With the right approach, your quote pipeline becomes not only manageable but a vital source of competitive advantage.
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We sat down with Porsche Westlake’s Service Director, Sam Abregel, to address 8 categories of warranty fraud to watch out for. Given the vast amount of transaction data and the presence of anomalous patterns indicating fraudulent activity in these categories, there is a huge opportunity to harness predictive analytics and machine learning models.
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 abnormal behaviors in data that signal threats of risk and fraud.
As the volume of online transactions continues to grow exponentially, there is a new quest for enterprises to start new channels of business, gain more online presence, retain existing revenue streams, and stay relevant to current technology. Many organizations are unable to detect patterns related to Fintech fraud because they are stuck doing traditional rule-based approaches. Emerging modern technologies, like NEMESIS, use the power of AI and machine learning to fight against financial fraud.
Fraud isn’t something new, but it is becoming more complex and sophisticated. From bribing exam administrators to CFOs conducting unethical transactions, these five fraud cases were some of the most shocking for 2019.
