Product releases Archives - MindBridge

Financial systems were not designed to operate continuously. They were built around cycles, checkpoints, and human review, but that model is breaking. As finance becomes more automated and execution accelerates, the controls designed to govern it are falling behind. What used to be reviewed periodically now unfolds continuously, creating a governance gap where oversight remains periodic, reactive, and sample-based.

New user experience

We’re proud to unveil a new, modern interface for Ai Auditor that has a stylish look and feel and brings enhanced accessibility with a WCAG 2.0-compliant color palette. To make navigation and access to functionality as easy as possible, we’ve updated the user interface (UI) to a new sidebar that offers a cleaner look and exposes controls that are in context and on demand.

Risk overview dashboard

This dashboard contains the key metrics to provide an overview of the risk areas. You can immediately identify notable entries and focus attention on those that pose a heightened risk of misstatement or error.

Ai Auditor uses a combination of rules-based, statistical, and artificial intelligence Control Points to analyze entries in sub-ledgers and put them into buckets: high risk, medium risk, and low risk.

Trending dashboard

This dashboard contains a summary view of the top outstanding vendors (AP) and customers (AR), including a comparison of all balances to previous periods to determine any significant or unusual changes. You can filter the page by ending balance or total activity.

In the table below, you can see which customers or vendors require attention by looking at the balances. Vendors or customers are ranked in order of the current year’s ending balance. Vendors or customers that didn’t exist in previous years will be marked as new.

You can see the change in dollar value between the prior and current year’s ending balance in the variance column and % change and % of total balance. To see what entries make up your current balance with each vendor or customer, you can drill down on the entry in the table to land on the Data table page which has the entries detail.

Aging dashboards contain metrics that help you to view each vendor/customer, the amount they are owed, and the amount of time they have been owed. Based on these dashboards, you are able to:

  1. Recreate the aged AP or AR reports to compare to reports provided by the client.
  2. Understand the historical distribution of AP or AR balances to identify anomalies.
  3. In the AP analysis, identify old invoices outstanding to understand potential cash flow issues or misstatements in vendor balances.
  4. In the AR analysis, identify outstanding invoices to determine appropriateness of allowance for doubtful accounts.

The Aging graph allows you to view the amount of money owed to each vendor/customer, and the amount of time that money has been owed. You can view either the total vendor/customer balances or the balances of specific ones. Time can be displayed by month, quarter, or period.

Enhanced ingestion workflow

The updated Data page guides you through each step of the ingestion process. Since uploading different datasets unlocks different analytical capabilities, we list the features along the right side of the page. Clicking a feature will reveal the required dataset(s) for each.

Customers can learn more about this release in our online documentation, or you can book a personalized demo here.

Large transaction support

Transactions that contain a large number of entries can limit an auditor’s ability to assess the true transaction risk or identify problematic entries. In Ai Auditor, large transactions are also often given higher risk scores due to the fact that a large number of entries contribute in a disproportionate way to the overall transaction risk score versus other transactions with smaller numbers of entries.

To this end, we now recognize and suggest alternatives for the treatment of large transactions. During the loading of data in the Review Data stage, Ai Auditor displays statistics about the file, including details about the number of transactions and their corresponding number of entries.