What is text analysis in fraud?

What is text analysis in fraud?

Textual analytics is a type of data analytics that is used to explain, understand and interpret a situation or a person’s actions or thoughts. The use of textual analytics to assess fraud risk, analyze text in emails and social media, and understand sentiment in the right context is discussed.

Can data mining be used to detect fraud?

However, data mining makes it possible to detect other, more subtle signs of fraud with high levels of accuracy. Customer information can be analyzed to predict general trends and spot fraudulent transactions before a customer even knows that their card or account has been compromised.

What is the most common method of fraud detection?

An anonymous tip line (or website or hotline) is one of the most effective ways to detect fraud in organizations. In fact, tips are by far the most common method of initial fraud detection (40% of cases), according to the Association of Certified Fraud Examiners (ACFE) 2018 Report to the Nations.

Which data mining technique is appropriate for fraud detection?

We present data mining techniques which are most appropriate for fraud analysis. We present automobile insurance example. Three data mining techniques used for fraud analysis are: i) Bayesian network, ii) Decision tree, and iii) backpropagation. Bayesian network is the technique used for classification task.

How do auditors detect fraud?

Audit Procedures That Helps in Detecting Fraud

1. Having Fraud Brainstorming Session. According to the MASA, the audit engagement team must have a fraud brainstorming session before they start performing the audit.
2. Performing Journal Entry Testing.
3. Inspecting Accounting Estimates.
4. Checking for Significant Unusual Transaction.

How can auditors detect fraud?

Audit Procedures That Helps in Detecting Fraud

1. Having Fraud Brainstorming Session.
2. Performing Journal Entry Testing.
3. Inspecting Accounting Estimates.
4. Checking for Significant Unusual Transaction.

How is occupational fraud initially detected?

So, if perpetrators work to hide their fraudulent activity, how is occupational fraud initially detected? In the cases studied, 40% of the frauds were initially detected by tips. The second most common method was internal audit, which accounted for the initial fraud detection in only 15% of the cases.

How are fraud patterns used in text mining?

Here are the patterns I was thinking of and the related fraud that i would like to detect: Numeric Patterns – fictitious invoice numbers, fictitiously-generated transaction amounts. Time Patterns – transactions occurring too regularly, activity at unusual times or dates. Name Patterns – similar and alerted name and addresses.

How to do novelty detection using text mining?

The text will take a bit of playing with, but is pretty straightforward to normalize and turn into a feature set. I suggest applying TFIDF to normalize each text document against the entire corpus. You will then have lots of text features that you can join with your metadata features to do novelty detection.

How are words represented in a fraud Dictionary?

Each concept is further represented by words, phrases, entities etc. The presence of these words/phrases in the document implies occurrence of fraud concept in that transaction. The end result of this exercise will be a fraud dictionary that is a repository of concepts and suspicious key words.

How to identify fraud concepts in a business?

As a first step you’ll have to identify fraud concepts with help from subject matter expert for the line of business in concern. Fraud concept is a person, characteristic, entity, or event that represents a suspicious scenario and similar concepts can be grouped together to form a concept category.