• Thirumalasetty Vijay Kumar, Prof.Syeeda Mujeebunnisa

Let’s be real—everybody’s kinda obsessed with catching financial fraud these days. Banks, companies, regular people scrolling through their bank statements—nobody wants to wake up to “surprise, your money’s gone!” The old-school setup, you know, those rule-based systems that flag stuff like “Hey, this guy just spent $2,000 at a pet store in another country,” aren’t really cutting it anymore. Scammers have gotten clever, and honestly, those systems miss a ton. Tons of false alarms, too. It’s like your bank crying wolf every five minutes, and then missing the actual wolf entirely. So what’s the fix? Lately, everyone’s been buzzing about machine learning. Basically, it’s like giving your fraud detection tools a brain—or at least a pretty good fake one. These algorithms chew through mountains of data, spotting weird patterns you’d never catch with just a checklist. Supervised learning, unsupervised learning, deep learning—all the buzzwords, but they actually work. Banks can look at years of data, find stuff that screams “fraud,” and then catch it when it pops up again. And, yeah, all the experts keep saying—if you don’t get this right, people stop trusting the whole system. Money vanishes, faith vanishes, everything just crumbles. So, machine learning isn’t just a nice upgrade. It’s kinda essential if you don’t wanna get left behind—or robbed blind.

Credit Card Fraud Detection

"Machine Learning Approaches for Credit Card Fraud Detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.c53-c61, July-2025, Available :http://www.jetir.org/papers/JETIR2507208.pdf

"Machine Learning Approaches for Credit Card Fraud Detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. ppc53-c61, July-2025, Available at : http://www.jetir.org/papers/JETIR2507208.pdf