Corporate Governance and Fraud Prevention: Enterprise-wide view of fraud in India

In our view, an enterprise-wide view of fraud is the future of fraud prevention.

Organisations in India have traditionally relied on surprise checks and audits on random samples to determine the risk of fraud, misconduct, and non-compliance. Now, with data mostly residing in IT systems, Indian organisations are increasingly moving to a framework that relies on deploying technology to determine fraud in its infancy. To achieve this objective, organisations need to adopt advanced technologies that incorporate data visualisation, statistical analysis, text mining, and voice searching concepts that can be applied across data sets from disparate sources.

Organisations would require an interface that seamlessly integrates data from disparate complex systems to run a combination of rule- and AI-based analytics to detect anomalies as part of the on-going transaction monitoring. An enterprise approach can improve efficiencies in investigations as organisations would no longer be required to manually gather data from multiple systems and integrate the data. The data can be aggregated and integrated into one platform and the time saved could be spent on analysis.

Below are some considerations to ensure a smooth shift to an enterprise-wide fraud prevention platform:

1. Building a business case: Given the mixed outcomes from organisations that have embarked on enterprise-wide fraud prevention programmes, there is a need to clearly outline expectations from the programme and communicate its expected benefits to the management. This should include aspects such as improved visibility on red flags and reduced efforts towards data gathering, which can now be invested in analysis and fraud prevention.
2. Seeking the right expertise: Implementing an enterprise-wide framework can be difficult considering the elements involved, including the selection of the right tools. Risk and compliance leaders should consult with third-party experts on their experiences with various tools prior to selecting an implementation partner.
3. Building in-house expertise to run such a platform: The success of this framework depends on the knowledge and experience of users interpreting the results. Implementation of an enterprise-wide framework should be followed up with training users in the framework.
4. Being realistic about the turnaround time for meeting expectations: There is a perception that integration of data is easy and results would be seen immediately. Overnight adoption of any new framework/technology is not realistic; organisations should initially focus on success through a series of pilot projects.

Conclusion

Mining big data can be a powerful tool in managing compliance. There is a growing need to integrate both, structured and unstructured data, and perform advanced analytics to prevent suspicious and fraudulent transactions. Integration of data is an important step, which would require considerable time and effort. There are several plough-in tools available in the market; however, organisations should understand that the key challenge lies in proper implementation. Therefore, a customised and scalable interface (supported by a subject-matter expert with successful implementation experience) complemented into the solution is the need of the hour for organisations looking to invest in an enterprise-wide fraud risk management framework.