Document-Genetics-GlobeABBYY FlexiCapture 10 - Data and Document Capture Customer Success Story

8th September 2011

Increase operational efficiency, improve access to data and reduce labour costs. 

The bank is among the largest real estate financiers offering mortgages in the region with a portfolio in excess of 80 billion Euros.  Mortgages are sold under different brands, largely through a network of independent brokers, and all of the associated paperwork generated is forwarded to the company's centralised team for processing.

Customer
Mortgage division of large multi-national bank with over 400 billion Euros in assets.

Problem
Processing large volume of mortgage application documents received per post

Issue to resolve

  • Document classification is a manual operation, prone to error and time consuming
  • Retrieving documents later is difficult and also time consuming
  • Overall timeline to process one mortgage application is too long
  • Too many employees are required to handle these tasks

Goal
Increase operational efficiency, improve access to data and reduce labour costs

The bank is among the largest real estate financiers offering mortgages in the region with a portfolio in excess of 80 billion Euros.  Mortgages are sold under different brands, largely through a network of independent brokers, and all of the associated paperwork generated is forwarded to the company’s centralised team for processing.

Mortgage applicants must submit a series of supporting documents to the bank in order to secure a loan.  The bank has identified around 200 different types of documents they receive by post on a regular basis, amount them pay slips, employment contracts, passports and other identification cards, city council home appraisals, bank account statements, insurance policies, marriage certificates and pension documents.

Each parcel that arrives must be opened by one of the dozen employees in the central mail room.  These workers must forward the documents on to the processing department where more than 200 clerks commence the time intensive task of identifying each type of document and correctly filing it with the corresponding customer record.

The volume of paperwork involved is large and the amount of labour intensive.  On average 25,000 individual documents arrive every single business day and they all must be categorised and filed correctly.  The problems with this process are threefold: the time to manually identify documents is too long, the chances for human error are high and the time required later for clerk to search and find a single document in order to approve or deny the customer's mortgage application is often lengthy.

To speed up this process the bank turned to ABBYY FlexiCapture, an intelligent data capture platform which automates the classification of documents and also performs key data extraction.  FlexiCapture can be used in many different scenarios in almost any industry because of the ability to develop templates to read any type of document.  FlexiCapture analyses each of the elements of a document – text, headings, graphics, etc. to understand what type of document it is in order to correctly classify it.

In the bank's mail room documents sets are checked for completeness, collected into batches and then captured digitally by a scanner.  Each scanned batch is automatically imported into ABBYY FlexiCapture which classifies the document and then input;s it into the customer's back-end Document Management System (DMS).  From the DMS one of the 200 clerks is able to quickly and easily access and retrieve the documents they need in order to process the mortgage applications.

With this solution the bank is now classifying the vast majority of their incoming documents with ABBYY FlexiCapture and the benefits have been clear.  Document separation is done early in the workflow at the scanner station reducing the possibility of errors.  Documents which are recognised correctly are automatically classified into two dozen types which simplifies the search and retrieval process downstream.  And a largely automatic document classification system reduces time and labour and creates significant opportunities for cost reduction.

With a similar configuration organisations can reduce manual labour costs for such tasks by up to 50%.  This frees employees up to focus on higher value tasks.  But more important, the payback period of ROI for such a solution can be achieved in less than 10 months.  Finally, over a three year period a company that processes on average 25,000 documents per day can see a total savings of 200 to 300%.