• Sudiksha Wandre
• Sudiksha Wandre
• shefali Desai
• Akruti Patel
• Hezal Lopes

There are totally different patterns in fraud. They constantly alter their behavior, necessitating the employment of unsupervised learning. Fraudsters gain access to trendy technology that enables them to commit fraud through internet transactions. Fraudsters build the idea that consumer behavior and fraud trends evolve over time quickly. As a result, fraud detection systems should be capable of detective work on-line transactions as a result of some fraudsters use on-line mediums to commit fraud once and then switch to different techniques. The aim of the projected system is that unsupervised learning could be a technique of learning that doesn't need direction.Credit cards that acknowledge the importance of accelerating individuals' shopping for power and allowing them to fulfill their daily wants, like vesture and technology with the rising use of credit cards, the frequency of CC (credit card) scams has skyrocketed. The largest credit card frauds area unit outline because the unethical use of credit cards by hackers or credit card users United Nations agency refuses to pay back the number owed. Credit card scams are also discovered by analyzing credit card purchase trends and exploiting historical information. This information analysis will assist banks and different businesses. As the bank doesn't provide information of customers .The aim is to take data sets from local sources and look for anomalies in patterns of fraud activity that have changed over time supporting this data back in time. A competent fraud notification system ought to be ready to detect the following forms of fraud. The fraud group action ought to be exactly recorded, and also the detection ought to be straightforward.

Credit card fraud detection, classification, KNN, Naive Bayes Machine learning algorithm.

"Cerdit Card Fraud Detection using Knn & Navie Bayes Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.e137-e142, April-2022, Available :http://www.jetir.org/papers/JETIR2204420.pdf

"Cerdit Card Fraud Detection using Knn & Navie Bayes Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppe137-e142, April-2022, Available at : http://www.jetir.org/papers/JETIR2204420.pdf