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How automation can eliminate financial errors

FYI, this story is more than a year old

A survey of 102 Australian C-suite executives and finance professionals in companies with more than $20 million in revenue commissioned by BlackLine has revealed that nearly half (46%) of respondents are not completely confident they can identify financial errors before reporting results.

The research found not only is there evidence of a disconnect between C-suite respondents and finance professionals when it comes to confidence in the accuracy of financial data, but a high eight in 10 respondents believe their organisation has made significant business decisions based on inaccurate data. 

Many identified this as a hidden problem, with nearly one third (32%) stating concern over errors that they know must exist, but of which they have no visibility. 

The BlackLine survey results show an acknowledgement that inaccurate financial data has negative implications both externally and internally, yet also shows that many organisations continue to be challenged by human error, ever-increasing volume of data sources, as well as outdated technology.

The recent Banking Royal Commission in Australia has recommended criminal charges for financial firms that fall short with their reporting, highlighting the importance of having accurate financial data wherever possible.

BlackLine A/NZ VP Claudia Pirko says, “Australian companies can no longer operate with uncertain financial data. 

“Increasing regulatory oversight is set to arise from the Banking Royal Commission recommendations and more financial transactions, from superannuation payments to mobile commerce, are happening in real time which suggests the need for real-time data accuracy.”

Misplaced C-suite trust in the numbers

Although over half (57%) of total respondents still claim to completely trust the accuracy of their own financial data in general, there is a significant discrepancy between the views of the C-suite and that of finance professionals.

While 81% of C-suite respondents claimed to completely trust the accuracy of their financial data, only 32% of finance professionals said the same.

Many organisations are betting their business on inaccurate financial data

A high nine in 10 (92%) CEO respondents think that either they themselves or their CEO has made a significant business decision based on out-of-date or incorrect financial data. 71% cite that this has definitely occurred in their organisation.

Low confidence levels in the ability to spot errors to ensure accurate reporting

About three quarters (77%) of respondents said that a company they’ve worked for had to restate their earnings due to inaccuracies in financial data that weren’t identified prior to close.

Only 17% of respondents agreed that they could trust that their finance team/CFO had identified all errors to ensure they are reporting accurately.

Respondents cited human error (29%), multiple data sources (36%) and a lack of automated controls (39%), as well as clunky technology (27%), as contributing factors to their lack of trust.

Counting the cost of hidden inaccuracies

Nearly all (94%) C-level respondents agreed that if inaccuracies in financial data were not identified prior to reporting, the impact would be negative.

These negative impacts included significant reputational damage (36%), an impact on their ability to secure additional investment (35%), and increasing debt levels (43%), with more than a quarter (26%) fearing fines and jail time.

Many large organisations are constantly having to fix financial errors in their accounts – in almost one in five (19%) of cases, C-suite respondents said it takes up to 10 days per month for their organisation to identify errors and make adjustments, potentially wasting as many as 114 days each year.

The implications of this are potentially severe. They include not only the financially negative impact of strategic decisions based on inaccurate numbers but also the repercussions of failing to comply in an ever-expanding regulatory global business environment.

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