The automation of reconciliations offers numerous advantages in accounting. Booking errors are a thing of the past, as is the tedious search for differences. We take a look at the ultimate resource in the form of a reconciliation tool that significantly simplifies accounting.
Transformation of financial processes = automation of these very processes
The digital transformation of financial processes describes their automation through advanced software technology. The aim of the transformation of financial processes usually focuses on the reduction of manual tasks.
The focus is also on converting and synchronizing data and improving collaboration. Above all, time-consuming, monotonous, error-prone, and "dangerous" work, in general, should be eliminated through increased automation. Automation can take over tasks that are particularly time-consuming and very monotonous for humans.
There are no really "dangerous" tasks in financial technology, however, not all people working in accounting see it that way. The search for differences as well as the reconciliation of payments corresponds to a time-consuming, but above all monotonous job, which then becomes "dangerous" when careless mistakes creep in. Ultimately, the figures must be right, which is not always easy to achieve.
The multiple stages of reconciliation
The process of the automation of data reconciliation has typically been achieved through several stages. The objective is to eliminate the time-consuming and highly error-prone manual reconciliation process. To achieve this, the first step is usually to compare the account balances in Excel. However, this is a rather basic approach for accounts and only works when there are only a few movements.
Differences in the balances can only be identified with this method if individual items are examined more closely. If the causes cannot be uncovered, higher write-offs are imminent, or higher tolerances for deviations must be accepted. This is not the aim of sophisticated reconciliation.
Experts in reconciliation are usually experienced Excel users. They have developed their own tools based on spreadsheets. The second level of automation is complex spreadsheets and macros. Here, the matching data can be improved slightly. The maintenance is however very time-consuming, just like the creation of the tools themselves. In addition, several people cannot work on the tools at the same time. Errors can hardly be tracked. The same applies to the verification of changes. It can therefore be concluded that spreadsheets are not suitable for sophisticated reconciliation. They are the first solution, but delays, mistakes, and crashes have to be accepted. Corrections to data errors must also be carried out manually.
At the third level of automation, the limits of general spreadsheets are exceeded, and more sophisticated data reconciliation technology is introduced. The limit is reached as soon as the complexity of the data and its volume can no longer be handled with additional staff and the compromises in the speed and accuracy of the reconciliations have a negative impact on financial results.
Specialised reconciliation solutions for more efficient automation
A specialized account reconciliation solution removes the barriers to automation. The introduction of such a solution is not possible overnight and typically takes place in three stages. These are based on the increasing complexity of the reconciliation solution. We present the individual stages of automation in more detail below, using our reconciliation solution ReconHub as an example.
Stage 1
In this stage, the reconciliation scenarios are kept quite simple. The formats of the input files do not change much and can be easily linked during import.
The data is not only accessed through a standard API but is also checked for completeness. This data analysis ensures a high level of quality and prevents data from being imported twice, for example.
This level is interesting in terms of performance, as many of the reconciliations cannot be implemented with Excel. A matching logic is used to reconcile the transactions in this case. Adjustments are made based on several parameters. Tolerances for deviations can be adjusted, with exceptions already governed by clearly defined rules.
In this stage, the focus is on automating the matching process. Users define the algorithm for comparing records with ReconHub. An unlimited number of comparison criteria are determined according to priority and scope. A matching pair can thus be narrowed down precisely. In the process, the intelligent system calculates in the background and indicates which combinations lead to the best results. If no automatic matching takes place, ReconHub suggests transaction pairs that most closely match the criteria. The user can confirm these and save them as a matching rule for the next time. The user does not have to act on these suggestions.
Stage 2
The automated processes are expanded further. The input data streams have intensified so that an automatic import can be planned appropriately. Reconciliation itself can be integrated into tasks, just like reporting and exporting data. By monitoring the input data and patterns of mismatches, the system can be tested for further optimization. The number of manual interventions is reduced.
The collection of numerous matching data from different sources is common and costly. It often involves hundreds of pieces of data that need to be compiled into a consistent format. With ReconHub, the one-time set-up of import templates facilitates this process by eliminating this effort. The platform can fetch all the files after fixed time intervals or they can be received through another means, E.g. push/pull. This way, the reconciliation of all data can be simplified.
The possibility of automatic scheduling makes it possible to execute all tasks on time. It does not matter whether it is an import, export, or reconciliation. Interruptions can be avoided through precise planning. A fixed rhythm is maintained, which is important for the regular reconciliation of all data. Users can set various checkpoints in the system to monitor progress and identify bottlenecks. All tasks can be arranged in logical groups where sequences can be observed to ensure a smooth flow.
User-created rules are particularly important in ReconHub. Manual operations can be transformed into system tasks that no longer need to be carried out manually. Besides the matching itself, this stage includes the conversion and enrichment of data. Furthermore, exceptions can be visually marked to make them easy to identify.
To create rules, users do not need to understand code and do not need to be able to program. Rather, it is a language similar to Excel that is easily adopted by users who are not in IT. Programming expertise is therefore not required to personalize the system. Users themselves determine how much the voting rules are customized. This approach is based on the needs as well as the necessity with which certain rules are to be set up.
Stage 3
At this level, complete automation of all coordination processes is available. All processes between different systems can be fully integrated. This includes reconciliations and exports as well as file transfers, to name just a few options. All processes are controlled from one place. As soon as one process is completed, the next one is triggered. This reduces further delays in processing.
For the financial close, workflow automation is critical. Strict time management as well as near real-time progress tracking are critical to reconciling all data. This is especially the case in large organizations that include balance sheets with hundreds of accounts.
Reconciliation and certification of accounts are only possible through full automation with precise timing. With ReconHub, you are able to implement these steps effortlessly. For the implementation, only timeframes and data feeds need to be recorded by the intelligent set of rules. The platform can then successfully take over the task of automatic reconciliation.
New possibilities with an individually configurable platform
It is true that the dream of many people is that after a voice command, an AI executes all commands. In the process, all scenarios, variables, and probabilities that can occur are considered. Automation is not quite there yet, although the future will certainly take such a path. For now, the key is to perform account reconciliations securely, reliably, and as time- and cost-efficiently as possible.
With ReconHub, Abrantix offers a platform that is configured individually by users. Processes can be replicated in the digital space, making digitization easier. By using our solution, the level of automation can be continuously optimized.
Users benefit from automation whilst retaining control over the design of all processes, delivering an automatic turnover reconciliation that no longer causes headaches. We offer customizable solutions for any financial accounting as well as for any size of the company.
