Using Analytics to Detect Possible Fraud: Tools and Techniques (Wiley Corporate F&A)

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(as of Dec 25,2024 01:41:07 UTC – Details)

ASIN ‏ : ‎ B00E1E6HRQ
Publisher ‏ : ‎ Wiley; 1st edition (July 16, 2013)
Publication date ‏ : ‎ July 16, 2013
Language ‏ : ‎ English
File size ‏ : ‎ 16714 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Enabled
Print length ‏ : ‎ 458 pages

In the world of finance and accounting, detecting fraud is a top priority for companies looking to protect their assets and maintain the trust of their stakeholders. With the rise of technology and data analytics, organizations now have powerful tools at their disposal to detect and prevent fraudulent activity.

In our latest post, we explore the various tools and techniques that companies can use to leverage analytics in detecting possible fraud. From predictive modeling to anomaly detection, there are a variety of methods that can be used to identify suspicious patterns and behaviors within financial data.

By implementing these advanced analytics techniques, companies can proactively identify potential fraud risks and take swift action to mitigate them. With the right tools and strategies in place, organizations can protect themselves from financial losses and reputational damage caused by fraudulent activity.

To learn more about how analytics can be used to detect possible fraud, check out our latest post on Wiley Corporate F&A.
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