Financial Sector | Customer Success Story
Banking Industry

ZircoDATA has extensive industry experience in the financial sector. Read on to find out how we utilised our experience and industry know-how to help a major Australian Bank achieve success.


As part of its mortgage fulfillment operations, a major Australian bank servicing over nine million customers across Australia, New Zealand and worldwide, had a disjointed strategy incorporating multiple vendors across scanning of pre and post-settlement documents, document management and archive storage. They approached ZircoDATA with the requirement for an integrated solution which incorporated the collection of pre-settlement mortgage documents from the post office, scanning and document recognition, through to the creation of mortgage security packets and lodgement to secondary (active) and archive storage.

ZircoDATA’s custom solution for this client incorporated a fully integrated mailroom and document management programme. In 5 states, around Australia, returned mortgage documents are collected daily from the Post Office Locked Box from 5am. There are also additional deliveries from the bank’s internal courier service. Mortgage packs are uniquely identified, quality checked, and then scanned. Individual documents are classified using Optical Character Recognition (OCR) and an automated document classification engine containing over 200 document templates. Images are released and transferred throughout the day via drip feed secure file transfer, with the day’s production completed by 4pm. Key value documents are extracted from each batch, and lodged to active storage as security packets. The remaining scanned documents are lodged to archive storage, with metadata uploaded to identify individual documents which are available for retrieval as required.


By streamlining the scanning and document management processes, our client was able to reduce inefficiencies due to multiple hand-off of records, as well as gaining visibility of processed records within 24 hours of collection from the mail. The document classification engine achieves accuracy in excess of 98%, which reduces the need for subsequent triage due to document classification errors.