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Who’s Bogus? Catching Fraudulent Firms in Delhi

Institutions & Governance India

Photo credit: Adobe Stock Images

A common VAT tax evasion strategy in low ​compliance​ environments ​involves “bogus” firms set up for the purposes of fraud — they generate false paper trails and sell fake receipts to real firms, so that those “costs” can be subtracted out of what the firms owe the tax authority in VAT taxes. While the scope of revenue loss from this type of fraudulent activity is inherently hard to track, officials in Delhi suggest that the government may be losing as much as $300 million. ​Identifying these fraudulent firms would be an important step to helping recover this lost tax revenue, but locating them is a problem for tax administrators with limited capacity. The Delhi tax authority typically identifies ‘bogus’ firms by visiting the physical site to see if the firm is conducting legitimate business. However, the tax authority cannot physically visit all of the firms that they have flagged as potentially fraudulent, thus many bogus firms continue to write fake receipts to real firms.

Researchers have designed, and are currently implementing, a machine learning tool to more efficiently identify these fraudulent firms in Delhi. The machine learning algorithm is trained on data from firms the Delhi tax officials have already audited, including whether they were found to be fraudulent. The authors then ran a proof of concept test: would the algorithm have identified more fraudulent firms correctly if it had been deployed to target audits, compared to the status quo inspection decisions of Delhi tax officials?

The researchers found that if the tax administration had used the algorithm to predict which firms were fraudulent to target their physical inspections, they could have prevented enough VAT tax evasion to increase revenue by an estimated US$15 – 45 million (Mittal 2018). Given the successful proof of concept, the researchers have received active expressions of interest from the tax authorities to adapt this tool to deploy in two Indian states.

Researchers
Partners
  • The Delhi Revenue Authority
Timeline

2017 — ongoing

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