Why bank-statement import auto-matches 99% of payments and what makes the 1% exceptions resolvable in twenty minutes instead of an hour.
The old way. Monday morning, three hundred forty payments arrived in the bank account over the weekend. The finance clerk opens a spreadsheet, exports the bank statement, opens the billing system, and starts cross-referencing payment references against open invoices. Two hours of pivot tables later, twenty payments still don't match.
The process repeats every Monday. Half the unmatched payments are typos in the customer's reference; the other half are partial payments that need allocation across multiple bills.
What ISPCQ does. Bank statements import nightly. The auto-matcher pairs payments to invoices by reference, amount, and date heuristics. Three hundred thirty-two of three hundred forty match without human intervention. The remaining eight land in a pre-processing queue, each annotated with the probable matching invoice, the customer's contract status, and any recent support interactions. Aelita's Billing Exception Radar surfaces ageing exceptions automatically.
The operational outcome. What used to take two hours takes twenty minutes. The unmatched-payment queue stays under ten entries even at month-end. Aelita drafts the customer-facing payment-confirmation messages.
One of twenty-two detailed articles on real ISP workflows. Each walks through the problem, what teams used to do, what ISPCQ does, and the operational outcome. The architecture is the same; the workflows differ.