The Importance of Data Quality in Financial Reporting

Data quality has always been at the heart of financial reporting, but with rampant growth in data volumes, more complex reporting requirements and increasingly diverse data sources, there is a palpable sense that some data, may be eluding everyday data governance and control. FSN’s recent research, “Agility in Financial Reporting and Consolidation,” finds a surprisingly high level of data errors in the record-to-report (R2R) process, which affects the agility of reporting, contributes to the bunching of activity around the period end (“Month-End Mountain”) and, in some cases, presents a significant risk of material misstatements in reporting. Clearly, if data errors are left unchecked, it can have serious consequences.

FSN: Agility in Financial Reporting & Consolidation

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In a fast-changing environment in which reporting agility is crucial, 72% finance functions say that their reporting agility is affected or greatly affected by data errors and 60% say that these errors give rise to the risk of material misstatement. Finally, data errors contribute significantly to the month-end peak suffered by 60% of organizations in the survey. So where do these data errors arise?

Errors are typically introduced in the early stages of the reporting cycle. FSN’s study points to two major causes, namely, closing the books in reporting entities and data capture from these business units as month-end “actuals” are harvested for inclusion in the group (corporate) reporting pack. An over-reliance on manual data entry into spreadsheet templates, used by around 40% of all organizations, is a major cause of error. One reason is that the degree of validation and “reasonableness” checks that can be built into disconnected spreadsheets is severely limited and, to the extent that financial controls exist, they are largely manual.

Interfaces between operational systems (usually the general ledger) and the group reporting pack are frequently unautomated and depend on crude mapping tables, also maintained in spreadsheets, to marshal source data to its proper destination. So, there are plenty of opportunities for errors to creep into the financial reporting process.

Despite the foregoing difficulties, data quality management is frequently neglected by finance functions. FSN’s research indicates that almost double the attention goes into improving reporting at the end of the process rather than data capture and controls at the beginning. (81% of organizations focus on improving financial reporting with just 48% on data capture and 46% on controls). The irony is of course that data errors severely undermine the integrity and trustworthiness of reporting. Put bluntly, there is little point investing in improving reporting while data errors flow through the process unchecked.

Although the FSN study cannot pinpoint the exact percentage contribution that data errors make to the month-end mountain, any errors that are not trapped when and where they occur, lead to significant bunching of activities and delays at the corporate center every period-end. In fact, the research finds that the reporting process is slower and less agile than the roughly comparable process of planning, budgeting, and forecasting. Evidently, an inconvenient knock-on effect of data errors in financial reporting is that they have the potential to slow down broader performance reporting as well.

Taken as a whole, the lack of data quality has a profound impact on the efficiency and dependability of the entire record to report process. Organizations that neglect data quality management, leave themselves vulnerable to serious misstatement and reporting delays.

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