Machine Learning Approach to Detect Fraudulent Banking Transactions (Paperback o

Machine Learning Approach to Detect Fraudulent Banking Transactions (Paperback o

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In today’s digital age, with the rise of online banking and transactions, fraudulent activities have also become increasingly sophisticated. Traditional methods of fraud detection are no longer sufficient to keep up with the evolving tactics of fraudsters.

Machine learning, a subset of artificial intelligence, has emerged as a powerful tool in detecting fraudulent banking transactions. By leveraging algorithms and statistical models, machine learning can analyze large volumes of data in real-time to identify patterns and anomalies that may indicate fraudulent activities.

This book provides a comprehensive overview of the machine learning approach to fraud detection in banking transactions. It covers the fundamental concepts of machine learning, the types of fraud that can occur in banking transactions, and the specific algorithms and techniques that can be used to detect and prevent fraud.

Whether you are a data scientist, a fraud analyst, or a banking professional looking to enhance your fraud detection capabilities, this book will provide you with the knowledge and tools needed to effectively detect and prevent fraudulent activities in banking transactions.

Available in paperback or ebook format, this book is a must-read for anyone interested in leveraging machine learning for fraud detection in the banking industry.
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