Complex instruments can’t be treated like bank accounts
We are all familiar with the standard type of reconciliation used by banks, or accounting software. It essentially compares two sets of data, or data files, and looks for differences. These ‘exceptions’ are then flagged so that the books can be balanced, or ‘zeroed’.
Reconciliation systems which are based on file comparison begin from the premise that each file is a complete set of the data that needs to be reconciled. One of the difficulties with this is that for many organisations such as FCMs, banks and brokers, data sources come from multiple counterparties but frequently need to be reconciled against a single data source, such as internal books and records, or a back-office system.
This is why using generic reconciliation tools to deal with complex instruments like Exchange Traded Derivatives, Futures or Options is so difficult and prone to inaccuracy.
In part this results from the nature and structure of the data itself, but other complexities arise from the fact that, for many reconciliations, values have to be calculated on a repeated basis from pre-existing positions and subsequently repriced as new data emerges. Rolling balances based on items like margin and OTE can’t be derived solely from the day’s files. They need to be held somewhere secure and audited – a role for which spreadsheets are entirely unsuited, yet frequently employed.
A purpose-designed reconciliation platform will absorb all of this data into a structured database and enable end-users to generate multiple types of reconciliation without the need to re-import separate data files. This means that reconciliations are based on a uniform set of reference data, the results securely stored and exceptions identified at a granular level.
Of course, while locating exceptions is crucial, it is just the beginning of a properly managed process. That’s a subject for a future blog.