Portfolio demo - synthetic data.
This dashboard illustrates the product thinking behind a biller-facing collections analytics surface I designed for a national bill-payments platform serving 20,000+ billers across 30 categories. All billers, figures, and trends below are generated sample data. No proprietary data, designs, or internal material are reproduced.
Biller Collections Analytics
Self-serve performance view for a biller's collections through the platform rails
Transaction volume
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Collections value
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Success rate
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Technical decline
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Business decline
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Complaints / 10K txns
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Volume and success rate by month
Volume growth means little if success rate decays with it - both on one chart so the trade-off is visible.
Decline rates: technical vs business
The split is the routing logic. Technical declines (gateway, timeout, connectivity) are the platform's to fix. Business declines (validation failures, fetch mismatches, customer-side) are the biller's funnel to fix.
Volume mix by category
Category mix sets benchmark expectations - a utility and an insurer should not be judged on the same decline baseline.
Complaints per 10K transactions by category
Complaints are normalised per 10K transactions, not raw counts - raw counts just rank the biggest categories.
Biller detail
Click a column header to sort. The SPOC view a biller's operations team logs into - their own numbers, benchmarked against their category.