In the past decade, the role of CFOs has expanded beyond heading the finance team to being a strategic catalyst for the company’s growth. To present the C-suite with strategic recommendations, CFOs require accurate and real-time financial data.

Unfortunately, this isn’t a luxury many can afford. Without a ‘single source of truth,’ companies will struggle to measure their KPIs and make informed predictions. So, on top of their new responsibilities, they must bear the burden of presenting a definitive view of the business that leadership trusts.

How did we get here?

CFOs have taken up responsibilities that belonged to COOs and CEOs, including:

· Researching new partnerships and opportunities

· Finding talent

· Providing timely data to drive company decisions

This has increased the number of roles that report to the CFO office. According to McKinsey, the growth in roles reporting to CFOs between 2018 and 2021 was as follows:

· 7% in cyber security

· 10% in digital

· 10% in M&A transactions

· 14% in investor relations

· 16% in procurement

Despite this increase in influence and duties, current solutions do not fully address the need to quickly create reliable data for small, mid and large-sized companies. But why not get new tech talent to help with the data reconciliation? While it’s an option, it still doesn’t solve the challenges of data reconciliation. Plus, CFOs prefer to have their teams focus on forecasting instead of getting bogged down in the complexities of data reconciliation.

Challenges of data reconciliation

Data reconciliation is similar to reconciling credit card statements and your budget, only on a larger scale. Corporate finance teams compare thousands, if not millions, of transactions to ensure they are complete and accurate. This process helps detect errors, fraud, discrepancies, and opportunities for growth. However, the conventional data reconciliation process is marred with challenges, including:

Data fragmentation

Most companies’ data lives in disparate applications, platforms, spreadsheets, and databases, and is often “owned” by different departments in the business. This siloed nature of data affects the finance team’s ability to keep a single source of truth, which means they often spend time reconciling reporting from overlapping systems.

To overcome this challenge, CFOs need to centralize their data repositories, create data governance structures, and allow for collaboration among different stakeholders.

Diverse data formats

Because data is pulled from different sources, the team is faced with the challenge of working with diverse data standards, protocols, and formats. This adds to the complexity of reconciling and standardizing data.

Regulatory and compliance requirements

CFOs must ensure that their financial data adheres to various regulatory standards such as GAAP and IFRS. Since these regulations are ever-changing, teams have to monitor them continuously and adapt. This process becomes even more complicated when a company operates in multiple jurisdictions, each with its own set of regulations.

Manual processes and human error

Despite tech advancements in the finance space, many organizations still rely on manual processes for data reconciliation. This dependence on manual entry is time-consuming and increases the chances of human error, leading to significant financial discrepancies, distortions, and erroneous conclusions and decisions.

For many CFOs, the inefficiencies of manual data entry are a significant bottleneck in financial reporting, with teams spending up to two weeks correcting errors from the past month.

Custom in-house reconciliation tools

Some CFOs have considered hiring dedicated data engineers to solve data reconciliation challenges. On paper, this expert seems to have the skills to fix all these data reconciliation issues. But many companies don’t have comprehensive data infrastructure, so they are doomed from the start unless they build an in-house data reconciliation tool.

While it’s a workable solution, building a custom tool can be extremely expensive and complex to develop and maintain. The company needs to allocate resources to hire more specialized technical staff who have the expertise to design, develop, and maintain these systems. Moreover, the complexity of integrating these tools with existing systems adds another layer of difficulty to the reconciliation process.

As a result, it’s difficult for CFOs to justify such an investment, especially when the return on investment isn’t realized immediately.

Limited insights

Despite being expensive, custom-built reconciliation solutions often present limited insights, making it difficult for non-technical users to access and derive meaningful data. These solutions are usually designed with a focus on functionality, not usability.

Automate data reconciliation

Data reconciliation presents technological, organizational, and regulatory complexities that CFOs must navigate to ensure the accuracy and reliability of their financial data. While custom in-house solutions and BI tools are feasible solutions, they have their fair share of challenges. They are largely inadequate in solving the problem of unreliable and inaccurate data.

The best approach is to incorporate a comprehensive solution that integrates advanced technology, improves data governance, and ensures compliance with regulatory standards. This is where Preql comes into play. Preql provides a robust platform that automates the reconciliation process, integrates seamlessly with existing systems, and provides secure, accurate, and compliant financial data in real time. By leveraging our system’s capabilities, CFOs can improve the efficiency of their team without burning them out.

To learn more about how Preql can transform your data reconciliation process, request a demo or contact us for more information.

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