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Confused about data reconciliation and bank reconciliation? In this Conciliac blog post we offer you an analysis of the distinctions between these crucial financial processes. Plus, best practices and tips for effective reconciliations.

Table of Contents:

• What is data reconciliation?
• What is bank reconciliation?
• Data reconciliation and bank reconciliation: what is the difference?
• Data Reconciliation Best Practices for Businesses

We are here to address the subtle differences between data reconciliation and banking, which have their respective fields of application.

In both cases, the purpose is to compare sets of information to identify discrepancies, eliminate potential errors and make better decisions based on certainties.

But how do these exercises differ?

In what follows, we invite you to an examination of the distinctions between these processes, as well as a review of best practices and tips for effective reconciliations.

What is data reconciliation?

This comprehensive and all-encompassing process involves the comparison of data sets to identify discrepancies and achieve an efficient reconciliation through the so-called data match, whereby errors are eliminated in the course of the reconciliation process for one fundamental purpose: to ensure that the data are reliable so that the best decisions can be made on the basis of them.

In the course of reconciliation, errors are eliminated with a fundamental purpose: to ensure that the data matched are reliable so that the best decisions can be made based on them. Are good arbitrations possible with inaccurate data?

Data reconciliation is used for a variety of purposes and in many areas. The process is also used to recognize possible fraud, human error, duplication, suspicious activity, etc.

In short, it is a verification process that aims at the veracity of the information. In this exercise, the aim is to ensure that the data is consistent with each other, and that it reliably reflects movements in the real world.

As we will examine when reviewing data reconciliation best practices, automated systems maximize the benefit of these processes by bypassing manual reviews that suffer from a higher error rate. Automating tasks brings speed and efficiency.

What is bank reconciliation?

Bank reconciliation is one of the types of data reconciliation; one of the forms that these validation processes take.

Specifically, it is a useful procedure to know the state of finances, detect errors in accounting, and check the accuracy of the records in the operations.

As we explained earlier in this blog, bank reconciliation consists of contrasting the records of account transactions (available in the accounting books) with the movements recorded by the entities (in the bank statements issued). In this way, the necessary corrections are made.

It is important to keep in mind that the objective of bank reconciliations is not to achieve a full match between the balances recorded by a company and the statements. Instead, the primary purpose is to elucidate which variable caused the difference.

To more fully understand what a bank reconciliation is, let’s look at an example.

Let’s imagine that a startup bought a projector for presentations and paid $2,000 for the device. In the bank reconciliation for the month of purchase, the amount on the invoice issued by the vendor is compared to the movement in the company’s bank account to verify the match.

To graph this example comprehensively, it is important to consider that the process will also be applied to sales. This will help us understand the differences between data reconciliation and bank reconciliation. For example, if the same company offered a service for which it charges $30,000, at the time of reconciliation, the amounts invoiced and the income to the account must also match.

Data reconciliation and bank reconciliation: what is the difference?

So far we have seen what a data reconciliation is and what the process applied to bank accounts is all about. What is the difference between the two exercises?

We will explain it concretely as follows: every bank reconciliation is a data reconciliation; but not every data reconciliation is a bank reconciliation.

In this sense, we repeat: the bank reconciliation is one of the different types of reconciliation. Strictly speaking, there are different variants and applications of this procedure, for example the following.

• Of suppliers.
• Of Inventory.
• Of customer
• Of inputs, in different sectors and industries.
• Of credit cards.
• Etc.

The confusion between the two exercises (one of a general nature, the other more specific) is largely due to the great importance of accurate reconciliation of data in accounting. It is not trivial: the financial departments of companies manage crucial and sensitive information for the smooth running of the organization.

Therefore, it is possible that all reconciliations are considered to be bank and/or accounting reconciliations, when this validation procedure is also necessary in other areas.

Data Reconciliation Best Practices for Businesses

One of the keys for reconciliation to translate into good news for companies (from small and medium-sized to large companies) is to perform the exercise on a regular basis, narrowing the margins for error.

Then, to increase the periodicity of these exercises is to opt for automated reconciliation solutions. Among the advantages of doing so, the following stand out.

• Automated processes add agility and avoid obstacles that usually occur in manual exercises.
• Complexities are avoided: automation simplifies
• Automated processes make it possible to take real advantage of innovative technologies. In this way, activities in various business sectors are “riding the wave” of technological advances.
• Automated reconciliation software reduces the risks that may be committed by human agents, facilitating detection and solutions.
• It is an integrative procedure, relevant for companies operating in an increasingly digitalized world.
• We’ve said it before: with clear information, better decisions are made. Automation is the key to accurate data.

It should be noted that human specialists remain indispensable. The advantages of working with automated systems lead to better management of valuable resources, such as time and effort. The logic is obvious: by freeing themselves from mechanical and repetitive tasks, the members of a company can devote themselves to actions that are more closely linked to the core of the business.

If you are wondering how to streamline bank reconciliation with technology, or any of the variants of this process, another good practice is to take this path with the advice of specialists.

Solutions such as Conciliac EDM collaborate to make the validation process profitable, allowing your company to grow, with clear and easily accessible reports, from a centralized platform.