Inductive learning and classification techniques have been applied in many problems in diverse areas. In this paper we describe an AI-based approach that combines inductive learning algorithms and meta-learning methods as a means to compute accurate classification models for detecting electronic fraud. Inductive learning algorithms are used to compute detectors of anomalous or errant behavior o...

This paper addresses an effective learning method that enables us to directly optimize neural network classifier's discrimination performance at a desired local operating range by maximizing a partial area under a receiver operating characteristic (ROC) or domain-specific curve, which is difficult to achieve with classification accuracy or mean squared error (MSE)-based learning methods. The ef...

Financial institutions in the form of banks provide facilities credit cards, but with development technology, fraud on card transactions is still common, so a system needed that can detect quickly and accurately. Therefore, this study aims to classify fraudulent transactions. The proposed method Ensemble Learning which will be tested using Boosting type 3 variations, namely XGBoost, Gradient Bo...

The use of trade credit as a short-term financing is increasing in the last years; large firms use more days to pay small firms than they need, which causes financial fatal consequences to suppliers. These financial problems are not new, but with the credit crunch they are coming up because the massive use of the trade credit impacts negatively on suppliers whose insolvency and bankruptcy risks...

Two clichés sum up the telecommunications policy world for the past half dozen years. First, the only constant is change. Second, the more things change, the more they stay the same. The main topics of debate have turned, in just three years, from unbundled network elements and “open access” to video franchising reform and “net neutrality.” But the deep structure of the debate remains eerily fa...

The use of Big Data analytics for business improvements is a vital strategy for survival. In this paper, we report a study that investigates the role of BD analytics on consumer finance, credit card finance in China—a research area that has largely remained unexplored. The largeness and diversity of Chinese consumer market merit an urgent attention and understanding of role of BD analytics is s...

We describe initial experiments using meta-learning techniques to learn models of fraudulent credit card transactions. Our experiments reported here are the first step towards a better understanding of the advantages and limitations of current meta-learning strategies on real-world data. We argue that, for the fraud detection domain, fraud catching rate (True Positive rate) and false alarm rate...

Students entering college have limited financial experience while making complex borrowing decisions. This paper examines a policy lever that may improve these decisions: high school personal finance graduation requirements. We use a difference-in-difference strategy exploiting differential timing of state mandates and a sample of incoming freshmen at four year institutions in the National Post...

n contemporary days the more secured data transfer occurs almost through internet. At same duration the risk also augments in secure data transfer. Having the rise and also light progressiveness in e – commerce, the usage of credit card (CC) online transactions has been also dramatically augmenting. The CC (credit card) usage for a safety balance transfer has been a time requirement. Credit-car...

The use of Big Data analytics for business improvements is a vital strategy for survival. In this paper, we report a study that investigates the role of BD analytics on consumer finance, credit card finance in China—a research area that has largely remained unexplored. The largeness and diversity of Chinese consumer market merit an urgent attention and understanding of role of BD analytics is s...