Independence Blue Cross Uses Big Data to Boost Customer Retention

Independence Blue Cross, a health insurer in the Philadelphia region, has turned to a predictive analytics platform to foresee patterns in patients' health data and gain new customers.

Independence Blue Cross (IBC), a Philadelphia-based health insurer, plans to use predictive analytics to find ways to better retain customers in its health plans.

The insurer is using InsightsOne's big-data platform based on open-source Hadoop to conduct real-time petabyte-scale predictive analytics, the companies announced on May 9.

IBC has been looking to boost the growth of health care IT in the Philadelphia area. The company held a Game Changers Challenge in July 2012 to highlight innovations in health and wellness and awarded a $50,000 grant to telehealth startup 1DocWay.

Big data and predictive analytics are growing trends in health care as providers look to collect data on patient behaviors and outbreaks of diseases to help predict outcomes.

As for IBC, the technology helps them increase their health insurance business.

Predictive analytics is on the rise in the insurance industry, according to a recent survey by Trilogy Insurance & Financial Services and Insurance Networking News. The survey found that insurers use big data platforms for customer segmentation, improving their competitive advantage and retaining their customers.

"Predictive Analytics is key to helping business make informed decisions and identify risks and opportunities," Ravi Chawla, director of informatics at IBC, told eWEEK in an email.

"IBC is leading the way with their use of big data and machine learning, and is really demonstrating their commitment to customer satisfaction," Waqar Hasan, CEO of InsightsOne, said in a statement.

IBC and InsightsOne conducted a pilot in July 2012 that explored how machine-learning technology could help the insurance company identify which customers require proactive outreach so the company could resolve issues for these customers before they need to call the insurer's customer service lines. IBC then began using it more extensively in October 2012.

"These pilots demonstrated that we can more precisely predict customers that may experience service issues and take the necessary actions to ensure they don't have any problems," Chawla said.

By using the InsightsOne software, IBC is also able to identify potential new customers.

InsightOne can use IBC's call center notes, claims and behavior data from consumers and channels to predict customers' needs.

"IBC is combining the power of technology and big data to predict future customer satisfaction issues, so that we can proactively reach out to them to take care of any problems that they may have," Chawla said. "This is part of our customer satisfaction initiative to provide the highest level of service to our members."

The insurer can help identify which of its plans would best suit potential customers by examining claims data, he said.

"We are able to accurately identify prospects looking for insurance and match them to the right product for them as an individual or family," Chawla said.

When analyzing potential customers' health data, IBC is sure to adhere to the Health Insurance Portability and Accountability Act (HIPAA), Chawla noted.

"IBC maintains very high standards for all our information systems and we will only use HIPAA-compliant solutions," Chawla said. "We have strict policies and procedures in place to maintain our members' privacy."

Chawla said a "leap in precision" occurs when analysis of big data is combined with machine learning.

"The use of big data means that much more data can be analyzed and much more sophisticated analysis can be done," Chawla said. "And when combined with machine learning, our ability to detect patterns is increased even further."