Business
Challenge:

  • The client is a technology giant and the worldwide leader in software, services, and solutions. They rely on their partner organizations across the globe to promote, expand, and retain their business.
  • The client runs a Skills Initiative program to promote the sales of their cloud-based products by providing training to customers across the globe through partners. They pay subsidies to partners every month based on the volume of training activities reported.
  • A huge surge in the volume of training activities was observed towards the end of the fiscal year. The client paid out a huge subsidy to Partners for the reported training activities.
  • The paid-out subsidy was way higher than the estimated budget.
  • This called for an audit of the training data reported by partners to check for any inconsistencies.

TurnB Approach

Decided on key areas to conduct the audit

Identified areas with a potential for data inconsistencies.

Checked for inconsistencies in each identified area by analyzing training data reported by partners.

Shortlisted key areas with significant inconsistencies to perform an audit.

Conducted a pilot study

Selected the top 5 cases of inconsistency from the shortlisted areas and decided to perform a sanity check with partners.

Reached out to partners and collected additional documentation to support the authenticity of the training conducted.

Validated cases based on the documentation and authorizations provided by partners.

Extended audit and calculated subsidy impact

Discussed the outcome of the pilot study with stakeholders.

Decided to extend the audit to the top X cases, covering 50% of the financial impact.

Reached out to partners representing the top X cases.

Confirmed unauthorized ones based on supporting documents from partners

Calculated the total subsidy impact for unauthorized trainings.

Implications

Confirmed an over-reporting of trainings worth $1 million in subsidy impact.

Clawed back $500K from partners (50% of total) from payments approved in the current fiscal year.

Identified a few data discrepancies with the client’s internal data, which led to the development of a more reliable internal data source.

Additional automated checks and business rules were put in place, developing a more robust validation mechanism.

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