Could Blockchain Have Prevented Scandalous Banking Fraud

While digital banking systems have built capacity for large transaction volumes and payment efficiency, fraudsters have found novel ways to execute scams. Case in point, the US$ 1.4 billion Nirav Modi case involving India’s Punjab National Bank (PNB). The loophole exploited by Nirav Modi makes a fitting case for the application of blockchain smart contracts to predict and prevent fraudulent activities. Industry experts suggest that blockchain technology in Insurance can be  used to manage transactions and accounts could have prevented or detected such a scam in its infancy. 

A Brief Insight into the PNB Bank Scam

The scam was based on the issuance of fake letters of undertaking worth ₹11,356.84 crores (US$ 1.4 billion) for the benefit of Nirav Modi, an Indian diamond retailer. The diamond entrepreneur who goes by the same name had the support of a former PNB employee, Gokulnath Shetty. Allegedly, Shetty had issued numerous fake letters of understanding (LoU) or letter of credits (LoC) without collateral for Nirav Modi for seven years. 

According to the bank officials, rogue employees had bypassed the lender’s internal messaging system called CBS (Core Banking System) to avoid detection. They placed messaging instructions via the SWIFT global payment system and requested Indian banks’ overseas branches to pay the cash as loans. 

PNB bank was using different ledgers to manage the information settlement mechanism SWIFT and the payment settlement mechanism CBS. While a bank’s internal control uses the CBS for validating transactions, regulators use it for inspection and various audits. 

How a Private Blockchain-based Reconciliation Solution Could Have Been Effective 

According to blockchain experts at Oodles, a private blockchain network facilitates only permissioned auditors, regulators, and payment processors to access real-time transactions. Had PNB bank implemented a private blockchain solution to reconcile its SWIFT payments, such a fraud would not have happened. Such a solution could have immediately detected any malicious transactions from occurring. It would have looped in all stakeholders to verify that the payment settlement information is genuine and loan requests are backed by substantial collaterals. In addition, regulators and auditors could have also managed to readily access all transaction details from end to end. 

With trained machine learning algorithms, blockchain can also provide a solution to detect fraudulent patterns. It can secure all processes with cryptography mechanisms and an immutable ledger. It makes forging documents or information almost impossible while ensuring non-repudiation. 

Relevant Reads: How Private Blockchain Solutions Reinforce Business Processes

How Blockchain Smart Contracts Could Have Prevented the Fraud

In this public sector bank fraud, a blockchain smart contract could have prevented the fake issuance of LoUs. It would have detected inconsistencies during automatic reconciliation with the core banking system (CBS). It also would have denied the payment initiation over the SWIFT network by following the defined limits.

Smart contracts inherently eliminate the dependency on intermediaries and facilitate real-time transaction execution. In the banking context, a smart contract is a program that can enable banks to automatically facilitate, verify, and enforce the negotiations of a deal. Also, it can enable efficient audit trail and procedural compliance while ensuring that all stakeholders share collective intelligence. 

Conclusion

For sure, we can’t refer to blockchain technology as the panacea for all the banking industry’s challenges today. However, given the blockchain’s potential, industries globally are eying on how to integrate their legacy systems with it. Our blockchain application development and consultancy services might help you find loopholes in business processes and optimize them with blockchain.

For the banking industry, it is the best time to embrace a revolutionary technology like blockchain.