Author: Hristo Marintchev
The reconciliation lifecycle
An earlier article defined the enterprise reconciliation lifecycle as encompassing four primary stages: data import and enrichment, matching, exception management, and finally reconciliation. Below we seek to address the main attributes of the first of these – import and enrichment – to ensure a coordinated approach to an effective enterprise-wide reconciliation strategy.
What exactly is being imported?
Before this can be answered, the first question to ask is "What needs to be reconciled and why?" Within most operations there are two distinct groups of data that require periodic reconciliation. The frequency of when this takes place depends on many factors, not least the level of risk to the business of not identifying problem areas – errors, fraud, missing data to name a few – as they arise.
Category 1 typically encompasses transactional based data, nowadays often matched daily. Examples include bank and other cash accounts, trades (buys and sells), and positions where inventories are managed. Typically the data requiring comparison, and therefore prior import into a matching engine, comes from both an internal source such as a cashbook in the general ledger, and an external source such as an electronic statement from the bank.
Category 2 represents general ledger accounts that require review and verification for accuracy. The reconciliation of these is done less frequently – monthly, maybe quarterly, possibly even only annually if the risk level is deemed low. More often than not the sources of data are internal only and represent balances possibly with supporting transactions to explain changes from one period to the next.
Naturally, there are other types of data comparison that also take place within most organizations, either on a recurring or one-off basis. Regardless, the process remains similar: data is collected, imported into a database, where it adds value cleansed and enriched prior to the application of match rules.
Why enrich the data?
Simply, to ensure the highest automated match rate without compromising the quality of the overall reconciliation. Remember: the three principal benefits of an effective reconciliation strategy are to reduce operational costs, mitigate risk, and enhance and ensure compliance. By enriching the data as it gets imported one addresses the first two by increasing the level of automation (reduced costs) and speeding up the identification of errors (reduced risk).
Enrichment takes many forms. It could be adding to or substituting data so that it is consistent across the data files being imported, for instance normalizing securities codes used for the matching of positions and trades in the investments industry. Or it could simply be adding the name of a general ledger account from yet another source so that users verifying balance sheet accounts at quarter end have a clear view of what they are looking at. Often look-up tables are defined and maintained automatically to achieve this, themselves also requiring the import of referential data.
The benefits of effective data import and enrichment
There is little point in implementing an enterprise-wide approach to reconciliation – be it transactional or period end balance based – if it does not deliver positive results. As with so many things in life, getting it right early on ensures less cost and pain downstream. Investing the time and effort to get the import phase right – and review the quality of resultant match rates – ensures a smooth start to the reconciliation lifecycle to deliver improved compliance, lower costs and reduced operational risk.
Article Source: http://www.articlesbase.com/accounting-articles/the-enterprise-reconciliation-lifecycle-4077390.html
About the Author
Hristo Marintchev of ReconArt, an transaction reconciliation software solution, is pleased to offer information relating to the enterprise reconciliation process. Visit ReconArt.com today.
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