Search Results for: health insurance

Several key insurance carriers began to experiment with AI in the last decade, including Progressive, All-State, and State Farm. Although not as large as the banking and retail industries, the AI vendor landscape in insurance is growing.

The insurance industry is responsible for a multitude of sensitive financial data concerning both its customer base and staff. Any breach to an insurance company's CRM or other claims database could compromise the personal data of multiple people at once, which puts the company at risk as well.

Customer data is essential for insurance firms to stay competitive in the coming decade. Insurance companies at present have backlogs of data on past and existing customers in the form of policy agreements, applications, and claims forms. They’ve also collected millions of images showing car damage, property damage, and personal injuries.

There are many possibilities for automation in the healthcare industry outside of AI. Robotic process automation (RPA) technology can serve healthcare companies with various use cases involving data transfer and clinical documentation. Moving important information from the business’ frontend to their deeper business processes is among the most common use cases for RPA in healthcare, and many other solutions emerge from this idea. A similar phrase and field to RPA is called White Collar automation and readers can find a full interview on white collar automation in healthcare today here. 

The healthcare industry holds perhaps the most responsibility of any industry when it comes to ensuring data privacy. A breach in electronic medical records (EMRs) could tarnish a healthcare company's reputation, put undue stress on patients, and render the company in violation of regulations.

In recent years, the demand for greater cybersecurity has risen even among the everyday citizen. This is especially true for one’s personal and financial information, which fraudsters are constantly finding new methods of breaching accounts to find. This need for security has also risen in insurance, and numerous AI firms are selling claims fraud detection solutions to the insurance sector.

Although one might assume healthcare companies are investing the most amount of money into AI for R&D efforts, such as clinical trials, drug discovery, and surgical robotics, the top healthcare companies don't seem to be publicizing their efforts if they are.

Various use cases and applications for AI and machine learning in the healthcare industry are proposed more frequently now than ever. Healthcare leaders may find it difficult to keep up with where AI is being applied in their sector.

Machine learning has far-ranging applications in the finance space broadly from document digitization to document search, chatbots to fraud detection. The insurance space in particular, however, stands to benefit from AI and machine learning applications in a few unique ways. They could help insurance firms with a challenge that’s at the forefront of the insurance world: attracting and meeting the needs of millennial customers.

Episode Summary: There's a lot of venture money pouring into artificial intelligence in healthcare. From pharma to hospitals and beyond, the potential applications in healthcare are promising.