AI + automation = effortless financial analysis

In a recent, information-packed webinar, MindBridge AI experts Nick and Brad demonstrated how the innovative MindBridge API is transforming the industry by leveraging AI-driven risk assessment and transactional analysis. This valuable session catered to financial professionals, including external auditors, CFOs, controllers, and internal auditors, and showcased the different user groups when it comes to technology within MindBridge and specifically the API.

In this blog post, we provide a summary of some key takeaways from the webinar. Keep reading for more details, or click below to view the recording.

Session hosts

The power of MindBridge API for efficient risk management

In the webinar, Nick and Brad explained that MindBridge’s primary objective is to empower organizations to mitigate financial and operational risks effectively. They highlighted how MindBridge distinguishes itself from competitors by concentrating on general ledger data and using risk indicators derived from conventional rules, machine learning, and statistical methodologies for financial anomaly detection.

Exploring the benefits of the MindBridge API

The API’s ease of use, transparency, and scalability are all possible due to its compliance with the Open API standard. During the webinar, Nick and Brad illustrated two impactful use cases that demonstrate how to maximize the benefits of the MindBridge API:

1. Streamlining Analysis with Power Automate: Nick shared his experience in creating a workflow that initiated a financial analysis, monitored its progress, and notified the user upon completion. Despite minor setbacks, this example illustrated the API’s simplicity and potential to pinpoint high-risk areas for targeted audit planning. The demonstration included using API calls and Microsoft Teams to initiate the analysis and fix issues in real time.

2. Merging MindBridge Data with Corruption Index in Power BI: The speakers showcased a unique scenario where they integrated MindBridge risk scores with a corruption index dataset to enhance company-wide risk assessment. Brad explained, “By developing a heat map of risk scores and a color-coded map of corruption convictions, we emphasized the advantages of recognizing high-risk regions and their potential impact on pricing and other aspects.”

Nick and Brad also discussed how the API allows users to perform various tasks, such as creating engagements, analyzing, ingesting data, and managing results. This capability enables more frequent analyses, time-saving autonomous uploads, and ultimately streamlines the financial analysis process, including anomaly detection in finance.

API documentation and support

The presenters emphasized the importance of the auto-generated API documentation available from the source code, which is regularly updated to ensure consistency and ease of use for users. Additionally, they mentioned the open API spec that can be downloaded from the admin section, which is always up to date.

Key takeaways

During the Q&A portion, the presenters explained how MindBridge detects red flags using risk indicators or “control points” based on rules, statistical methods, or machine learning algorithms for financial risk assessment. They also confirmed that the software caters to advisory firms of all sizes, delivering valuable insights and comparative analytics based on the data provided.

The webinar concluded with an announcement for an upcoming session on vendor payments control, scheduled for May 18th. In this session, we will demonstrate a live example using a public payment dataset, showcasing the insights that can be uncovered without additional information. Don’t miss this opportunity to gain a competitive edge in financial risk detection with AI-driven payment analysis. Register now and elevate your financial analysis capabilities!