November 2017

Evolving technology is creating more and more data – more than we know what to do with. David Meynell examines the what this means for trade finance and how the the right identifiers can support KYC compliance and fraud prevention

According to Chaos Theory, a butterfly fluttering its wings on one side of the world can cause a hurricane on the other side of the world1 . If the butterfly had not fluttered its wings at just the right point in space/time, the hurricane would not have happened. A more rigorous way to express this is that small changes in the initial conditions lead to drastic changes in the results2 . Imagine this effect magnified many times over and one can, perhaps, begin to imagine the impact of big data.

It is increasingly evident that we are on the cusp of a dramatic change in the world of trade finance. Digital developments are now announced on an almost daily basis. But it must not be forgotten that, as basic as it may sound, the key to real transformational change will be dependent on efficient and effective data management. But what is transformation? It can be defined as a marked change in form or nature.

King Data

Christine Legarde
IMF MD Christine Lagarde says this is a world where data is king (Image source: Wikipedia)

Depending on the sources used, it is estimated that as much as 99% of all available data has been generated in the past two years. As pointed out recently by Christine Lagarde, IMF Managing Director, this is a world where data is king. 

The founder of the World Wide Web, Tim Berners-Lee, had never been in doubt about the importance of data. He opined that data is a precious thing and will last longer than the systems themselves. He went on to express the opinion that it’s difficult to imagine the power that we will have when so many different sorts of data are available. An executive of Gartner made a particularly prescient comment some years back, when he stated that information is the oil of the 21st century, and that analytics is the combustion engine3 .  His reference to analytics highlights the critical issue that there is so much data – how can it be handled and what can we do with the data?

Over a century ago, the German philosopher, Friedrich Engels, stated that a change in quantity also entails a change in quality. Certainly my initial thought, when I think about the vast amount of data available now and in the future, is that we can change so much. But it is worth first going back a step or two. Data as a standalone has limited usage. It is only when such data can be analysed, and analysed in an effective manner, that it actually becomes useful. Huge volumes of data may be compelling at first glance, but without an interpretive structure they are meaningless 4.  Or, to put it another way, without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway5.

In a discussion on the future of cities, Sarah Williams, an assistant professor at MIT, highlighted that big data will not change the world unless it is collected and synthesised into tools that have a benefit. Klaus Schwab, Executive Chairman of the World Economic Forum, made the point that products are being enhanced by data, which improves asset productivity.

The essence of this new era is a distillation of data, transforming data into information, using information to gain knowledge, and ultimately using knowledge to achieve wisdom6.  It is not a giant leap to realise that having the ability to interpret data in new ways will lead to improved product development, speedier time to market, enhanced risk mitigation, superior market and client evaluation, and better innovation.

Provenance

cybersecurity
There are more devices connected to the Internet than there are people. (Image source: https://southfront.org)

The gathering and storage of data has become ever easier in our world but, according to a Veritas Global Databerg report, 85% of data held by European organisations is either redundant or has no known value, leaving only 15% considered as business critical 7.   It is important to realise that much of the generated data is in an unstructured format, therefore it is in this area that more work needs to be done. As mentioned by Ciaran Martin, the Chief Executive of the National Cyber Security Centre in the UK, there are now more devices connected to the Internet than there are people and, with the growth of our dependence on technology (and the generated data), comes an increased risk 8

Such risk includes, not least, the ability to identify from whence data originated. This is partially addressed by the Global Legal Entity Identifier (GLEIF) system9 , a non-profit entity overseen by more than 70 regulators that created a system capable of issuing unique identifiers inexpensively. The Legal Entity Identifier (LEI) is an alphanumeric code that connects to key reference information enabling clear and unique identification of legal entities participating in financial transactions. Knowing ‘who is who’ will provide incredible data benefits for trade finance institutions, particularly with regard to KYC/KYCC/AML and CDD.

In a blog from Steven Beck, Head of Trade Finance at Asian Development Bank, he states that without reliable identifiers, the huge pool of metadata that is promised by Fintech development may be impossible to navigate. As he further points out, GLEIF provides an essential piece of infrastructure for the future economy; it helps to advance Fintech to a stage where it can have meaningful benefits for society10.

The recent White Paper produced by Boston Consulting Group addressed a number of the issues that we are facing in the global trade finance ecosystem 11.  They estimate that, within trade finance, four billion pages of documents are produced annually. In their opinion, more than 90% of data field interactions could be simplified or eliminated all together, creating a process that is not only faster, but also less vulnerable to error and fraud.

Big Data in action

big data
Transforming trade (Image source: Deutsche Bank)

It is an interesting exercise to scrutinise a typical trade deal and assess where and how ‘big data’ could facilitate a transaction by utilising any or all of Artificial Intelligence (AI), Distributed Ledger Technology (DLT), Digital Cloud-based Databases, Smart Contracts, 3D Printing, Advanced Robotics, Internet of Things (IoT), and leveraging the differences between the physical and digital worlds. Potential advantages could be obtained in a number of scenarios including12 :

  • Contractual agreements between any combination of parties in a trade transaction
  • Buyer application for a trade instrument (letter of credit, guarantee etc.)Simplified preparation of documents
  • Access to pre/post-inspection information and updates
  • Tracking of goods in transit; atmospheric and environmental conditions of goods in transit
  • Re-sale of goods in transit
  • Learn at an early stage of problems encountered with goods in transit
  • Arrival of goods at destination
  • Transfer of ownership of goods
  • Automatic release of goods
  • Execution of insurance as required
  • Access to collateral status and monitoring
  • Reduction of potential fraud and corruption
  • No reliance on intermediaries
  • Automatic release of contingent liabilities
  • Automatic release of warranties, indemnities, counter-indemnities
  • Automatic release of liens, insurance or collateral
  • More efficient and timely usage of credit facilities
  • Reduced requirement for manual document checking
  • Simplified administration and cost reduction
  • Improved KYC, KYCC, CDD and AML; more transparency for regulators
  • Immediate awareness of exact date/time of departure and arrival of goods
  • Facilitate financing at lower rates than usual due to the availability of real-time information

According to the European Commission13 , such developments can produce several effects:

  • On the business side: it drastically modifies customer expectations, product enhancement, collaborative innovation and organisational forms. New technologies make assets more durable and resilient, while data and analytics change the way they are maintained.
  • On governments: as new technologies increasingly enable citizens to engage with governments, while governments gain more and more tools to increase their control over population. Governments and legislators must collaborate closely with civil society to be able to properly answer to challenges.
  • On people: one of the greatest challenges is on privacy, on the notion of ownership, consumer patterns and how we devote time to develop skills.

As mentioned in a Deutsche Bank Research report 14, modern data analysis methods will be used just as routinely as a seamlessly integrated web of all distribution channels. Flexible digitised infrastructures will in future enable banks to implement modern technologies and appropriate finance-specific Internet services efficiently and, above all, in a timely manner.

An analysis by the Financial Stability Board 15,   highlights that more efficient processing of information, for example in credit decisions, financial markets, insurance contracts and customer interactions, may contribute to a more efficient financial system. The applications of AI and machine learning by regulators and supervisors can help improve regulatory compliance and increase supervisory effectiveness.

Turning to a real-life example of the value of big data, Deutsche Bank, in conjunction with IBM and a number of other banks, is working on a digitalisation initiative now known as ‘we.trade’ (formerly Digital Trade Chain)16, .  The intent is to seamlessly connect the parties involved in a trade transaction i.e. the buyer, buyer’s bank, seller, seller’s bank and transporter. This solution will provide identification of supply chain counterparties and allow real-time tracking of goods and shipments. As mentioned by Roberto Mancone, Global Head of Disruptive Technologies and Solutions, this may, at a later stage, allow clients to rate each other, based on reliability, timely delivery and timely payment.

Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?
The Rock, T.S. Eliot, 1934

David Meynell is co-owner of www.tradefinance.training, a consultant at TradeLC Advisory, and Senior Technical Advisor to the ICC Banking Commission.
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1Edward Lorenz, 1972, "Predictability: Does the Flap of a Butterfly's Wings in Brazil set off a Tornado in Texas?”
2The Fractal Foundation, http://fractalfoundation.org/resources/what-is-chaos-theory/
3Peter Sondergaard, 17 October 2011
4Tom Boellstorff, Ethnography and Virtual Worlds, 16 September 2012
5Geoffrey Moore, author and consultant, 13 August 2012
6See: https://www.tradefinance.training/blog/articles/from-data-to-wisdom-where-next-for-trade-finance/
7See: www.isc2.org/-/media/609C97216F1B46099C3ABCDEC4C929D2.ashx
8New Statesman, Spotlight supplement, 20 October 2017
9See:https://www.gleif.org/en/about/this-is-gleif
10See: https://blogs.adb.org/blog/how-turn-blockchain-fintech-hype-reality
11Boston Consulting Group White Paper, SIBOS 2017, Digital Innovation in Trade Finance
12 See: https://www.tradefinance.training/blog/articles/digital-ramblings/
13See: https://ec.europa.eu/digital-single-market/en/fourth-industrial-revolution
14See: https://www.deutschebank.nl/nl/docs/Fintech-The_digital_revolution_in_the_financial_sector.pdf
15See: http://www.fsb.org/2017/11/artificial-intelligence-and-machine-learning-in-financial-service/
16See: www.gtreview.com/news/fintech/banks-unveil-roadmap-for-we-trade-blockchain-platform/

 

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