Fraud Detection Using Descriptive, Predictive, and Social Network Analytics
Seria Wiedza Biznesowa szkolenie
Autorzy szkolenia Bart Baesens, Ph.D. Professor at KU Leuven (Belgium), and lecturer at the University of Southampton (UK); or Christophe Mues, Ph.D., Professor at the School of Management of the University of Southampton (UK); or Cristian Bravo, Ph.D., Associate Professor, Business Analytics, University of Southampton (UK); or Wouter Verbeke, Ph.D., Assistant Professor, Business Informatics, University of Brussels (Belgium); or Stefan Lessmann, Ph.D., Professor, School of Business and Economics, Humboldt University (Germany)
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.Naucz się
Kto powinien uczestniczyćFraud 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
Before attending this course, you should have a basic knowledge of statistics, including descriptive statistics, confidence intervals, and hypothesis testing.
To szkolenie wykorzystuje oprogramowanie SAS Enterprise Miner
Base SAS and SAS Social Network Analytics are also used in this course.
|Nazwa szkolenia||Czas trwania||Czas dostępu||Język||Koszt||Dodaj do koszyka|
|Fraud Detection Using Descriptive, Predictive, and Social Network Analytics||21.0 godziny||180 dni od daty zamówienia||angielski||2 100 PLN / 1 120 USD|
Informacja: Przepraszamy, w tej chwili nie ma zaplanowanych terminów dla tego szkolenia. Jeżeli wyrażasz chęć odbycia
tego szkolenia zadzwoń pod numer 22 560 46 20 lub wyślij wiadomość.