Fraud Detection Techniques
Expert-defined terms from the Certified Professional in Fraud Investigation Case Studies in the Pharmaceutical Industry course at London School of Business and Administration. Free to read, free to share, paired with a globally recognised certification pathway.
Fraud Detection Techniques #
Fraud Detection Techniques
Fraud detection techniques are methods used to identify and prevent fraudulent a… #
In the context of the Certified Professional in Fraud Investigation Case Studies in the Pharmaceutical Industry, these techniques are essential for uncovering fraud schemes that may impact the financial health and reputation of pharmaceutical companies.
Artificial Intelligence (AI) #
Artificial Intelligence (AI)
Artificial intelligence (AI) refers to the simulation of human intelligen… #
In fraud detection, AI can be used to analyze large datasets and identify patterns that may indicate fraudulent behavior. AI algorithms can learn from historical data to improve accuracy in detecting anomalies that may be indicative of fraud.
Benford's Law #
Benford's Law
Benford's law , also known as the first #
digit law, is a mathematical principle that states that in many naturally occurring datasets, the leading digits are not evenly distributed. Instead, smaller digits (such as 1) tend to appear more frequently than larger digits (such as 9). This law is often used in fraud detection to identify anomalies in financial data that may indicate manipulation.
Data Mining #
Data Mining
Data mining is the process of analyzing large datasets to discover patter… #
In fraud detection, data mining techniques can be applied to identify unusual patterns that may indicate fraudulent activities, such as unexpected transactions or irregularities in financial records.
Machine Learning #
Machine Learning
Machine learning is a subset of artificial intelligence that involves the… #
In fraud detection, machine learning algorithms can be trained on historical data to identify patterns of fraudulent behavior and flag suspicious activities in real-time.
Red Flags #
Red Flags
Red flags are warning signs or indicators of potential fraudulent activit… #
These can include unusual financial transactions, discrepancies in records, suspicious behavior by employees, or deviations from standard procedures. Recognizing red flags is essential for fraud detection and prevention in the pharmaceutical industry.
Statistical Analysis #
Statistical Analysis
Statistical analysis involves the collection, organization, and interpret… #
In fraud detection, statistical techniques can be used to analyze financial data and identify anomalies that may indicate fraudulent behavior. By applying statistical analysis, investigators can assess the likelihood of fraud and prioritize their efforts accordingly.
Transaction Monitoring #
Transaction Monitoring
Transaction monitoring is the process of continuously reviewing and analy… #
In fraud detection, transaction monitoring systems can flag unusual patterns, such as large or frequent transactions, that may indicate fraudulent behavior. By monitoring transactions in real-time, organizations can detect and prevent fraud before it causes significant harm.
Unsupervised Learning #
Unsupervised Learning
Unsupervised learning is a machine learning technique where algorithms ar… #
In fraud detection, unsupervised learning algorithms can be used to detect anomalies in financial transactions that may indicate fraudulent behavior. By analyzing the data without predefined labels, unsupervised learning can uncover previously unknown patterns of fraud.
Whistleblower Hotline #
Whistleblower Hotline
A whistleblower hotline is a confidential reporting mechanism that allows… #
Whistleblower hotlines are an essential tool for fraud detection in the pharmaceutical industry, as they provide a channel for individuals to raise concerns without fear of retaliation. By encouraging whistleblowers to come forward, organizations can uncover fraudulent activities and take appropriate action to address them.