Digitally-enabled data mining approach expands scope of audit opportunities

Customer-centric payment integrity program achieves significant savings for major U.S. healthcare payer

The Challenge

A major U.S. healthcare payer was seeking improved results from its payment integrity program, specifically its data mining practice. Unlike a clinical claims audit that challenges how a provider billed a claim, data mining is used to determine if a claim was paid correctly.

There are many ways that a payment can be incorrect. Updates to a payer’s billing system usually are done manually, a process that is prone to error and can result in incorrect pricing. To address these internal oversights, data mining has become a common practice for all healthcare payers. This work is conducted in-house, or a payer works with a partner like EXL to find and address claims that were erroneously paid.

EXL Health has partnered with the payer for many years and has a long-standing data mining program with this organization. EXL offered the payer a new approach to data mining by combining domain expertise, data and analytics, and proprietary AI-driven models.

Human Ingenuity

Data mining has traditionally been a people-driven process where subject matter experts manually look at data to find and investigate errors. To create an enhanced view of the payer’s claims, EXL Health applied a more data- and analytics-driven approach to data mining. This digitally-enabled model improved EXL’s ability to see the data through a different lens and provided new opportunities to investigate for erroneous payments. Since the EXL analytics team could access and review so much more data, they were able to offer insights that previously were not possible for the domain experts to see.

The team utilized robust analytics using the rules-based and query-based algorithms of EXLMINE™ to identify claims with likely errors and overpayments. Working with this sophisticated selection module, the analytics team determined unexpected fluctuations on the payment trend.

The team could compare data from multiple sources and multiple tables and quickly provide well-informed comparative data. Acting like a GPS system, the EXL analytics team presented a guided path to show where in the data the EXL domain experts should investigate further.

One of the key success factors was the cross-functional hybrid team consisting of a business team with analytics knowledge and an analytics team with business knowledge. These teams were able to understand the needs and nuances of the payer, their data, their systems, and effectively identify data mining concepts.


EXL’s customer-centric, data-driven data mining program has increased the effectiveness, timeliness, and cost savings for the payer. Combining analytics and domain expertise, the EXL team now works with focused data in a more structured fashion. This new approach to data mining has resulted in tremendous growth in payer savings since its inception three years ago.

  • Prior to 2020, the EXL Health team achieved $25 to $30 million in savings for the payer per year
  • Since 2020, EXL has consistently shown 45% growth year-over-year on the savings identified

EXL’s digitally-enabled data mining program continues today at the payer. Its success has contributed to EXL Health expanding its leadership role with other payment integrity programs, including clinical claims audit. EXL Health now is their most preferred vendor for all of their 15 clinical audit review programs, including both pre-pay and post-pay.