Loss Prevention Services

Access to data anywhere and anytime

EY Virtual is specifically designed to ingest a wide range of data sources, structured and unstructured, to help companies gain a consolidated view of their risk environment instead of resorting to sampling. The EY data-centric approach does not view a certain level of data quality as a prerequisite for a loss prevention project. Instead, data quality is viewed as a potential cause of loss that needs to be addressed in the same way as other losses.

Interactive and integrated case management capabilities

Through EY Virtual’s built-in interactive case management tool, investigators can manage alerts and drill into specific risk areas in real time. Users also have the ability to automate certain escalation procedures using workflow tools. The case manager can integrate a wide range of data sources so that information needed for the investigation is available at one central location.

Visual executive dashboard and robust reporting

The EY Virtual executive dashboard helps operational leaders monitor the performance of multiple locations in one consolidated view in real time. Custom reports can be programmed using a robust set of easy-to-use configuration features.

Enhanced, continuous risk assessments

At the core of the EY offering is a library of proprietary, sector-specific antifraud and loss schemes developed from historical incidents. EY teams will also work with you to develop custom approaches based on your unique business model and risk profile. EY teams translate each scheme into machine-learning scoring models. The results are used to detect fraud and loss risks, and determine appropriate remediation efforts. EY teams also monitor remediation activities to drive continual improvement of risk scoring.

Multiple deployment options

Through managed offerings or preferred provider arrangements, EY teams forge long-term relationships with organizations and gain deep knowledge of their risks and potential for recovery. Effective loss prevention programs are developed with remediation measures that leverage both advanced technologies and nontechnical approaches.

Using interactive surveys or in-person workshops, EY professionals help kick off each project by working with business stakeholders to evaluate existing processes and controls, as well as the fraud and loss scenarios for each restaurant. The resulting risk profile is used to build a business case and serves as the basis for loss diagnosis.

Using data from various systems (e.g., POS, billing), EY teams help determine the root causes for various loss categories (e.g., process errors, data manipulation) and quantify risks using AI and other advanced analytics technologies. In parallel, a data- and analytics-based infrastructure is built for ongoing risk analysis and monitoring.

Remediation efforts typically are carried out in a staged approach designed to provide early return on investment. At the end of each stage, remediation results are assessed and used to plan for the next stage. Finally, insights gained from risk analysis and remediation efforts are combined into one comprehensive report, and fed into an ongoing program review and improvement process.

The use of analytics is expanded to provide estimates for total losses from theft and fraud in a given restaurant or chain by physical location, type of employee, promotion or other criteria. The loss quantification function also can be used to calculate losses from franchisee underreporting of revenue, training errors and accounting issues, such as inaccurate cost analysis of menu items and poor inventory management.

Using interactive surveys or in-person workshops, EY professionals kick off each project by working with business stakeholders to evaluate existing processes and controls, as well as loss risks during the meter-to-cash process. The resulting risk profile is used to build a business case and serves as the basis for loss diagnosis. Using data from various systems (e.g., billing), EY teams help determine the root causes of various loss categories (e.g., process errors, data manipulation) and quantify risks using AI and other advanced analytics technologies. In parallel, a data- and analytics-based infrastructure is built for ongoing risk analysis and monitoring.

Remediation efforts typically are carried out in a staged approach designed to provide early return on investment. At the end of each stage, remediation results are assessed and used to plan for the next stage. Finally, insights gained from risk analysis and remediation efforts are combined into one comprehensive report and fed into an ongoing program review and improvement process.

The use of analytics is expanded to provide estimations, by location or customer segment, for the total losses caused by fraud, defective meters and water losses. The loss quantification function also can be used to calculate losses from accounting issues, such as poor data quality, incorrectly applied tariffs, inaccurate estimations and missed invoices.