A bank reconciliation is the process of comparing the bank account records of a company to the company's internal financial records to ensure that the two sets of records agree and to identify any discrepancies. Generally, the process involves comparing bank statements, such as monthly bank statements, to the internal records of the company. Accountants use various tools to perform bank reconciliations, such as spreadsheets and accounting software. The data typically included in a bank reconciliation includes deposits made, checks written, and other transactions that have occurred in the period being reconciled.
Cascade streamlines the process of comparing bank statements and internal financial records, ensuring that the two sets of data match up. Its user-friendly interface makes it easy to spot discrepancies and reconcile accounts. Additionally, Cascade provides comprehensive analytics to help users to delve deeper into the data to uncover issues and spot patterns. The bank reconciliation process is made effortless with Cascade, making it the perfect tool for any business.
A customer, an independent accountant, had been feeling the strain of manually performing bank reconciliations every month. Despite having the technical skills necessary to complete this task, the use of generic spreadsheets was proving to be inefficient and time-consuming. After researching various data analytics tools, they decided to give Cascade, a no-code, automated, drag and drop data analytics tool a try. With its intuitive and user-friendly features, our client was able to quickly set up automated bank reconciliations, saving invaluable time and money. With Cascade, our client was able to optimize their workflow and focus on more complex tasks.
Explore the use case below.
The data featured in this workflow includes a January bank statement and corresponding extract from a companies general ledger. One of the major challenges with this data was the format that it is shared with the individual performing the bank reconciliation. The data is comma delimited, but when opened in Excel or Google Sheets, the data is retained in a single column.
The use of the Text to Columns tool in the Cascade tool suite allows for effortless parsing of the data into separate fields. Specifically, the Text to Columns tool does not require the user to specify the number of columns to expect to be parsed. Therefore, it is an ideal solution in generic data sets that might have a different number of columns in the dataset.
The preparer was also able to standardize the data schema, rename columns, and remove blank records with tools from the Cascade Clean tool group.
When dealing with hundreds of transactions and records from disparate data sources, it is often difficult to find anomalies such as incorrect dates, incorrect values, and empty records. Cascade allows users to easily isolate these data anomalies so that the preparer can make corrections either in the source, or request amended reports from data suppliers. A bad output is the result of bad inputs. Therefore, it is vital for preparers to easily isolate anomalies and mistakes in the data, even when there are hundreds of records in the data source.
In this bank reconciliation use case, the preparer used Filter tools to isolate records with empty dates. After these records were separated from the data, the accountant can easily review whether there are further actions that need to be taken or whether the discrepancies are acceptable.
When performing the bank reconciliation, the preparer was adamant about making sure that transactions and general ledger entries were recorded on the same date. This is often challenging in generic spreadsheets that might hide timestamps. The preparer used the DATENORMALIZE() function in Cascade to first confirm that dates across all data sources were consistent and standardized. Afterwards, the preparer was able to quickly use a Join tool to combine the two data sources. As a result, there were records from both the bank statement and general ledger that did not have corresponding transactions on the same date from the other data source. The Join tool allows the preparer to easily pinpoint these differences in the data and make the necessary adjustments that they need to make in the general ledger.
Reduce, reuse, recycle
The best part of building a workflow in Cascade is its reusable functionality. Month after month, the preparer simply has to confirm the refreshed data source and either run the workflow, or schedule the workflow run if they are confident that the data will be ready for their analysis by the time of the execution. As well, the preparer is now exploring using Cascade Webhooks feature to automate the process of executing the workflow upon receiving refreshed data from their client. Next steps include scheduling the workflow from a monthly report to a daily report or an event report - executed every time the workflow’s Webhook is triggered.
Many of us are turning to no code, data analytics, drag and drop products like Cascade to streamline our bank reconciliations. Cascade makes the entire process of reconciling the bank statement and general ledger much easier. All you have to do is to upload the data, drag and drop the relevant items and the reconciliation is done in a flash. Plus, Cascade also allows you to quickly identify discrepancies in transactions and make the necessary corrections. If you're looking for a simpler and more efficient way to reconcile bank statements and general ledgers, then Cascade is the perfect solution.