WHAT IS EMPLOYEE FRAUD?

The way to credibility.

Employee Fraud (EF) service is about identification of employees/candidates at higher risk of counterproductive work behaviors (CWBs) that are harmful to the organization and/or co-workers. Early identification of such employees/candidates enables the company in advance to take steps to prevent undesirable financial losses and harms to company’s reputation in the eyes of existing and potential customers and general public.

For identification of employees at increased risk of CWBs data mining, machine learning and artificial intelligence techniques are used. It is a set of mathematical tools used for analysis of large volumes of data and finding of hidden connections and regularities in them. Input data into mathematical models used in EF service can be – besides psychometric data - work related and other information ordinarily collected by companies’ HR departments (job performance, KPI, number of absences, average number of hours worked per week, educational level, average monthly wage, number of years in the company, previous career, age, gender, number of dependent children, etc.)

For companies using EF service there is (with exception of situations when also psychometric data are used) no need for financing and organizing separate and specially targeted data collection because they can use already existing “operational data” generated as a byproduct of routine HR processes. This continuous data acquisition allows incessant updating of a database of historical data on which are based mathematical models identifying employees at high risk of CWBs This fact ensures that mathematical models will reflect the most up-to-date factors associated with CWBs, so taken steps and interventions will be most effective.

HOW WILL EMPLOYEE FRAUD HELP YOUR COMPANY?

• Early identification of employees/candidates at higher risk of CWBs
• Identification of the major factors associated with higher risk of CWBs
• Minimal costs associated with implementation of the system and setting its parameters
• Continuous adaptability of the system and its regular updating

USAGE OF EMPLOYEE FRAUD

• Pre-selection of suitable candidates with respect to the risk of CWBs
• Possibility of targeted (overall or individual) interventions in order to prevent CWBs
• Prevention of adverse financial losses
• Maintenance of company’s reputation