Artificial intelligence in customer-facing financial services: a systematic literature review and agenda for future research
Purpose The objective of this study is to provide a systematic review of the literature on
artificial intelligence (AI) in customer-facing financial services, providing an overview of …
artificial intelligence (AI) in customer-facing financial services, providing an overview of …
Explainable artificial intelligence in information systems: A review of the status quo and future research directions
The quest to open black box artificial intelligence (AI) systems evolved into an emerging
phenomenon of global interest for academia, business, and society and brought about the …
phenomenon of global interest for academia, business, and society and brought about the …
[HTML][HTML] Artificial Intelligence risk measurement
Financial institutions are increasingly leveraging on advanced technologies, facilitated by
the availability of Machine Learning methods that are being integrated into several …
the availability of Machine Learning methods that are being integrated into several …
[HTML][HTML] Interpretable machine learning for imbalanced credit scoring datasets
The class imbalance problem is common in the credit scoring domain, as the number of
defaulters is usually much less than the number of non-defaulters. To date, research on …
defaulters is usually much less than the number of non-defaulters. To date, research on …
Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
An explainable federated learning and blockchain-based secure credit modeling method
F Yang, MZ Abedin, P Hajek - European Journal of Operational Research, 2024 - Elsevier
Federated learning has drawn a lot of interest as a powerful technological solution to the
“credit data silo” problem. The interpretability of federated learning is a crucial issue due to …
“credit data silo” problem. The interpretability of federated learning is a crucial issue due to …
Explainable artificial intelligence (XAI) in finance: a systematic literature review
As the range of decisions made by Artificial Intelligence (AI) expands, the need for
Explainable AI (XAI) becomes increasingly critical. The reasoning behind the specific …
Explainable AI (XAI) becomes increasingly critical. The reasoning behind the specific …
Interpretable vs. noninterpretable machine learning models for data-driven hydro-climatological process modeling
Due to their enhanced predictive capabilities, noninterpretable machine learning (ML)
models (eg deep learning) have recently gained a growing interest in analyzing and …
models (eg deep learning) have recently gained a growing interest in analyzing and …
Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring
Customer credit scoring is a dynamic interactive process. Simply designing the static reward
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …
[HTML][HTML] Credit scoring methods: Latest trends and points to consider
Credit risk is the most significant risk by impact for any bank and financial institution.
Accurate credit risk assessment affects an organisation's balance sheet and income …
Accurate credit risk assessment affects an organisation's balance sheet and income …