Related papers: Predicting and Explaining Customer Data Sharing in…
Maritime transport is a pivotal logistics mode for the long-distance and bulk transportation of goods. However, the intricate planning involved in this mode is often hindered by uncertainties, including weather conditions, cargo diversity,…
This paper explores the integration of Explainable Automated Machine Learning (AutoML) in the realm of financial engineering, specifically focusing on its application in credit decision-making. The rapid evolution of Artificial Intelligence…
We analyze the network of transactions among cities based on the electronic invoice database for the municipalities in the Cear\'a state, Brazil. It consists of approximately 3.7 billion records, registered during the period between the…
Recently, economic depression, which scoured all over the world, affects business organizations and banking sectors. Such economic pose causes a severe attrition for banks and customer retention becomes impossible. Accordingly, marketing…
Bank crisis is challenging to define but can be manifested through bank contagion. This study presents a comprehensive framework grounded in nonlinear time series analysis to identify potential early warning signals (EWS) for impending…
In the recent years money laundering schemes have grown in complexity and speed of realization, affecting financial institutions and millions of customers globally. Strengthened privacy policies, along with in-country regulations, make it…
This transformation of food delivery businesses to online platforms has gained high attention in recent years. This due to the availability of customizing ordering experiences, easy payment methods, fast delivery, and others. The…
Transparency of Machine Learning models used for decision support in various industries becomes essential for ensuring their ethical use. To that end, feature attribution methods such as SHAP (SHapley Additive exPlanations) are widely used…
It is of high interest for a company to identify customers expected to bring the largest profit in the upcoming period. Knowing as much as possible about each customer is crucial for such predictions. However, their demographic data,…
Evolving borrower behaviors, shifting economic conditions, and changing regulatory landscapes continuously reshape the data distributions underlying modern credit-scoring systems. Conventional explainability techniques, such as SHAP, assume…
Wearable devices can offer services to individuals and the public. However, wearable data collected by cloud providers may pose privacy risks. To reduce these risks while maintaining full functionality, healthcare systems require solutions…
Social networks represent nowadays in many contexts the main source of information transmission and the way opinions and actions are influenced. For instance, generic advertisements are way less powerful than suggestions from our contacts.…
The explosion in high-resolution data capture technologies in health has increased interest in making inferences about individual-level parameters. While technology may provide substantial data on a single individual, how best to use…
Business statistics play a crucial role in implementing a data-driven strategic plan at the enterprise level to employ various analytics where the outcomes of such a plan enable an enterprise to enhance the decision-making process or to…
This research article analyses and demonstrates the hidden implications for fairness of seemingly neutral data coupled with powerful technology, such as machine learning (ML), using Open Banking as an example. Open Banking has ignited a…
One of the service providers in the financial service sector, who provide premium service to the customers, wanted to harness the power of data analytics as data mining can uncover valuable insights for better decision making. Therefore,…
This paper examines two different yet related questions related to explainable AI (XAI) practices. Machine learning (ML) is increasingly important in financial services, such as pre-approval, credit underwriting, investments, and various…
Strategic customer behavior is strongly influenced by the level of information that is provided to customers. Hence, to optimize the design of queueing systems, many studies consider various versions of the same service model and compare…
Inferring information related to users enables to highly improve the quality of many mobile services. For example, knowing the demographic characteristics of a user allows a service to display more accurate information. According to the…
Data sharing by researchers is a centerpiece of Open Science principles and scientific progress. For a sample of 6019 researchers, we analyze the extent/frequency of their data sharing. Specifically, the relationship with the following four…