Blog

Big Data – benefits for Trade Finance

17/04/2018

Some of the below has been extracted from an article written by David Meynell for the Deutsche Bank flow news portal. The full article is available at:

http://www.cib.db.com/insights-and-initiatives/flow/knowledge_from_information.htm

 

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.

 

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 engine.  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?

 

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 wisdom. 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.

 

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. 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

 

Such risk includes, not least, the ability to identify from whence data originated. This is partially addressed by the Global Legal Entity Identifier (GLEIF) system, 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.

 

A recent White Paper produced by Boston Consulting Group addressed a number of the issues that we are facing in the global trade finance ecosystem.  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.

 

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 including:

 

  • 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

 

An analysis by the Financial Stability Board 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.

http://www.fsb.org/2017/11/artificial-intelligence-and-machine-learning-in-financial-service/

 

As mentioned in the above article, there is no doubt that we will also see benefits within industries closely connected with trade finance. A recent report from Trelleborg highlights that big data has the potential to transform the maritime industry.

 

As the report states: "Through application and insights, big data is creating new opportunities?to drive innovation and deliver tangible operational efficiencies across the shipping world. But information alone is not enough. It is the analysis of this data and the actionable insights it provides that will move our industry forward and determine our future."

http://www.trelleborg.com/en/media/products--and--solutions--news/trelleborg--whitepaper--provides--comprehensive--overview--of--big--data--in--the--maritime--sector

 

  

www.tradefinance.training


Back to recent articles