3 books on AI for Fraud Prevention [PDF]
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Fraud (online scam) is a variety of schemes and techniques used by hackers that intend, for example, to convince users to transfer money to a fake account. The number of successful fraud cases is growing every year as grows the number of applications and services. Hackers are targeting not only users but also company employees. Fraudsters are becoming smarter and their schemes are becoming more sophisticated. New fraudulent patterns are emerging so fast that risk monitoring teams simply can’t keep up with them.
In this context, the key factor is the learning of anti-fraud systems, their ability to recognize new schemes and flag them as potential threats within the selected risk scoring model. The bottom line? Today we see a clear trend toward strengthening IT infrastructure security with AI- and ML-based anti-fraud solutions.
AI-powered anti-fraud systems operate by the principle of "prevention is better than emergency protection". Security teams develop and implement neural networks, algorithms and behavioral analysis to quickly detect when something goes wrong, whether it's a suspicious transaction, an anomaly in user behavior or a glitch in the data flow. For example, someone suddenly starts using their account differently than usual, typing too fast or using unfamiliar words. The system will flag such actions as potentially dangerous. Then, it's up to the SecOps to address these red flags.
Here are some PDF books about AI for Fraud Prevention:
1. Machine Learning Approach to Detect Fraudulent Banking Transactions
2022 by Riwaj Kharel
Download PDF
2. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
2015 by Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke
Download PDF
3. Fraud and Fraud Detection, + Website: A Data Analytics Approach
2014 by Sunder Gee
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
In this context, the key factor is the learning of anti-fraud systems, their ability to recognize new schemes and flag them as potential threats within the selected risk scoring model. The bottom line? Today we see a clear trend toward strengthening IT infrastructure security with AI- and ML-based anti-fraud solutions.
AI-powered anti-fraud systems operate by the principle of "prevention is better than emergency protection". Security teams develop and implement neural networks, algorithms and behavioral analysis to quickly detect when something goes wrong, whether it's a suspicious transaction, an anomaly in user behavior or a glitch in the data flow. For example, someone suddenly starts using their account differently than usual, typing too fast or using unfamiliar words. The system will flag such actions as potentially dangerous. Then, it's up to the SecOps to address these red flags.
Here are some PDF books about AI for Fraud Prevention:
1. Machine Learning Approach to Detect Fraudulent Banking Transactions
2022 by Riwaj Kharel
Download PDF
2. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
2015 by Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke
Download PDF
3. Fraud and Fraud Detection, + Website: A Data Analytics Approach
2014 by Sunder Gee
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
