Employing data analytics for anti-corruption measures is a strategy that many firms are adopting at an increasing rate.
The reason: businesses deciding to digitize and digitalize due to the pandemic, thus cases of frauds, embezzlement, money laundering, and bribery observed a drastic boom.
Discover how data analytics for anti-corruption measures are being utilized by businesses.
For accurate results to be generated through data analytics, it requires one critical component: data.
So, gathering data from different sources such as financial records, employee and customer data, annual reports, and anything else that holds information is crucial.
Along with this, simply having access to data is not enough. Before gathering analysis, the data must be cleaned and prepared.
Here are the 4 types of data analytics engaged in fighting the different types of corruption.
Anti-Corruption Measures with Descriptive Analytics
By analyzing historical data and developing statistical models, trends and patterns can be observed over time. The priority is to measure deviations from normal behavior.
For example, each department has a predetermined budget allocation. If the expenditure towards one component does not follow the pattern and witnesses a sudden increase or decrease, then it could be a sign of embezzlement.
Anti-Corruption Measure with Diagnostic Analytics
Beyond simply identifying anomalies in behavior and trends, finding the underlying reason behind them is important to create preventive measures. Thus, conducting root cause analysis becomes easier.
For example, unusually high expenses claimed by employees, or a supplier is being registered for multiple transactions, then finding primary causes are necessary.
Also Read: How Does Technology Help Us to Fight Corruption
Anti-Corruption Measures with Predictive Analytics
Predictive analytics is to determine the possibility of incurring risk and predicting future corruption cases. Every type of corruption has a certain risk associated with them.
A senior employee supporting a known relative for a position holds a different setback to the firm compared to bribery. So, statistical models are developed by assigning risk rank to various stakeholders and their interactions with the business.
Anti-Corruption Measures with Prescriptive Analytics
Prescriptive analytics is, as the name suggests, suggestive corrective measures and improvement strategies to deal with corruption.
By using intelligent insights gained, the optimal strategy can be taken for the targeted area. This would be through regular audits and implementing stricter measures.
Different mitigation measures and their impact on reducing corruption are evaluated to see which strategy delivers optimal results.
Closing Thoughts
By leveraging data analytics for anti-corruption, business can optimally develop strategies to detect, diagnose, predict, and prevent corruption from hampering their venture.
