Large organizations deal with thousands of customers. Each customer is unique ? they run different ERPs, different accounts payable systems, and varying methods for providing remittance and payment. Many organizations consider such differences, especially when it comes to remittance, to make automating cash applications inherently difficult, time-consuming, and expensive.

? it is important to note that capturing the data is only the first step towards achieving real automation. ?

As discussed in earlier chapters, customers tend to send remittance information in various formats ? checks in form of check stubs, via e-mail, hosted on web portals, or via EDI. The latest technologies can capture data from all of the above formats and convert them into electronic format to be processed further. However, it is important to note that capturing the data is only the first step towards achieving real automation. Once the data is extracted, it is necessary to cleanse it so that it is easily recognizable by your accounting system and all the invoices are automatically matched and cleared without the analyst having to perform any manual activities. The formatting and cleansing of data can be done using a sequence of rules which transform the extracted raw data into a format that matches open invoices and can be automatically processed by the ERP. These rules would cover the full processing of the remittance and payment ?from identifying the right invoices paid so that cash application does not require human intervention for coding deductions and short payments so that disputes can be processed faster. A successful cash application automation system typically needs 100 to 500 configured rules to ensure a high degree of automation, depending on the number of payers and the format and information provided with the remittance. There are several different categories of rules that modern systems must support. Invoice identification rules help with matching a paid amount to an exact open invoice in cases where a different invoice number is provided or a PO number is provided instead of an invoice number. Deduction coding rules can help with the creation of dispute cases and providing reason code information to speed up a dispute resolution. Discount related rules can validate applicable discounts taken on a payment. Depending on the nature of the problem and the degree of automation required, different rules can be applied to quickly perform the manual tasks of translating the remittance information into formats that can be used to close invoices. A common problem that automation rules are effective at solving is the presence of no-remittance payments, where customers pay without providing the supporting documentation. Automation rules enable a solution to this problem by applying cash to open invoices in a predictive, deterministic way, much like a human analyst would. It is possible to configure rules to do different things, depending on the customer. Some examples seen are ?oldest open invoice first,? ?amount match,? etc. In general, these are rules that the cash application team already follows. It is simply a matter of allowing an analyst to configure the rules in the system, instead of them having to apply the rules manually each time. Automation rules are critical in removing the dependence on human intervention and achieving a high degree of automation. Rules not only enable matching of payment to invoices based on remittance processing and data cleansing, but also the processing of payments without remittance with a high degree of accuracy. This technology is fundamental to achieving a high automation rate.