rules reduced that by 55–60%. Missing fields or format errors trigger rejection notices with specific remediation guidance rather than generic bounce-backs.
Data Extraction and System Updates
Validated documents feed an extraction layer that pulls structured data - customer details, policy references, claim values, compliance identifiers - and writes directly to Salesforce and downstream systems via Power Automate. Manual re-entry is removed entirely. Each update generates an audit log entry automatically.
Escalation and Routing Logic
Classification thresholds, escalation triggers, and routing rules are configurable through a low-code workflow engine. Operations teams update logic as product lines or regulatory requirements change - without engineering involvement. Low-confidence classifications route to staff with full context attached.
Reporting and Visibility
Email volumes, processing backlogs, response times, and escalation rates surface through a business intelligence layer in Power BI - replacing manual weekly reporting with real-time dashboards.
All interaction data and audit trails feed into Salesforce via BNXT's cloud services infrastructure, connecting the digital worker layer to existing systems without replacing them.
The 1.2 million hours figure is the aggregate - what it looked like varied by function.
In claims and onboarding, the change was the intake speed. Documents that previously sat in validation queues for 2–3 days were cleared the same day. Staff who spent mornings on overnight email backlogs started the day on exception queues instead - the straightforward work was already done before they arrived.
Document validation saw the sharpest quality shift. Manual checking at volume produces inconsistent catch rates. Automated validation against fixed rules removed that variability - the 55–60% error rate reduction reflects consistency as much as speed.
Data re-entry was the least visible drain before deployment and the clearest saving after. Extracted fields writing directly to downstream systems removed a step performed thousands of times monthly - small per instance, significant in aggregate.
Queue depth, throughput, and escalation rates - now visible in Power BI - changed how capacity decisions were made: against live data, not after the week had closed.
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