Before establishing how to automate it, let's define reconciliation (more colloquially known as recs).
Reconciliation describes the process of matching transactions to a general ledger. Balance sheet reconciliation, in particular, is how sub-ledgers (or accounts) are matched to a general ledger or balance sheet.
Reconciliation is an essential component in financial reporting. By verifying that all transactions (such as the accounts payable, accounts receivable, deferred accounts, etc.) have been correctly recorded in the company’s books, finance departments and shareholders can be confident in the figures. They can then make business decisions guided by a precise and accurate understanding of the company’s financial position.
At its core, reconciliation involves comparing two sets of data. As a repetitive yet detail-orientated process, it is ripe for automation. In 2024, we’ve seen the advent of several sophisticated automated balance reconciliation software tools. But why should companies consider automation to close their books?
As we’ve written about extensively, (AI-led) automation is designed to auto-complete repetitive processes that otherwise slow down professionals. Manually completing reconciliation is traditionally completed via Excel. It can take hours. In comparison, automation takes mere seconds.
In fact, 97% of finance professionals agree that automating reconciliation is important for business. Continuous, end-to-end reconciliation saves businesses time and money in several key areas, including:
Instead of manually tracking the status of data via phone calls or emails, automated reconciliation automatically monitors which transactions have been uploaded and reconciled. For global firms, the increased transparency (while maintaining proper permissions) can make it easier for international staff to access key data.
Manual errors can cost businesses – big time. An oft-reported statistic from a 2021 Gartner study claims that bad data costs businesses across all industries $12.9 million annually. For finance professionals, in particular, a survey by data engineering platform dbt earlier this year reveals that poor data quality was the biggest obstacle for data professionals when preparing data for analysis.
By automatically preventing costly errors, organisations can free up time previously spent on manual checks and corrections, boosting productivity.
An interesting benchmarking study by PwC shows that 42% of Financial Planning and Analysis (FP&A) activities in 2023 focused on collection, reconciliation and distribution – instead of strategic analysis and presentation. Surprisingly, that figure was up from 25% in 2019. Potential causes for this increase in basic data preparation tasks could be the result of companies choosing to focus on addressing backlogs, particularly resulting from the recent surge in data volume.
Either way, it is the responsibility of firms to ensure their staff have the tools they need to focus on the most productive activities. Effective automated reconciliation tools can deliver a high return on investment (ROI) – but how?
While automated reconciliation delivers undeniable benefits on paper, it’s essential to understand how it is more than the sum of its parts. Rather than automating reconciliation through common financial tools like Excel, specialised tools – such as balance sheet reconciliation software – offer a safer, more efficient service. The main problems with Excel are that:
With all its shortcomings, automated reconciliation through Excel may might be a frustrating experience.
A method that many finance professionals use when completing recs is using Excel’s Power Query tool. This tool compares the variance between two lists (immediately) indicating cells with non-continuous data.
Though Power Query can automate a significant part of the reconciliation process – the comparison – it is not an end-to-end process. The user must still create and merge the lists before manually correcting any errors.
Automated reconciliation isn’t about eliminating Excel; it’s about guiding manual labour away from the granular comparison of figures. Newer tools centre around Excel, automating the process of structuring and comparing lists of transactions.
Specialised tools for automated reconciliation will contain features to preserve the safety and accuracy of financial data. Examples of these features include:
Role-Based Access Control (RBAC) ensures system users have the correct permissions for their roles. This might be as straightforward (for reconciliation tools) as assigning roles (e.g. admin or user) or restricting access to non-relevant projects. Audit trails and activity tracking can also support the effectiveness of these controls. In addition to robust RBAC, multilayered security can prevent unauthorised and potentially fraudulent transaction changes.
Maintaining security over financial data matters more than any certification. Instead, it means that the automated reconciliation tool:
When robust security meets strong functionality, the result is an industry-leading automated reconciliation tool.
Balance sheet reconciliation software compares the information in a balance sheet with other sources, such as customer accounts, bank statements and more. The software extracts the information from balance sheets and then uses a matching engine to verify the data’s fidelity. It will flag any inconsistencies for manual review. The reconciliation process may then be summarised into a report.
Of course, there are alternatives to end-to-end specialised balance sheet software for companies looking for more autonomy over their data. Tools that can assist in automating the reconciliation process might include:
Of course, any tool assisting reconciliation might generate inaccurate data under certain circumstances – if poorly integrated or if accounting standards change.
Though automation offers a high ROI if integrated correctly, it’s essential to anticipate the limitations of automated reconciliation tools. Let’s address three common concerns associated with operating automated reconciliation technology.
Interoperability refers to the ability of systems and apps to communicate (with one another). Interoperable systems can smoothly transmit data without any effort on the user’s part.
However, synchronising data presents issues for firms with multiple financial systems. For example, you might want to connect an automated reconciliation system with other financial reporting systems, general ledgers, etc. If not, you could end up manually shuttling data, spending more time transferring and preparing data than you would without an automated system in the first place.
If using an external vendor for automated reconciliation, you must address any integration issues proactively. Ask a vendor about their prior implementations and the challenges they’ve overcome.
How would you prefer the automated reconciliation system to respond if the inputted data is inaccurate?
Ideally, the system should automatically correct errors. For instance, the system could identify and correct the error if a transaction is posted to the wrong account. The next best option is for the system to flag them for manual review. The automated reconciliation software should log all errors for reference and future improvements.
Though it is only a potential limitation, changes in accounting standards (e.g. Accounting Standards Codification (ASC) 606) might cause rigidly calibrated automated reconciliation systems to fail.
Ideally, the reconciliation tool possesses the flexibility to adapt to the user’s requirements. Advancements in AI and machine learning will likely lead to automated reconciliation software with greater customisation capabilities, such as allowing for more precise matching rules.
The future of automated reconciliation software isn’t defined. However, a few avenues promise advancements in this software’s current capabilities.
An article by CFO suggests a high-quality matching machine could be trained to conduct automated reconciliation in real time. They dubbed real-time reconciliation the future of automated reconciliation – and we agree.
Other advantages of immediately accessing data include:
Auditors can access financial data anytime, providing timely snapshots of a company’s financial health.
Automated reconciliation data is fed into a central database, providing all company employees a ‘single source of truth’.
Establishing a real-time flow of data is not easy to develop and integrate. However, in the future, we might see real-time reconciliation become commonplace across firms of all sizes in financial services.
Blockchain has recently been making waves in fintech circles. Blockchain is a distributed ledger system that provides secure and verifiable record-keeping. It is transparent and immutable.
Ultimately, its potential to automate reconciliation processes through invoice-matching ledgers is promising. One key consideration is how to integrate blockchain technology with current technologies. As GoCardless notes, the uptake of such technology is likely to be slow (yet promising).
Auditors and financial performance consultants may need to confirm that financial statements or annual report data align with the accounting system data. The reconciliation process can ensure the analysis is based on accurate and verified numbers.
Extracting the data from financial statements is the first step. That’s why we developed Financial Statements AI – our tool for extracting data and insights from balance sheets. It’s accurate, user-friendly and ready to try.
Find out how to get involved with Financial Statements AI here.
