When does class start/end?
Class hours may vary, please reach out to contact@ascendientlearning.com if you have any questions.
Fraud Detection Using Descriptive, Predictive, and Social Network Analytics
A typical organization loses an estimated 5 of its yearly revenue to fraud. This course shows how learning fraud patterns from historical data can be used to fight fraud. The course discusses the use...
Read MoreOverview
A typical organization loses an estimated 5 of its yearly revenue to fraud. This course shows how learning fraud patterns from historical data can be used to fight fraud. The course discusses the use of supervised learning (using a labeled data set), unsupervised learning (using an unlabeled data set), and social network learning (using a networked data set). The techniques can be applied across a wide variety of fraud applications, such as insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and counterfeiting. The course provides a mix of both theoretical and technical insights, as well as practical implementation details. During the course, the instructor reports extensively on his recent research insights about the topic. Various real-life case studies and examples are presented for further clarification.
Skills Gained
- Preprocess data for fraud detection (sampling, missing values, outliers, categorization, and so on).
- Build fraud detection models using supervised analytics (logistic regression, decision trees, neural networks, ensemble models, and so on).
- Build fraud detection models using unsupervised analytics (hierarchical clustering, non-hierarchical clustering, k-means, self organizing maps, and so on).
- Build fraud detection models using social network analytics (homophily, featurization, egonets, PageRank, bigraphs, and so on).
Who Can Benefit
- Fraud analysts, data miners, and data scientists; consultants working in fraud detection; validators auditing fraud models; and researchers in financial services companies, banks, insurance companies, government institutions, health-care institutions, and consulting firms
Prerequisites
- Before attending this course, you should have a basic knowledge of statistics, including descriptive statistics, confidence intervals, and hypothesis testing.
Course Details
Introduction
Fraud Detection
- The importance of fraud detection.
- Defining fraud.
- Anomalous behavior.
- Fraud cycle.
- Types of fraud.
- Examples of insurance fraud and credit card fraud.
- Key characteristics of successful fraud analytics models.
- Fraud detection challenges.
- Approaches to fraud detection.
Data Preprocessing
- Motivation.
- Types of variables.
- Sampling.
- Visual data exploration.
- Missing values.
- Outlier detection and treatment.
- Standardizing data.
- Transforming data.
- Coarse classification and grouping of attributes.
- Recoding categorical variables.
- Segmentation.
- Variable selection.
Supervised Methods for Fraud Detection
- Target definition.
- Linear regression.
- Logistic regression.
- Decision trees.
- Ensemble methods: bagging, boosting, random forests.
- Neural networks.
- Dealing with skewed class distributions.
- Evaluating fraud detection models.
Unsupervised Methods for Fraud Detection
- Unsupervised learning.
- Clustering approaches: hierarchical clustering, k-means clustering, self-organizing maps.
- Peer group analysis.
- Break point analysis.
Social Networks for Fraud Detection
- Social networks and applications.
- Is fraud a social phenomenon?
- Social network components.
- Visualizing social networks.
- Social network metrics.
- Community mining.
- Social-network-based inference (network classifiers and collective inference).
- From unipartite toward bipartite graphs.
- Featurizing a bigraph.
- Fraud propagation.
- Case study.
Fraud Analytics: Putting It All to Work
- Quantitative monitoring: backtesting, benchmarking.
- Qualitative monitoring: data quality, model design, documentation, corporate governance.
Schedule
FAQ
Does the course schedule include a Lunchbreak?
Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.
What languages are used to deliver training?
Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.
What does GTR stand for?
GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.
How do I find an Ascendient Learning training location?
We have training locations across the United States and Canada - View a complete list of classroom training locations.
Which delivery formats are available?
At Ascendient Learning, we offer training that is Instructor-Led, Online, Virtual, and Self-Paced.
Does Ascendient Learning deliver group training?
Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.
What does vendor-authorized training mean?
As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.
Is the training too basic, or will you go deep into technology?
It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.
How up-to-date are your courses and support materials?
We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.
Are your instructors seasoned trainers who have deep knowledge of the training topic?
Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.
Do you provide hands-on training and exercises in an actual lab environment?
Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.
Will you customize the training for our company’s specific needs and goals?
We will work with you to identify training needs and areas of growth. We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.
How do I get started with certification?
Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.
Will I get access to content after I complete a course?
You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.
How do I request a W9 for Ascendient Learning?
View our filing status and how to request a W9.
Reviews
It was very informative and covered all the required materials along with handson labs for practice.
Great training it covered the most importan topics if GitHub copilot with good explanation and good labs.
ExitCertified gave a great course on AWS that covered all of the basics in depth with good lab materials.
Good training. A lot to take in for the short amount of time we have though
ExitCertified provided us with a great opportunity to learn more about React and in easy to follow way.
