A Financial Statement Data Consolidation process needs to be accurate and visible to all interested parties. At the end of this process, financial statements should be consolidated into “a single version of the truth”. The procedures performed to complete the process should be accurately documented and management should clearly see financial numbers by territory, cost center, department, etc. Finance departments have pressures of having to deliver accurate financial and regulatory reports challenged by a lengthy, or inefficient, close process with multiple manual steps and checkpoints. For these departments, collecting and verifying data is challenging from diverse locations and multiple general ledger, as is processing data consolidations such as minority interest, currency, multiple GAAP and regulatory reports. Also financial statements are delivered just in time, with little time available for analysis or review. The process is often a slow and error prone process that drains organizational resources and delays vital decisions.

These issues are particularly challenging for organizations where legislation such as the transparency directive, is driving the acceleration in reporting timeframes and demanding increased certification of final results. This puts enormous pressure on systems to support these requirements.

Data Semantics helps customers address the challenge of facilitating continuous performance improvement practices while efficiently meeting the demands of compliance and external reporting under for compliance with Sarbanes-Oxley, ICFR, and IFRS. We support organizations to produce reports under different regulatory guidelines, and provide a financial data consolidation foundation system to support additional management reporting while reducing the amount of time to perform a period end close and provide financial clarity. We also help with thorough documentation of procedures to ensure knowledge transfer within your company. Once this software is implemented to consolidate multiple entities and General Ledgers, data can be pushed to forecasting or budgeting models, which can then be used to enhance analytical reporting.

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