Corporate fraud, a new and distinctive predator

Among the different types of credit fraud, corporate fraud deserves a chapter of its own. Despite representing fewer cases than individual fraud, the blows to credit organizations are more severe and it's even more complex and difficult to detect than individual credit fraud.It is also now growing rapidly, whereas it was once marginal. Like other types of fraud, it is taking full advantage of the evolution of business practices: digitalization, demands for speed, the leasing boom, and so on...

Corporate fraud affects both private and public financiers. It has taken hold of the emergency aid measures put in place by the States to combat the crisis in Covid-19 (partial unemployment, solidarity funds, guaranteed loans, etc.). And it now affects all products that can be the subject of business credit (vehicles, industrial equipment, computers, etc.), with a particular focus on the automotive sector.

• What are the particularities of this devastating yet still poorly understood fraud?
• What can Artificial Intelligence (AI) and Machine Learning (ML) solutions do against this unique predator?

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Figures

• Reports of suspicious use of French state emergency schemes have increased +16% per year according to Tracfin
• The average amount of fraudulent partial unemployment files transmitted is 260 000€ by Tracfin on December 31, 2020 (Source : Challenges)

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Summary

1. Introduction: Corporate fraud - devastating and well-camouflaged
2. The phenomenon: The pitfalls and particularities of corporate fraud
3. Solutions: Fighting corporate fraud
4. Conclusion: The time has come to approach corporate fraud differently

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