MindBridge named in Gartner Autonomous Accounting Hype Cycle
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data analysis

Product releases

Revolutionizing accounting oversight: MindBridge’s next-generation anomaly detection 

The accuracy of financial data is not just an operational need but a strategic imperative. Clean financial data is crucial for reliable financial analysis, accurate reporting, and sound decision-making. Finance teams need to be the trusted source of truth. This allows the business to maintain consistent compliance, manage risks, and optimize performance in business operations

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Leadership

Change management: What is it, and why is it important?

Change is scary. But with a little risk, a lot of planning, and some extra effort comes an opportunity for growth and reward. That’s what makes change management so important. As a manager, department head, or executive how do you know when it’s time for change? How do you invoke change within an organization, and

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Financial automation: The good, the bad, and the future | MindBridge
Finance function

Financial automation: The good, the bad, and the future

Well, it’s finally here. According to an article from Forbes Magazine, we have reached the age of automation. From AI and machine learning to financial automation and robotics, we’re officially an automatic civilization. Please, be kind to our new robot co-workers. Okay seriously, this is important stuff, even if we did all see it coming.

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Person moving to the future of audit
AI and technology

How the new SAS-142 audit evidence standard embraces technology and automation

A new audit evidence standard has been released by the American Institute of Certified Public Accountants (AICPA) that includes significant updates around how technology and automation can be leveraged throughout the audit process. Here, we’ll examine this standard and some of the most significant examples of how the AICPA has explicitly considered the applicability of

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Man using MindBridge to access financial risk
AI and technology

Assessing audit risk during engagements

Three ways Ai Auditor strengthens your audit planning The determination of where audit risks of material misstatement lie is a critical output of the audit planning process. Usually, identifying those risks is based on the auditors understanding of their client and the client’s operating environment. Auditors can now rely on a data-driven approach to better

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Moving squares versus circles
AI and technology

How AI and data can power an effective audit plan

An effective audit starts with a solid audit plan. While the overall audit strategy and plan can vary between clients, an auditor will usually establish risk assessment procedures and a how-to response for the risk of material misstatement. The challenge is that sometimes, even the most thorough and comprehensive audit plans can still have gaps.

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Improving audit risk assessment longterm
AI and technology

Improving audit risk assessments with AI-driven analysis of Accounts Receivable and Accounts Payable subledger data

The cornerstone of well-planned and high-quality audit engagements is a robust risk assessment process. Such a process is critical to identifying risks of material misstatement and their relative significance by providing a fulsome understanding of the entity subject to audit and the environment in which it operates. The nature and extent of these audit risk

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