Catch Me If You Can: Fighting Fraud With Blockchain

Fraud impacts organizations of all types and sizes across a wide range of industries and geographies.

In 2018, firms worldwide lost more than $7 billion to internal fraud schemes, according to a "2018 Report to Nations," by the Association of Certified Fraud Examiners - which analysed 2,600 real cases of occupational fraud from companies across 125 territories and 23 industries.

Addressing the risk of fraud is a key challenge for all organizations.

Employees working in organizations transacting in digital currency would therefore find it very difficult to tamper with payment records, thereby preventing many asset misappropriation schemes such as theft of company assets - which, according to the ACFE, represented 89% of reported fraud cases.

In this context, blockchain could be very effective in addressing financial statement fraud schemes, which involve overstating assets, revenues and profits, and understating liabilities, expenses and losses - costing organizations a median of $800,000 per case, according to the ACFE report.

According to PwC's "Global Economic Crime and Fraud Survey 2018" - which gathered data from 7,200 respondents across 123 different territories - usage of a blockchain-enhanced system for information exchange may help to reduce the risks and costs to reputation of senior managers committing fraud.

Currently, organizations address fraud by establishing a code of conduct, engaging with external auditors and providing authority to internal audit teams.

Employing the use of data-monitoring tools and analytics also contributes to lower losses and faster detection of fraud cases, as reported by the ACFE. However, the ACFE report also cited the most common method of initial fraud detection did not rely on technology at all, but through employee tips and whistleblowing, representing 40% of cases.

Blockchain is therefore not likely to solve all types of fraud, especially those that take place primarily offline, nor does it serve to detect or predict when fraud takes place.

The technology's tenets serve as a significant fraud disincentive and data integrity enforcement tool that can be used to tackle real problems, such as protecting migrant workers from corrupt employment practices and preventing tampering in real estate investment transactions.