By Alejandro Correa Bahnsen, Chief Data Scientist

Alejandro Correa Bahnsen is part of Easy Solutions’ Research organization. In this role, Alejandro spends his time on the application of data science to Easy Solutions’ products to ensure our company continues to offer the most advanced and effective fraud prevention solutions. Alejandro holds a Ph.D. in machine learning from Luxembourg University.

From Real-Time Learning to Reinforcement Learning with Asynchronous Feedback

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Online, or real-time, transactional fraud detection systems have recently created quite the buzz in the info security industry. Read more

Building AI Applications Using Deep Learning

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Recently, we have seen a huge boom around the field of deep learning; it is currently being implemented in a wide variety of fields, from driverless cars to product recommendation. Read more

Classifying Phishing

Classifying Phishing URLs Using Recurrent Neural Networks

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Easy Solutions data scientists, including the author of this article, will present extensive research on the use of deep neural networks to detect phishing sites. Read more

Machine Learning Explained

Machine Learning Explained

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Machine Learning Explained

 

Machine learning models are often dismissed on the grounds of lack of interpretability. There is a popular story about modern algorithms that goes as follows: Read more

Isolation forests

Benefits of Anomaly Detection Using Isolation Forests

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One of the newest techniques to detect anomalies is called Isolation Forests. The algorithm is based on the fact that anomalies are data points that are few and different. As a result of these properties, anomalies are susceptible to a mechanism Read more

Phishing

The Technical Side of Phishing and How to Prevent It

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This post is part of our continuing series of exploring and integrating new probabilistic tools for fraud prevention.

Phishing, by definition, is the act of defrauding an online user and tricking them into clicking on a malicious link Read more

Fraud Data Scientist

Applying Data Science to Fraud Prevention

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Eighty thousand Kindle users. Sixty-five million Tumblr users. What do they have in common? Both groups had their login credentials breached, courtesy of hackers. While these attacks didn’t directly target financial Read more

Fraud Detection

Fraud Detection That Accounts for Misclassification Using Cost-Sensitive Logistic Regression

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This article is a continuation of a previous post entitled “Evaluating a Fraud Detection Using Cost-Sensitive Predictive Analytics.” Read more

phishing

Phishing Attack Analysis: Estimating Key Cluster Features and Why It’s Important

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A recent report showed how we can gain a better understanding of phishing attacksand attackers by using cluster analysis.Subsequently, in a recent post we showed how Read more

Clustering of Phishing Attacks

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Easy Solutions data scientists, including the author of this article, will present extensive research on phishing patterns and correlations between attacks. Read more