arXiv research

Model predicts missing boarding stops in smart card data.

Paper predicts in-situ metro passenger density using smart card data.

Investigates the cost-effectiveness of security features in smart card chips.

TripDecoder recovers metro routes and travel times from smart card data.

Study evaluates SHAP for credit card default model consistency.

Historically, games of all kinds have often been the subject of study in scientific works of Computer Science, including the field of machine learning. By using machine learning techniques and applying them to a game with defined rules or a structured dataset, it's possible to learn and improve on the already existing …

ARIMA model detects credit card fraud in unbalanced datasets.

The credit cards' fraud transactions detection is the important problem in machine learning field. To detect the credit cards's fraud transactions help reduce the significant loss of the credit cards' holders and the banks. To detect the credit cards' fraud transactions, data scientists normally employ the unsupervised…

Study optimizes classifiers for credit card mail campaigns and default prediction.

Standard economic theory, starting with Adam Smith's invisible hand, holds that those who trade for their own selfish motives of maximizing their private preferences may contribute more to the public wealth than those who claim altruistic motives. Under restrictive conditions, this has been shown to result from a self-…

CARD detects treatment responders with machine learning and adjustment.

Machine learning and data mining techniques have been used extensively in order to detect credit card frauds. However, most studies consider credit card transactions as isolated events and not as a sequence of transactions. In this article, we model a sequence of credit card transactions from three different perspectiv…

Machine learning and data mining techniques have been used extensively in order to detect credit card frauds. However purchase behaviour and fraudster strategies may change over time. This phenomenon is named dataset shift or concept drift in the domain of fraud detection. In this paper, we present a method to quantify…

Expert system predicts credit card charge-offs using macroeconomic indicators.

Machine learning and data mining techniques have been used extensively in order to detect credit card frauds. However, most studies consider credit card transactions as isolated events and not as a sequence of transactions. In this framework, we model a sequence of credit card transactions from three different perspect…

We present a model of credit card profitability, assuming that the card-holder always pays the full outstanding balance. The motivation for the model is to calculate an optimal credit limit, which requires an expression for the expected outstanding balance. We derive its Laplace transform, assuming that purchases are m…

Semi-supervised GANs with log-signatures improve credit card fraud detection.

CARD models predict the distribution of continuous or categorical responses.

The study reveals fundamental limits of fraud detection in card payment networks.

Research examines motivations and factors influencing retailers' payment method choices.

This paper summarizes AI methods for detecting credit card fraud.

Study evaluates AD methods for fraud detection in online credit card payments.

CaT-GNN improves credit card fraud detection by integrating causal reasoning into GNNs.

Money flow models are essential tools to understand different economical phenomena, like saving propensities and wealth distributions. In spite of their importance, most of them are based on synthetic transaction networks with simple topologies, e.g. random or scale-free ones, as the characterisation of real networks i…

We introduce a new virtual environment for simulating a card game known as "Big 2". This is a four-player game of imperfect information with a relatively complicated action space (being allowed to play 1,2,3,4 or 5 card combinations from an initial starting hand of 13 cards). As such it poses a challenge for many curre…

CARDS improves decoding efficiency and alignment quality for LLMs.

Wrist movements can reveal digits, posing security risks.

Study Figgie card game strategies using agent-based simulation.

Proposes a probabilistic framework for smart contract risk quantification.

The paper proposes a method to detect credit card fraud using sparse Gaussian approximations.

Paper proposes auction method for smart derivatives to avoid disputes.

Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinat…

For any compact Riemannian surface $S$ and any point $y$ in $S$, $Q_y^{-1}$ denotes the set of all points in $S$, for which $y$ is a critical point. We proved \cite{BIVZ} together with Imre Bárány that card$Q_y^{-1} \geq 1$, and that equality for all $y\in S$ characterizes the surfaces homeomorphic to the sphere. Here …

Recently, a wide range of smart devices are deployed in a variety of environments to improve the quality of human life. One of the important IoT-based applications is smart homes for healthcare, especially for elders. IoT-based smart homes enable elders' health to be properly monitored and taken care of. However, elder…

In this study, we employ Generative Adversarial Networks as an oversampling method to generate artificial data to assist with the classification of credit card fraudulent transactions. GANs is a generative model based on the idea of game theory, in which a generator G and a discriminator D are trying to outsmart each o…

Stablecoins offer efficient settlement but externalize costs and risks.

Study develops a new model for predicting individual mobility based on activity patterns.

FinTech uses data science and AI to transform finance.

The paper categorizes four types of scale-up: smart, dumb, forced, and fumbled.

BreachRadar detects points-of-compromise in bank transactions to prevent fraud.

Improved security of smart contracts by classifying them into four categories.

Future buildings will offer new convenience, comfort, and efficiency possibilities to their residents. Changes will occur to the way people live as technology involves into people's lives and information processing is fully integrated into their daily living activities and objects. The future expectation of smart build…

Assessment of risk levels for existing credit accounts is important to the implementation of bank policies and offering financial products. This paper uses cluster analysis of behaviour of credit card accounts to help assess credit risk level. Account behaviour is modelled parametrically and we then implement the behav…

Deep reinforcement learning (DRL) has gained a lot of attention in recent years, and has been proven to be able to play Atari games and Go at or above human levels. However, those games are assumed to have a small fixed number of actions and could be trained with a simple CNN network. In this paper, we study a special …

Study develops smart contract framework for procurement under demand variability.

A new method streamlines digital payment programming using smart contracts.

In this paper, we propose a game theoretical adversarial intervention detection mechanism for reliable smart road signs. A future trend in intelligent transportation systems is ``smart road signs" that incorporate smart codes (e.g., visible at infrared) on their surface to provide more detailed information to smart veh…

SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks. SMART provides users with an intuitive interface for creating labeled data sets, supports active learning to help reduce the required amount of …