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Drive Away Fraudsters With Driverless AI - Venkatesh Ramanathan, Senior Data Scientist, PayPal

#artificialintelligence

Share results from experiments conducted on large scale payment transaction data. Venkatesh is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection. He has over 20 years experience in designing, developing and leading teams to build scalable server-side software. In addition to being an expert in big-data technologies, Venkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP) and had worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.


Fintech and retail lead the fray in AI adoption by industry

#artificialintelligence

Compared to other industries, the finance industry jumped quickly to finding value with artificial intelligence. Currently, AI is being used in a variety of ways within the financial services industry. The most prominent use case for AI is in fraud and anomaly detection. When fraud occurs, financial firms end up covering fraud prevention services for the impacted victims. In addition to having to manage funds lost through fraud, financial institutions often find themselves tangled in a variety of other issues pertaining to the loss of reputation.


Machine learning and big data know it wasn't you who just swiped your credit card

#artificialintelligence

You're sitting at home minding your own business when you get a call from your credit card's fraud detection unit asking if you've just made a purchase at a department store in your city. It wasn't you who bought expensive electronics using your credit card – in fact, it's been in your pocket all afternoon. So how did the bank know to flag this single purchase as most likely fraudulent? Credit card companies have a vested interest in identifying financial transactions that are illegitimate and criminal in nature. According to the Federal Reserve Payments Study, Americans used credit cards to pay for 26.2 billion purchases in 2012.


Machine learning and big data know it wasn't you who just swiped your credit card

#artificialintelligence

You're sitting at home minding your own business when you get a call from your credit card's fraud detection unit asking if you've just made a purchase at a department store in your city. It wasn't you who bought expensive electronics using your credit card – in fact, it's been in your pocket all afternoon. So how did the bank know to flag this single purchase as most likely fraudulent? Credit card companies have a vested interest in identifying financial transactions that are illegitimate and criminal in nature. According to the Federal Reserve Payments Study, Americans used credit cards to pay for 26.2 billion purchases in 2012.


Artificial Intelligence to Amplify FinTech

@machinelearnbot

AI has taken some steps into banking, but it also poised to transform how banks learn from and interact with customers. Financial services will lead the charge in the implementation of AI. Africa's mobile phone market has expanded to become larger than either the EU or the United States with some 650 million subscribers (2016 data). At the same time, Internet bandwidth has grown 20-fold as hundreds of thousands of kilometres of new cables have been laid across the continent to serve an increasing number of its 1.2 billion Africans. Augmented experience on how to recommend how much to spend and on what. AI is already driving the reinvention of existing products and interactions. Endowing the modern workforce with AI, machine learning, payment intelligence and advanced analytics fintech will thrive, amplify and fly. FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.