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Financial institutions have continued to fall victim to trade finance fraud while an industry-wide solution has remained elusive. Ronen Cohen, VP of strategy at Duality Technologies, discusses how lenders are now navigating data privacy barriers to define new approaches.
Duplicate financing fraud is the financing of the same or similar invoice multiple times, and it’s a problem that has plagued the trade finance landscape for decades. However, challenges around collaboration driven by privacy regulations and competition have so far prevented financial institutions from finding an effective solution.
These tactics have featured in several high-profile cases, including the collapse of Singapore oil trader Hin Leong in 2020, which led to more than 20 banks losing some $3.5 billion. As a result, some banks eased their trade finance activity while others exited the market altogether.
All this adds pressure to an industry in which regulatory capital constraints have already restricted banks’ ability to lend.
One of the reasons the trade finance gap has widened – and now stands at $1.7 trillion, according to the Asian Development Bank – is that lenders are also having to keep more collateral as a contingency for fraud.
As such, duplicate financing is a problem that affects not only lenders’ revenue but also businesses’ access to capital and wider economic growth.
The data challenge
Inter-bank collaboration is vital. A major factor in trade finance fraud is the inability to share the appropriate data between lenders in a timely manner.
Financial institutions need access to information across siloes – whether internally across borders or externally from other providers – so that they can collaborate and jointly analyze it to derive insights.
The problem is they only share that data if they can preserve privacy, confidentiality, regulatory compliance, and competition.
Too much transparency would fuel competitive concerns, as revealing details of a key account, for example, could expose valuable information to the market.
Firms must also respect their country’s privacy and financial sector laws, which in some cases prohibit them from declaring they have a business relationship with a specific party – which is the case in countries like Hong Kong and Singapore.
Solutions have emerged to help tackle duplicate trade finance fraud and many are blockchain or hashing based.
With blockchain, however, the problem is that its key benefit is also its downfall – transparency.
Even in a closed network, any participant can see the data being shared, which compromises privacy and security, and reveals information about competitors’ customers and transactions.
As a result, trade financiers are reticent to join blockchain initiatives or avoid adding their most valuable data, making the solution incomplete and ineffective. Essentially, blockchain does not adequately address these regulatory and competitive concerns, which hampers how effective these solutions can be.
Alternatively, hashing has enabled simple comparisons, but the problem is it is easy for criminals to circumnavigate these checks.
A fraudster trying to hide duplicate financing can easily use different purchase order numbers or change data across documents to make them seem different and evade searches for matches or similarities.
Firms need technology that is fit for purpose and able to detect the more complex tactics that criminals deploy.
While there is some preliminary data sharing focused on invoice numbers and parties to a transaction, there are not any mechanisms to share additional risk indicators or fraudulent patterns.
This is important because a real fraudster – or a "good" company turning “bad” – can easily manipulate invoices to make them seem unique.
They cannot, however, manipulate transaction and lending patterns, which could be indicators of duplicate trade financing and other high-risk activities.
Protecting data privacy
If financial institutions could have the privacy and security guarantees that enable them to protect their data and users, as well as ensure regulatory compliance, they would be more open to sharing information.
A new approach has emerged that is already proven in preventing, detecting and investigating a variety of financial crimes – privacy enhancing technologies (PETs).
In trade finance, the PET with the most potential to tackle fraud is homomorphic encryption, which allows financial institutions to perform computations on encrypted data without ever decrypting it first.
This means they can share and analyze sensitive data without revealing the underlying information.
Using homomorphic encryption software deployed in a “hub and spoke” model, one lender who receives a financing request can ask others if they have already financed the same deal and gain insights into any potential duplicate activity.
The data itself remains decentralized so does not move across parties.
Homomorphic encryption also means the lender’s customer relationship is never revealed and any answers cannot be attributed back to a specific financial institution, thereby preserving competition.
Regardless of the specific technologies, what’s clear is the trade finance sector is undergoing a significant stage in its evolution.
Digitization is accelerating and will prove pivotal in helping financial institutions tackle lending constraints and the continual threat of fraud.
But it is collaboration that stands to have the greatest impact – and in this data-driven world, technology is finally emerging to enable this in ways that have not previously been possible.