Many Silver Bullets: The holistic approach to an improved trade finance environment
Ask the majority of financial institutions today how they are looking to improve their trade finance processes, and digitalisation will be one answer. Robotic process automation and artificial intelligence will be another, along with predictive analytics underpinned by better use of data. All this without mentioning the words distributed ledger or Blockchain.
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Our industry is in a truly unique moment; the mix of emerging technology, data availability and an increasingly volatile geo-political environment, creates the perfect storm for widespread change. However we can only make the most of this opportunity if we take a holistic view of change, across technology, regulation and culture. Many existing initiatives in trade and supply chain finance focus on technology; utilising emerging technology to change the way business is completed (digitalisation) or make the current processes more efficient (digitisation). One of the fundamental reasons most initiatives have not progressed past proof of concept, pilot or ring-fenced networks, is that they do not consider which environment is required for digital trade to scale in a sustainable and safe manner.
The trade arena and the rules that govern it are geared towards paper-based manual processing, and liability being transferred at a set point in time. Implementing a process where there is shared control and liability for intangible digital objects into the current paradigm will result in trust issues across the network. A fundamental reason that robotics will augment human processing instead of replacing it, is the human ability to make decisions when the situation is contextual or ambiguous. If an institution implements fully automated processes without human intervention, and something goes wrong, who is to blame? The bank? The technology vendor? The creator of the algorithm?
According to the recent ICC survey, by 2035 robots are expected to add 20% and 55% to the GDPs of Brazil and China respectively. The same survey suggests only 2 – 8% of jobs in emerging economies will be impacted by robotics. This dichotomy suggests a ‘no one size fits all’ approach. The challenges in emerging economies go beyond the need to automate processes; 60% of SME applications for trade finance in the developing world get rejected and 68% of those SMEs will not return with a further application. In Africa and developing Asia, the estimated gap in SME financing is $120bn and $700bn respectively. These challenges are in large down to the appetite of global banks to do business in these markets, and the lack of liquidity, correspondent banking networks and ability to KYC at a local institution level.
Simply collecting more data also has its drawbacks. As the amount of data available increases, the effort required to collect, store and analyse the data increases exponentially. Currently there are 4bn plus paper documents in circulation for trade, amounting to circa 200bn data fields available to be screened and analysed. However, those fields only add around 1% in value. A process is required to determine the most relevant data to screen, how it should be interpreted and the most efficient means of doing so.
The third area that needs to be addressed is societal. Much of the focus for existing initiatives has been centred on removing paper from the network, where the benefits from a financial institution and corporate perspective are clear. This does not take into account other stakeholders in the ecosystem, such as the carrier companies and customs and port authorities. Let’s take an example; if a customs official has been checking physical documents for their whole career and is suddenly presented with a digital version that has been endorsed biometrically as opposed to using a stamp, what effect would it have? would there be trust in what is intrinsically being seen?
To use a parallel from the consumer space, imagine moving directly from physical cash to ApplePay without going through the journey of debit cards, chip and pin, and contactless payments? All players in the ecosystem need to be brought along the journey to ensure trust is garnered in the end result; hence the digitisation of existing processes is a key part of the move to new, digitalised business models.
Change needs to be viewed holistically and delivered at a technological, regulatory and societal level in order to maximise the unique situation we find ourselves in. At a technological level, delivering automation of processes allows transactions to be processed quicker with less risk, optimising the capital conversion cycle and reduces the cost of transacting for corporates. Effective use of bank and non-bank data allows more comprehensive sanctions screening and KYC capability; reducing the risk of doing business in emerging economies and allowing finance to be more inclusive for SMEs. At a regulatory level, enforced structured data and the delivery of standards that are appropriate for digital transactions will promote adoption across the wider ecosystem. Finally, institutions must lead their own people through the change in business models as well as the other ecosystem players, to ensure trust is propagated throughout the network as new processes are scaled and adopted.
The truth is technology is merely an enabler to improve processes and looking at individual tools in isolation of each other or the wider environment they are being used in will not make the most of the opportunity.