Allied Payment Network announced Tuesday that it would integrate MobiPAY, a mobile payment solution developed by Top Image Systems (News - Alert), into its PicturePay photographic payment system. PicturePay uses various optical character recognition (OCR) engines to read information from bills, reducing the need to enter data.
Ft. Wayne, Ind.-based Allied Payment Network, Inc.’s (APN) lone solution is PicturePay. It allows customers to take a picture of a bill, enter a payment amount and date and then the bill is automatically paid. Marketing analytics and back-end payment processing are part of the solution as well.
APN’s typical customer is a financial institution that designs user interfaces for customers, but needs a solution that does a lot of the technical work behind the scenes to handle financial transactions. First Financial Bankshares, Inc., an institution with 62 branches in Texas, is the first institution to use PicturePay technology. Its mobile banking customers can download an iOS or Android (News - Alert) mobile app to photograph and pay bills.
Top Image Systems, Ltd. (TIS) is based in Ramat Gan, Israel and develops enterprise content management (ECM) systems that read information from numerous sources like documents and emails, and digitizes the contents. Such digitization formats the information in a way that facilitates electronic searches and retrievals, much like a database.
The technology that allows bank customers to take photographs of documents and have them automatically processed is nothing new. For several years, it has been possible to deposit a check, simply by photographing it, thanks to OCR technology. Years before that service was available, it was possible to scan the information off business cards and store that information electronically.
If you can use OCR to read info from a business card into a digital address book or from a check to process deposits, then you can use it for a lot of other purposes too, including bill payment. Standardization in headings and terminology is going to play a key role in many OCR applications to ensure that the data being read is categorized properly.
It’s critical, for example, that if OCR software thinks it’s reading a past due amount that it is correct in that conclusion. In the bigger picture however, those hurdles should be relatively easy to overcome and the need to enter a lot of data by hand reduced, if not eliminated.
Edited by Maurice Nagle
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