The advent of Telehealth and Telemedicine have resulted in a proliferation of these instances. How do we deal with this altered environment? How do we stay ahead of the curve of emerging new fraud strategies?
Avijit Datta
The advent of Telehealth and Telemedicine have resulted in a proliferation of these instances. How do we deal with this altered environment? How do we stay ahead of the curve of emerging new fraud strategies?
Fraud has been causing rising challenges for businesses. Over 72% of businesses cite fraud as a growing concern, and about 63% of businesses report the same or higher levels of fraudulent losses over the past 12 months a
Fan Yang
Fraud has been causing rising challenges for businesses. Over 72% of businesses cite fraud as a growing concern, and about 63% of businesses report the same or higher levels of fraudulent losses over the past 12 months according to a report by Experian Global. The challenge is not just about preventing fraud, but figuring out how to predict it before it happens, so it can be prevented from happening at all. But before we make strategies to combat fraud, it’s important to understand the barriers associated with fraud detection strategies.
Healthcare claims are an inviting and alluring target for fraudsters due to their huge monetary value. In 2017 alone, HHS and DoJ recovered around 2.5 Billion Dollars in claims fraud. And that is just one year. The ch
Sierra Seabolt
Healthcare claims are an inviting and alluring target for fraudsters due to their huge monetary value. In 2017 alone, HHS and DoJ recovered around 2.5 Billion Dollars in claims fraud. And that is just one year.
The challenges facing healthcare payers are manifold as they try to tackle the rampant and growing problem of claims fraud. From high dollar impact, billing compliances to the high cost of manual investigations, the health care providers are sweating. So what exactly is Healthcare Fraud? And how can we try to mitigate them using technology?
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.
