Background. Property and casualty insurers score claims for fraud risk under conditions that shift as organized staged-loss rings adapt, genuine claims behaviour evolves, and seasonal catastrophe activity moves claim volumes. Guria et al. argue that...
Artificial intelligence (AI) can match specialist accuracy in cancer detection, yet adoption in clinical practice remains limited because most high-performing models are opaque, poorly calibrated and trained on data that cannot be shared across...
Machine-learning models for breast-cancer cytology are rarely published in a form that others can rerun, and their explanations are rarely checked for stability. This study develops a reproducible, configuration-driven pipeline — automated preprocessing,...
Financial fraud detection is a moving target: fraud tactics, legitimate consumer behavior, and the statistical relationship between transaction features and fraud risk all shift over time, so a model that is accurate on the data it was trained on can...
Computer vision has emerged as a transformative technology in citizen science, enabling automated analysis of images and videos at scales that would be impossible through human effort alone. This review examines the role of computer vision in citizen...
Background. Buy-now-pay-later (BNPL) lenders approve or decline loan applications in real time, and the fraud patterns those decisions must catch change as fraud rings adapt, genuine applicant behaviour evolves, and seasonal demand shifts. Guria et al....
Large enterprises continue to operate substantial estates of monolithic, tightly coupled applications even as cloud-native microservices, intelligent data pipelines, and zero-trust security models have become the accepted architectural baseline for new...
Temporal drift detection is well established in research, but fraud teams that deploy it face practical questions that research benchmarks rarely answer: how often the tests will raise false alarms, how large a shift they can see, whether they detect...
Federated learning allows multiple financial institutions to train a shared fraud-detection or financial-distress model collaboratively without any institution exposing its raw transaction or account data to the others, a privacy-preserving property that...
On April 17, 2026, the Federal Reserve, OCC, and FDIC jointly issued SR 26-2, Revised Guidance on Model Risk Management, which supersedes both the foundational 2011 guidance (SR 11-7 / OCC Bulletin 2011-12) and the 2021 interagency statement on BSA/AML...
Data quality assurance is a critical but resource-intensive component of citizen science projects. As project scale and data volume have grown, traditional expert-based quality assurance approaches have become increasingly inadequate, creating a need for...
The main aim of the International Journal of Modern Computing (IJMC) is to publish refereed, well-written original research articles...
Haleema Tayyab
Awan Tower, Peshawar, Pakistan
Monday – Friday, 9:00 AM – 6:00 PM (PKT)
For manuscript status queries, please contact the relevant journal's editorial team directly rather than the general office.
