ACL Analytics Reviews

We normally use ACL Analytics to automate what we call control testing across different business areas. We have several use cases for procurement which covers accounts payable. We are looking at payroll, employees sharing bank accounts or sharing last names, and all those different HR tests. We have a whole suite of approximately 56 bots testing for six controls. We use it for various business units and we have quite a lot of solutions.

With ACL Analytics alone it is a bit difficult, so we integrated it with a robots application that sits on the cloud. It helps us to control data extraction via our service accounts and automate all that process. In that way, we are able to run a task, and once it is completed, it deletes the data we have extracted from source, only keeping the exceptions that we have.

With ACL Analytics, you have an extension of writing scripts or commands, and what you can do with that is extend it to what they call the HighBond or Diligent robots. That Diligent bot uses Python. Now you are able to create a workflow based on what the result has been on ACL Analytics. For instance, when we have identified a user or a record that is a ghost employee, we need to send that record to business owners. The HighBond or the Diligent cloud bot kicks off the workflow where it triggers an automated notification to the business owner. Then the business owner can provide evidence on that record, and that record feeds back again onto HighBond, which has a storage area also for reporting. That information is stored back into our dataset, and then we are able to analyze it further.

The key feature of ACL Analytics is integration, which allows for vast amounts of data sources you can connect to. The tool itself allows you to integrate it into your audit work in terms of taking exceptions that you receive from your analytics. It provides integration into your GRC platform and into your audit working files, and then one key thing is the vast amounts of connectors.

We have seen a return on investment as we have mostly reduced working hours for the audit engagements. If an auditor was normally budgeted to take 600 hours, we have implemented a solution to take those audit hours down to 200 hours. We are mostly taking those metrics.

I use ACL Analytics for fraud detection in our banking system. We have robotic reports extracted from the system periodically. Every week, three reports are generated, providing us with a big picture to identify if any fraud has occurred.

ACL Analytics is a great application that helps me analyze data more effectively compared to other tools like Excel. It allows me to view extensive data and extract only the necessary columns for specific analytical missions. With over a million clients, this feature helps tremendously in identifying fraud detection in client accounts.

I work as an external auditor for a government agency. I use the tool for analytics.

We apply different methods, such as sampling, data manipulation, and sorting. I'm fond of the scripting feature, which automates routine tasks and saves time. It also offers data insights. 

The major benefit of ACL Analytics is its ability to save time. Tasks that used to take more than a week can now be completed in hours. Using scripts, we can run data and get the results.

The training programs were good. I found the training that came with the version I used in 2017 helpful, but the newer training was even better.

The most valuable feature of ACL Analytics is its powerful data control capabilities. Unlike Microsoft Excel or Crystal Reports, ACL Analytics enables me to efficiently execute and manipulate large volumes of data with just a few simple steps. This gives me a significant advantage in my work, making data analysis and audit processes much more efficient.

At the moment, I haven't encountered any significant issues with ACL Analytics because it seems quite robust and fully functional. However, in the future, to enhance the user experience, it would be beneficial if the software could improve its capabilities when extracting data from databases, particularly for those who may not be familiar with SQL queries. Predictive query suggestions could be a useful feature to make the process smoother and more user-friendly, helping users generate accurate queries without needing to memorize complex syntax or search for it online. Another area where ACL Analytics could improve is in handling Unicode characters and scripts. Currently, it restricts Unicode scripts to run on Unicode installations, which can be limiting. It would be beneficial if the software could allow unicode scripts on non-unicode installations and vice-versa without restrictions.

I use it for some matching that I try to do, and I use it for checking for duplicates. I do benefits analysis on it to look for outliers and things like that.

I'm pretty sure it's the most recent version that I have.

I like the fact that in the duplicate section, I can find matches, and I can find situations where certain cells or certain cell points match, but there's a difference as well between two different records.

I use the tool for duplicate payment searches. I analyze payments and select samples for testing. I combine different reports from various systems for subsequent analysis. It helped me uncover duplicate payments in the past. 

The tool's most valuable feature is its ability to import files from other software packages. Its reporting and visualization capabilities have made our reporting easier. Importing results into spreadsheets or other documents for incorporation into reports is particularly helpful.

For someone coming into it now, fresh out of the box, it will probably have a steep learning curve. When I started using it, I underwent some training, which helped.

The software's effective integration with other systems and data sources in our environment is notable. I find it pretty straightforward. I can easily download and import a report from a specific system.