Data Cleanup for Financial Services

Automate Data Cleanup for Financial Services

Stop wasting time on manual data cleanup. Our Harvard-educated automation experts build custom data cleanup workflows specifically for Australian financial services businesses, saving you 8+ hours/week.

8+ hours/week

Time saved

$1,500+/month

Cost reduction

98%

Client retention

2 weeks

First prototype

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The Problem

Manual data cleanup creates these challenges for financial services businesses.

Manual data cleanup wastes hours every week that your team could spend on higher-value work

Regulatory reporting takes days of manual data compilation

Errors in data cleanup create downstream problems across your financial services operations

Audit trail requirements make every process slower and more complex

Automated Workflow

Here is how we automate your data cleanup end to end.

Quality Assessment

Scan your database for duplicates, incomplete records, and outdated information.

✓ Tool: Google Sheets
✓ Action: Assess quality

Deduplication

Identify and merge duplicate records based on matching rules.

✓ Tool: Zapier
✓ Action: Remove duplicates

Standardisation

Standardise formats for phone numbers, addresses, company names, and other fields.

✓ Tool: Zapier
✓ Action: Standardise data

Enrichment

Enrich records with missing data from external sources where possible.

✓ Tool: Zapier
✓ Action: Enrich data

Quality Reporting

Generate data quality scorecards and track improvement over time.

✓ Tool: Google Sheets
✓ Action: Report quality

Tools Involved

We connect these tools into a seamless automated workflow.

Zapier

Google Sheets

HubSpot

Slack

Benefits

What you gain when you automate data cleanup.

Complete Data Cleanup Visibility

Know exactly where every data cleanup task stands at any moment. Real-time dashboards and automated alerts keep everyone informed without chasing.

Data Cleanup Automation Built for You

Unlike off-the-shelf tools, we build data cleanup automation tailored to how your financial services business actually operates. No workarounds or compromises.

Fast Return on Data Cleanup Investment

With 8+ hours/week of time reclaimed, most businesses see measurable ROI within weeks. Reinvest those hours into revenue-generating activities instead of manual data cleanup.

Reduce Errors and Rework in Data Cleanup

Automated data cleanup eliminates typos, missed steps, and human error. Every task follows the same validated process, every time.

Compliance & Regulations

Built with ASIC regulatory requirements, AML/CTF compliance, and Australian Financial Services Licence (AFSL) obligations in mind. Includes audit trails meeting APRA prudential standards.

Data Cleanup for Financial Services Automation FAQ

Data Cleanup automation for financial services businesses typically reaches prototype stage in 2 weeks, with the complete solution delivered in 4-8 weeks. We account for your specific tools, compliance needs, and team workflows from day one.

Our data cleanup automations connect to Zapier, Google Sheets, HubSpot, plus over 150+ other tools and platforms. Rather than replacing what works, we plug into your existing stack so the automation delivers value from day one.

Pricing depends on the complexity of your financial services workflow, the number of systems involved, and any custom business rules. Most automations fall within our standard automation tier. Book a free assessment to get a specific quote based on your requirements.

We design every automation to slot into your current financial services tool stack. During discovery, we document each system and process so the automation wraps around existing workflows seamlessly. Your team's day-to-day does not change - it just gets faster.

All our automations include error handling, retry logic, and alerting. If a step fails, the system queues it for retry and notifies your team. We provide 3 months of post-launch support, and our 98% client retention rate speaks to our ongoing reliability.

Definitely. A phased rollout lets us tackle the biggest pain points in your data cleanup process first. Each phase is standalone and delivers measurable value, so you are never waiting months to see results.