Integrity in analytics

In Assurance

EY Forensics professionals have an analytics platform for monitoring and managing external and insider risk.

What EY can do for you

As more stakeholders — vendors, suppliers, distributors, retailers and sales teams — use digitized technology, such as automated operational processes, real-time data analysis, and digital payments, the risk landscape is changing too.

EY Forensics has an analytics platform for monitoring and managing external and insider risk. It applies a six-step process:

  • Data collection and validation from all sources relevant for the client
  • Data completeness checks to help confirm the quality of data obtained 
  • Data mapping from the client’s system to the unified data model
  • Data analytics based on select parameters
  • Risk scoring for transactions 
  • Case management capability to handle the exceptions noted

This framework includes process automation to facilitate case investigations, internal audits and data management, and collaboration, which can highlight vulnerabilities and workflow improvements.

Once the risks identified are mitigated, companies must continue to monitor activities and measure the effectiveness of the anti-fraud measures. A risk management framework needs to be institutionalized to identify threats in the form of red flags. However, regular independent analysis is required to uncover new loopholes and workarounds.

Some practical examples

EY teams have used point of sale (PoS) data mapping and analytics to identify potential fraud in stores spread across multiple states within the US. By breaking down, we can identify activities by region, store, product, type of sale (cash or card) and cashier, suspicious activities ranging from pilfering — where goods or cash go missing — to large-scale leakages.

By highlighting patterns in customer or employee behavior or unusual activities, data analytics can identify the possibility of an individual store or cashier being targeted by organized crime.

For example, EY professionals developed a PoS analytics tool for a global coffee retail chain using forensic analysis to risk-score activities and identify problems within stores in terms of misuse by staff.

The tool runs analytics across data sets, including the number of complimentary cups and the number of staff “freebies” against the number of transactions per day. It then scores the results to identify which store presents the highest risk of losing revenue through this type of staff conduct. Risk analysis is applied to geographic regions, stores, employees and transactions. 

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