About the Author
Andy Botrill is BlackLine's Vice President EMEA.
Trust: firm belief in the trustworthiness, strength, truth, or ability of someone, or something. By this definition, trust in business may have recently weakened, particularly with regard to the integrity of financial data.
Indeed, in the UK, a series of major corporate collapses caused by mismanagement, followed by three major audit sector overhauls, have made financial services the most unreliable sector in the country.
Not surprisingly, restoring trust has become a priority for CFOs, and a good place to start is to improve internal trust. How do you do it With the number one engine of finance: data.
Financial data is the key
Since companies rely on financial data to make many important decisions, trust in the numbers is the first step in restoring trust. A recent BlackLine survey found that nearly 70% of business executives and financial professionals around the world felt their organization was making a major management decision based on inaccurate financial data. while more than half are not entirely sure that they can identify financial errors before reporting the results
By exploiting low-quality data, you risk becoming the next front-page scandal and damaging your reputation, but you can also seriously slow down your organization's efforts to transform in the long run.
As the risks associated with misrepresentations get better and better, finance professionals are willing to see more liability in the industry. So how can you be sure that the decisions made based on your data are the right ones?
Build trust in numbers
To establish real trust in data, the first crucial step is to ensure the reliability and accuracy of financial information. More than a quarter (26%) of finance executives are concerned about financial errors that they know exist but to which they have no visibility. With trust on the line, efforts need to focus on addressing the blind spots and invisible bugs that undermine confidence in the numbers.
Cloud-based, real-time process automation is at the center of these efforts. By automating time-consuming manual processes such as transaction mapping or journal entry, data not only becomes more reliable, but users can also spend more time on consulting and analysis tasks; in turn, adding more value to the business.
Continuous accounting, for example, which combines modern financial strategies with cloud technology, can put an end to high margins of error and provide faster analysis and greater operational efficiency. With real-time updates, consistent reporting, and numerous controls to strengthen accountability, departments are beginning to take advantage of improved data integrity and a stronger culture of trust.
Transparency: the key to accountability
As technologies like artificial intelligence (AI), machine learning, and robotic process automation (RPA) contribute more to the decision-making process, transparency becomes critical. Full transparency is not only essential for effective decision-making, but will also be an important factor in achieving "explicit" and "ethical" AI.
While finance professionals still hope to be responsible for book certification, they are increasingly opposed to decisions made by machine learning algorithms. Therefore, it has never been more important to understand why recommendations are made or how decisions are made. If not, how can you trust the validity of the result for which you are responsible?
The need for transparency will only grow as technology becomes more involved in financial decisions. For example, if an algorithm rejects a loan application based on factors like zip code, it may inadvertently mimic the bias we see in human decision making. However, understanding how the decision is made would allow a person to scrutinize or challenge it, helping to determine the correct but also ethical plan of action.
long term financing
Although a truly intelligent technology like AI is not a reality for finance, it will certainly start to fill more and more tasks and roles within the industry as it grows. Future Evolution For now, finance automation enables broader business decisions based on the most accurate and up-to-date information available.
Not only does this help build a culture of trust within the finance department, but the shift towards internal integrity will play a central role in building trust in the business as a whole, be it with customers, its shareholders or the public. .
In the end, using automation to improve the accuracy and reliability of your company's data will pay dividends down the road. After all, what will intelligent AI do if it learns from inaccurate and inaccurate data sets? And most importantly, who would call the shots or recommendations you make? The bottom line is that data-driven businesses simply won't succeed without laying the foundation for integrity and trust.
Andy Botrill is BlackLine's Vice President EMEA.