Case study

Discovering Fraud in Huge Noise

By SymphonyAI team



A major healthcare company (Fortune 500-ranked, global presence) were struggling to analyze their complex, transactional data sets and established a goal to find a robust solution partner to make them more dynamic in their analysis capabilities.

The over-payment of erroneous claims coupled with the resultant loss of interest from delayed collections, was having a detrimental financial impact which was unsustainable and particularly damaging to their revenue streams. Even with an acceptable level of fraud discovery, the organization still struggled to produce a behavioral model that
could be used for a variety of situations. They needed help to refine their models and lacked the in-house expertise to identify new indicators of fraudulent activity.

Ultimately, their desire was to become smarter, faster and more effective in processing their data sets to minimize fraud and the potential abuse of their products.

After a successful Proof of Concept, the platform implementation highlighted the following key findings and deliverables:

  • Existing methods produced too many claims leads
  • Discovered key characteristics of types of unfavorable behavior from submitted claims
  • Conservative savings of $6 million a year by recovering lost fraud dollars
  • 7x faster turnaround time on lead generation

About SymphonyAI

SymphonyAI is building the leading enterprise AI company for digital transformation across the most important and resilient growth verticals, including retail, consumer packaged goods, finance, manufacturing, media, and IT service management. SymphonyAI verticals have many leading enterprises as clients. Since its founding in 2017, SymphonyAI has grown rapidly to 2,000 talented leaders, data scientists, and other professionals. SymphonyAI is an SAIGroup company, backed by a $1 billion commitment from Dr. Romesh Wadhwani, a successful entrepreneur and philanthropist.

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