- Resampling Imbalanced Data and Its Limits - Dec 22, 2020.
Can resampling tackle the problem of too few fraudulent transactions in credit card fraud detection?
- Fraud through the eyes of a machine - Nov 24, 2020.
Data structured as a network of relationships can be modeled as a graph, which can then help extract insights into the data through machine learning and rule-based approaches. While these graph representations provide a natural interface to transactional data for humans to appreciate, caution and context must be applied when leveraging machine-based interpretations of these connections.
- DIY Election Fraud Analysis Using Benford’s Law - Sep 15, 2020.
In this article, we will talk about a Do-It-Yourself approach towards election analysis and coming to a conclusion whether the elections were conducted fairly or not.
- A Comprehensive Data Repository for Fake Health News Detection - Mar 19, 2020.
We introduce the FakeHealth, a new data repository for fake health news detection. Following a preliminary analysis to demonstrate its features, we consider additional potential directions for better identifying fake news.
- AI and Machine Learning In Our Every Day Life - Feb 7, 2020.
The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.
- How Data Analytics Can Assist in Fraud Detection - Nov 11, 2019.
A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies.
- What is Benford’s Law and why is it important for data science? - Aug 7, 2019.
Benford’s law is a little-known gem for data analytics. Learn about how this can be used for anomaly or fraud detection in scientific or technical publications.
- Machine Learning and Deep Link Graph Analytics: A Powerful Combination - Apr 23, 2019.
We investigate how graphs can help machine learning and how they are related to deep link graph analytics for Big Data.
- Introduction to Fraud Detection Systems - Aug 17, 2018.
Using the Python gradient boosting library LightGBM, this article introduces fraud detection systems, with code samples included to help you get started.
- AI for Fraud Detection – How does Mastercard do it? Learn how global leaders use AI - Jul 2, 2018.
At the AI in Finance Summit, Sept 6-7 in NYC, RE•WORK we will be showcasing the latest breakthrough technologies & their application in the financial sector with topics including Financial Compliance, Financial Forecasting, NLP, Investment, Blockchain & more.
- University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Fraud Detection) - Jun 1, 2018.
Seeking a senior research data scientist to participate to the AFFUT (Advanced Analytics for Fraud Detection) project.
- Managing model complexity in the fight against fraud, Apr 18 Webinar - Apr 10, 2018.
Learn how to optimize your models by leveraging robust data sets that improve performance; avoiding endless feature engineering and overfitting; and other useful steps.
- Using GRAKN.AI to Detect Patterns in Credit Fraud Data - Aug 30, 2017.
The term Horn Clause Mining, similar to Rule Based Machine Learning or Inductive Logic Programming, is used to describe the inverse of this functionality. Given a large enough knowledge base, can we infer rules that describe the data accurately?
- Stay ahead of cyberattacks and fraud with predictive analytics - Jun 6, 2017.
Even as cyber criminals and swindlers step up their game, companies can use predictive analytics to stay ahead. Discover the full scope of IBM SPSS predictive analytics capabilities.
- Cartoon: Taxes, Artificial Intelligence, and Humans - Apr 15, 2017.
In honor of Tax Day, new KDnuggets Cartoon looks at an unexpected white-collar job that may resist automation and Machine Learning.
- New e-learning course: Fraud Analytics using Descriptive, Predictive and Social Network Analytics - Jan 31, 2017.
This online course teaches how to find fraud patterns from historical data using descriptive analytics, and social network learning.
- Apple: Data Science Engineer - Dec 21, 2016.
Changing the world is all in a day's work at Apple. If you love innovation, here's your chance to make a career of it. You'll work hard. But the job comes with more than a few perks.
- Apple: Data Science Engineer - Sep 22, 2016.
Seeking a Data Science Engineer to lead the design and implementation of systems and tools to support the fraud prevention efforts of Analytic Insight.
- 7 Ways How Data Science Fuels The FinTech Revolution - Sep 16, 2016.
Here are 7 ways how data science is at the core of the current transformation of the financial sector.
- Boost your Business Analytics Skills - Jul 26, 2016.
Learn the latest business practices, concepts, methodologies and techniques in advanced analytics, data mining, survival analysis, explaining analytics to decision makers, fraud detection, and more with the SAS Business Knowledge Series.
- Link Analysis for Fraud Detection: How Linkurious enabled investigation of the massive Panama Papers leaks - Apr 6, 2016.
Linkurious is a partner of the International Investigative Journalist Consortium (ICIJ) since the Swiss Leaks scandal. ICIJ network of 370 journalists is using Linkurious to investigate the Panama Papers. Learn the inside story of the biggest data leak investigation in history.
- How to combat financial fraud by using big data? - Mar 25, 2016.
Financial fraud methods are becoming more sophisticated and the techniques to combat such attacks also need to evolve. Big data has brought with it novel fraud detection and prevention techniques such as behavioral analysis and real-time detection to give fraud fighting techniques a new perspective.
- Fraud Bots Mess Up Your Big Data - Mar 11, 2016.
The bots that cause digital ad fraud also mess up analytics. When they create fake visits, pageviews, ad impressions, clicks, etc. those metrics are not real and should be corrected for.
- Big Data and Data Science for Security and Fraud Detection - Dec 11, 2015.
We review big data analytics tools and technologies that combine text mining, machine learning and network analysis for security threat prediction, detection and prevention at an early stage.
- Detecting In-App Purchase Fraud with Machine Learning - Nov 25, 2015.
Hacking applications allow users to make in-app purchases for free. With help from a few big games in the GROW data network we were able to build a model that classifies each purchase as real or fraud, with a very high level of accuracy.
- How to discover stolen data using Hadoop and Big data? - Nov 11, 2015.
We discuss recent data breaches and present an approach that uses Hadoop and data fingerprint matching techniques to discover stolen data.
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- Discover the power of business analytics - Nov 3, 2015.
Learn the latest business practices, concepts, methodologies and techniques in advanced analytics, data mining, survival analysis, explaining analytics to decision makers, fraud detection, and more with these courses.
- Top KDnuggets tweets, Oct 20-26: Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality - Oct 27, 2015.
Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality; Cartoon: KDnuggets Addiction; Good overview: #BigData Infrastructure at IFTTT.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 6 and beyond - Oct 5, 2015.
Upcoming Webcasts on Analytics, Big Data, Data Science - Oct 6 and beyond, Preventing a Big Data Letdown, Compensation of Predictive Analytics Professionals, Predictive Workforce Playbook, Fraud Detection, Optimizing the Data Lake, and more.
- Systematic Fraud Detection Through Automated Data Analytics in MATLAB - Aug 27, 2015.
Fraud detection is one of the most challenging use case considering the number of factors it depend on. Here, we demonstrate how using hedge fund data in MATLAB you can automate the process of acquiring and analyzing fraud detection data.
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- New Hybrid Rare-Event Sampling Technique for Fraud Detection - Apr 26, 2015.
Proposed hybrid sampling methodology may prove useful when building and validating machine learning models for applications where target event is rare, such as fraud detection.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 7 and beyond - Oct 6, 2014.
Evolution of Classification, Billion Dollar Fraud Detection, Big Data Visualization, Deep Learning on Apache Spark, and more.
- Interview: Taylor Phillips, Square on Why Finance Needs Machine Learning and Data Science - Aug 1, 2014.
We discuss the role of data science at Square, common machine learning use cases, transition to real-time architecture, major challenges, expectations from data science, key qualities for data scientists, and more.
- U. Antwerpen: PhD Position, Data mining for tax fraud detection - Jul 18, 2014.
Develop new fraud detection techniques for historical data to help combat tax fraud in this PhD position at U. Antwerpen. Apply by August 10th, 2014.
- Data Mining Medicare Data – What Can We Find? - Apr 24, 2014.
Medicare released detailed reimbursement data for 2012: $77 billion paid to more than 880,000 health care providers, by doctor and procedure.We take an initial look and find large variances and potential indicators of fraud.
- FICO: 20+ Years of Analytics Innovations to fight Fraud - Mar 12, 2014.
FICO infographic shows 20+ years of analytics innovations protecting consumers from payments fraud. It highlights the most significant innovations in anti-fraud analytics for card payments, and offers interesting facts about payment fraud.