Analytics, Anomaly Detection, Fraud Detection, Predictive solutions

Fraud Schemes to Watch Out For in 2023...

Financial Services in 2023 will face a greater threat from fraud than ever before. Cybercriminals will increasingly use sophisticated techniques to exploit vulnerable systems, with attacks becoming more advanced and hard

Donna Sanchez

Financial Services in 2023 will face a greater threat from fraud than ever before. Cybercriminals will increasingly use sophisticated techniques to exploit vulnerable systems, with attacks becoming more advanced and harder to detect.

Anomaly Detection, Financial Services, Healthcare, Insurance, IT, Machine Learning

Why Anomaly Detection is Important...

With data driving most business transactions, it is essential to analyze and interpret patterns in behavior correctly. NEMESIS, an anomaly detection tool powered by machine learning, can detect and predict against abnorm

Sierra Seabolt

With data driving most business transactions, it is essential to analyze and interpret patterns in behavior correctly. NEMESIS, an anomaly detection tool powered by machine learning, can detect and predict against abnormal behaviors in data that signal threats of risk and fraud.

AI, Anomaly Detection, Fraud Detection, Growth Opportunities, Machine Learning

Anomaly Detection – A Machine Learning Solutio...

With the rapid growth of the internet and the IoT and the resultant digital transformation of the world we live in, there is an explosion of data that is being generated, collected, and stored. There is data available f

Darshana Daga

With the rapid growth of the internet and the IoT and the resultant digital transformation of the world we live in, there is an explosion of data that is being generated, collected, and stored. There is data available for “normal” transactions, as well as for the fraudulent of interest to a company. If one could successfully analyze this data and gain meaningful insights and draw conclusions from it, it would be possible to use that insight for reducing the threats and risks against organizations.