Healthcare Fraud Mitigation and Investigations: Impact of AI
In this article published by Financier Worldwide, BDO provides an overview of the scale of fraud in the healthcare sector and describes the nature and scope of the problem. Healthcare fraud can be categorized by internal fraud (employees), external fraud from consumers and companies defrauding the government. There is a lot of incentive for individuals as well as organizations to misbehave. While many organizations are operating on a global scale and increasing their reliance on data and technology, healthcare fraud is at an all-time high.
There are many different types of healthcare frauds that are typically perpetrated, and methods are evolving. Medical coding fraud, kickbacks, drug diversion and false claims are some of the most common healthcare fraud schemes. Many of these schemes share patters, though some have evolved with new twists.
As a highly regulated sector, healthcare has traditionally had strong monitoring and detection embedded in its culture. Compliance departments have built robust programs focusing on risks and processes. The rise of advanced technology and artificial intelligence (AI) is providing a new arms race between compliance officers and bad actors. There are many use cases for how AI is helping to detect healthcare related scams. Transactions monitoring is a mature use case that leverages ML models to detect anomalies in large data sets. The considerations for using AI for fraud prevention are generally the same as for those for implementing AI for any other use case. Data privacy and security, bias, transparency, and regulatory compliance top the list.
While the Healthcare industry is very excited about the possibilities that new technologies bring to bear, there are many pitfalls. It is important to define the use cases that are going to be the most beneficial to an organization and understand their specific risks. Looking ahead, there are many innovations we may expect to see in AI technologies to combat new healthcare fraud threats. Some of the most exciting innovation has do with human and machine interaction. Layering in an LLM chatbot over a compliance dashboard brings incredibly powerful analytics to people who otherwise might lack the skills, training, or accessibility to consume these results.
The article originally appeared in the July 2024 issue of Financier Worldwide
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