Accelerating a contact data cleanup surge with Microsoft native RPA

Accelerating a contact data cleanup surge with Microsoft-native RPA

A mid-sized Canadian financial institution launched a client contact cleanup campaign to prepare for MFA as part of a broader cybersecurity program. The campaign succeeded beyond expectations and immediately overwhelmed manual operations. A Microsoft-native RPA solution stabilized service levels in two weeks, reduced handling time to seconds, and ensured only true exceptions reached humans.

Why this mattered

MFA is widely treated as a core control to reduce account takeover risk and strengthen security posture, including in public-sector guidance aligned to zero trust principles. 

Contact changes are not just data entry in financial services. Certain changes can introduce regulatory review triggers, such as potential tax residency indicators under FATCA and CRS obligations. 

The challenge

The Marketing and Communications team asked clients to confirm or update their phone, email, and address using a form inside online banking.

The form did not update any core systems. Each submission generated an email to the contact centre where staff processed the update manually.

• Normal volume: 20 to 35 requests per business day

• Campaign week volume: more than 1,800 submissions

• Manual handling: 3 to 5 minutes per request to open the email, transpose data into the core banking system, resolve errors, and manage regulatory implications

• Baseline SLA: roughly two business days, immediately at risk

As a temporary measure, the campaign was paused and staff from other business units helped process the backlog. It was not sustainable.

A better solution was required, especially because there were no APIs available to update contact information in the core banking system.

Our strategy

We designed and deployed a queue-based RPA solution using the organization’s Microsoft stack, with strict security controls, end-to-end traceability, and clear exception pathways.

This approach reflects leading RPA operating practices:

• Decouple intake from execution using work queues for resiliency and throughput. 

• Build robust error handling and retry logic to manage transient failures cleanly. 

• Implement governance, least privilege, and data loss prevention guardrails appropriate for regulated environments. 

Our approach

We implemented the solution in three parts.

1) Intake and queueing

When an email arrived in the shared inbox from an online form submission, the automation:

• Opened the email and parsed content into structured key-value pairs

  • Example fields: account number, new email, new phone, new address

• Captured metadata for traceability, including the Outlook email ID

• Created a work item and placed it into a queue

Work queues allowed the organization to absorb demand spikes safely and process asynchronously, improving scalability and resiliency. 

2) Automated processing with tightly scoped access

An unattended bot pulled items from the queue and executed the update in the core banking UI.

Controls and safeguards included:

• Least-privilege credentials scoped to search and modify contact information only

• Secure credential handling aligned to Microsoft guidance, with support for vault-backed credentials where appropriate

• Clear exception rules

  • If the banking system raised warnings requiring judgement, the bot cancelled the update, marked the work item as exception, and forwarded the original email with a reason note to the contact centre

  • If no exceptions were raised, the bot completed the update, marked the item processed, and archived the original email for audit

Work item states:

• queued (default)

• processing

• processed

• on hold

• exception

• error

3) Routing, escalation, and production monitoring

Whenever a work item moved from processing into a terminal state, a workflow triggered the next step:

• Processed: archive email and close out the item

• On hold: no action taken

• Exception: forward to contact centre with the reason and context

• Error: escalate to IT operations for monitoring and remediation

This pattern aligns with Microsoft guidance for resilient flows, including structured failure handling and clear operational ownership. 

The results

The RPA solution was designed, built, tested, documented, and deployed in two weeks.

Outcomes:

• Immediate SLA recovery by eliminating the manual bottleneck during the campaign surge

• Average handling time reduced from 3 to 5 minutes to approximately 47 seconds per request

• Months of time savings during ongoing cleanup and MFA readiness work

• Improved data quality by removing transposition errors and enforcing consistent update steps

• Better human focus because only cases requiring judgement reached the contact centre

Illustrative impact (based on the first-week surge of 1,800 submissions):

• Manual effort at 3 to 5 minutes each equals roughly 90 to 150 staff hours

• Automated handling at 47 seconds each equals roughly 23.5 hours

• That is roughly 66.5 to 126.5 hours returned in a single week, plus fewer downstream errors

Best practices baked into the solution

Queue-first design for scalability

Queues buffer demand spikes, support prioritization, and allow multiple workers if parallel processing is needed. 

Exception-first thinking

In financial operations, the goal is not 100 percent automation. The goal is to automate the happy path and route exceptions with full context. This reduces operational risk and improves outcomes.

Security, governance, and DLP guardrails

We applied Microsoft governance guidance to control who can run, edit, or connect to automations, and to prevent accidental data exfiltration via connector misuse. 

Auditability and traceability

Capturing the email ID, maintaining an archive, and logging final states created an audit trail that supports operational assurance and internal control expectations.

Reliability engineering for automation

Retry policies and clear error pathways reduce fragility, especially in UI-based automations where transient issues occur. 

The broader lesson

This project reinforced a practical truth for modern automation programs.

AI can be powerful, but it is not always required to deliver high-impact outcomes. When systems lack APIs and the bottleneck is repetitive, rules-based work with well-defined exceptions, RPA is often the fastest path to stable operations and measurable value.