Disruptive Technologies – A 2021 Update by CTRM Center

RESEARCH AND REPORT

DISRUPTIVE TECHNOLOGIES

A 2021 UPDATE

Sponsored by

CONTENTS Introduction and Background |3 Survey Results |4 Disruptive Technologies in the Commodity Markets |13

Artificial Intelligence and Machine Learning | 14

Robotic Process Automation (RPA) and Automated Workflow |18

Blockchain |21

Will Blockchain Break Through? |28

Augmented and Virtual Reality |28

Disruptive Technologies and the Impact on CTRM and CM |31

About Invensoft |33 About Kyos |34 About Commodities People |35 About Commodity Technology Advisory LLC |36

INTRODUCTION AND BACKGROUND In 2021, Commodity Technology Advisory LLC (ComTech) published its first Disruptive Technologies research report (that version kindly sponsored by FIS). Technologies covered in the study scope included cloud/SaaS, Artificial Intelligence (AI), Machine Learning (ML), big data, automation and blockchain, amongst others. The findings were supported by an industry survey that led to the broad conclusions that cloud/SaaS and data management initiatives were in flight. AI, ML and automation seemed to be prepping for an explosion of use while blockchain was overhyped and lagging. Over the last couple of years, our general market observations as analysts have largely confirmed the results of the research. In early 2021, ComTech decided that the whole topic was worthy of a revisit as a result of many changes and trends in the industry and so began a new project. This report is the result of those efforts, and it was kindly sponsored by Invensoft, Kyos, and Commodities People. The entire commodities complex is undergoing significant change, driven at least in part by COVID and the resulting lockdowns. Other drivers for change like geopolitics, regulatory pressure, and increasing emphasis on cost containment and improving efficiencies in the physical side of the industry and commodity supply chains, have been sharpened by issues such as climate and sustainability. In turn, more environmental, social and governance (ESG) aware investors and consumers are also demanding and/or driving changes. Trade finance is also included in this mix of influences with the exit of many banks from the space and the increasing reliance on innovative nontraditional sources of financing. Just how were these ongoing changes, challenges and trends impacting the application of disruptive and other technologies

in the commodities industries? Digitalization has been an ongoing trend within the commodities complex for several years now and it has been accelerated by many of the business drivers noted above; and particularly so recently with the requirement for commodities companies to move to a work from home model – one that has exposed any number of process and technology weaknesses. In turn, digitalization has driven continuing investments in various technologies such as cloud, data management, workflow, automation, AI and ML. Innovations associated with digitalization, along with the other noted trends, also appear to often be catalyzed by disruptive technologies. For example, we now see AI being used to enhance commodity price forecasts, which has in turn induced several new providers leveraging AI to enter the price forecasting market. Automation facilitated by advanced technologies, particularly robotic process automation (RPA), is also being adopted by vendors and users, particularly to help guide and control processes via a distributed/home-based workforce.

Disruptive Technologies – A 2021 Update

What impacts have these trends had on technology adoption and investment? What are the use cases that motivated the investment in, and adoption

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of, these various technologies? These were the questions our survey and research asked.

SURVEY RESULTS ComTech conducted the survey component of this study between February 2021 and early June 2021 using a web-based tool. Survey responses were encouraged through email, blog and word of mouth efforts. ComTech also partnered with Commodities People to include an invitation to participate in the survey as industry players signed-up for their Commodity Trading Week event. In all, the disruptive technologies survey had 63 valid participants with just over half of those being in Europe (Figure 1). Both the North America and Asia-Pacific regions were also quite well represented. Although technology providers were the largest group of respondents (46%), end users of technology were also well represented (38%), with the remainder being consultants and systems integrators. The end users also had diverse backgrounds, with respondents representing an array of market segments including producers, consumers, banks and funds, and merchants (Figure 2). When asked about how various technologies might impact commodities and commodity trading over the next 12-24 months, it was apparent that cloud and SaaS may already be in the rear-view mirror. With these technologies having been broadly adopted and deployed across the industry, it’s perhaps not surprising that these technologies would be seen as

having the largest impacts. Data management and data mining, again somewhat mature and widely accepted technologies, follow closely behind in levels

Disruptive Technologies – A 2021 Update

of expected impact. AI and ML also ranked highly as even though they are still somewhat early in their adoption phase, several practical use cases have emerged for these technologies. By comparison, blockchain, despite much hype and investment over the last 5 plus years, remains some ways off it seems, ranking only slightly higher than opensource software and virtual/augmented reality (Figure 3). Workflow and microservices ranked somewhere in the middle; however, if you combine ‘significant’ and ‘some’ impact responses, then they also show potential in our respondent’s opinions.

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users shows little change versus the larger sample, except for Microservices, which drop further down the list.

Looking specifically at the responses of just the end

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Disruptive Technologies – A 2021 Update

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By comparison to the earlier 2018 study, it seems more respondents view all the technologies as having a more significant/deeper impact now, yet the relative ranking of those technologies remains nearly identical. AI and ML are seen as more important in this study and, as we predicted in 2017, appear to be front and center now in terms of attracting both interest versus the other newer/emerging technologies. In terms of investment plans (Figure 6), cloud and SaaS dominate with 84% of respondents saying their firms expected to invest in those technologies. AI and ML have moved up into the next place with almost 60% expecting to invest, while 32% expect to invest in blockchain. These numbers remain pretty much identical when just the end user group of respondents is analyzed. However, comparison with the 2018 results is interesting. Comparing the results from the current survey to those from 2018 indicates that investments in cloud and/or SaaS (74% in 2018 vs. 84% in 2021) and microservices (24% in 2018 vs. 41% in 2021) are expected to increase. Investment in areas like AI and ML and opensource will remain somewhat consistent while investment in blockchain (46% in 2018 vs. 32% in 2021), data management (66% vs. 56%) and VR/ AR (9% vs. 5%) might be expected to decline. Blockchain appears to be struggling even more in 2021 than it was in 2018 in the opinions of the respondents. When asked where blockchain might succeed commercially (Figure 7), there was little confidence of its commercial application in any of © Commodity Technology Advisory LLC, 2021, All Rights Reserved.

Disruptive Technologies – A 2021 Update

the tested areas except perhaps custody transfer / ownership transfer. Equally, using social media data draws little interest for most respondents (Figure 8), with the number of those who see value in mining social media for market indications having dropped from 39% in 2018 to 25% in 2021.

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Disruptive Technologies – A 2021 Update

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Referring to where disruptive technology will emerge from among the various types of technology providers (Figure 9), most expect it to emerge from the cloudbased AI/ML vendors (Azure, AWS, etc.) and technology platforms that facilitate digitalization of deal negotiation, contract management and related business processes. ERP providers are seen as the least innovative in bringing new technologies to market, trailing behind the other low-ranking segments, including global IT firms (IBM, Oracle etc.), industry consortia (Figure 9) and CTRM providers. When it comes to which types of firms are at the most risk of being disrupted by these emerging technologies, the respondents pointed to CTRM and ERP software firms as those most likely to impacted (Figure 10). Finally, as AI and ML are generating growing interest across the commodities trading space, we asked where these technologies might be applied for the most impact (Figure 11). Perhaps not surprisingly, “Data Analysis” is cited as the number one area for the use of this technology. Asset Modeling, Price Forecasting and to a lesser degree, Risk Management, are also all seen as areas for potential use. Commodities People often obtain ad hoc survey data from its conference sessions audience as well as collect data during registration for its conferences. It’s data also shows that while AI and ML seem to be seeing rapid deployment across several use cases, blockchain has not yet fully emerged commercially. A CTW tradeshow poll

showed that almost half of those responding felt AI to be a game changer and almost 1/5th was most excited by its potential. Though blockchain excites with its potential (26% in that same poll), almost half of another poll from the same conference suggest that it hasn’t yet shown its business case convincingly in commodity trading. These data points do help reinforce the trends

Disruptive Technologies – A 2021 Update

suggested by our own data. In summary, the 2021 survey results show only subtle yet arguably significant differences to the previous survey conducted in 2018, but those differences are informative. Cloud and SaaS seem to be the major focus for most firms and these technologies are clearly being broadly accepted within all sides of the industry. It could be argued that digitalization should be preceded by data management; elevating data mining/management as a significant area of

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investment, though there are hints that this focus is lessening somewhat. Viewed another way, perhaps there is an on-going shift from organizing data to attempting to extract value from it? Of course, at any point in time, each of these trends is at a different level of maturity or adoption within any individual company or technology vendor. While some innovative vendors have already fully moved to a “true cloud” platform, others for various reasons are only in the early staging of architecting their products to run

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Disruptive Technologies – A 2021 Update

effectively in a cloud environment. The same is true with respect to end users. Though each respondent may be at different points in the adoption curve for any technology, the cumulative data does provide a view of where the industry is generally with respect to the technology adoption curve for the technologies examined. As such, the data does suggest that we may be close to the peak of cloud adoption and perhaps slightly past the peak in terms of investments in data management. AI/ML and automation appear to still be prior to the peak of the technology adoption curve and can be expected to draw increasing levels of investment. These technologies are finding some use in practical business applications and new use cases are emerging. Our research indicates this is driven in large part by the need for better control of a remote workforce, and the massive growth in the volume of data generated and consumed by industry players and the need for new tools/applications to extract actionable insights from it. AI and ML empowered Robotic Process Automation (RPA) tools are also finding utility in allowing machines to manage routine work and process tasks, which in turn frees humans to focus their expertise on problematic exceptions. Though use cases in commodity trading are still somewhat limited in their scope, the early results from these efforts show enough promise and return on investment that we do expect to see increasing interest and investment in these areas. Blockchain, hyped and touted as “the next big thing” for the past 5-plus years, still seems to be some way

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off from broad practical application in the opinion of our survey respondents. Indeed, it may be further off now that it was thought to be in 2018. This is indicated not just in the lower percentage of respondents planning to invest in blockchain in our most recent survey, but also by the apparent lack of use cases to support its deployment. Based on levels of investment to date and the results achieved, it seems that blockchain will be likely be used initially to securely record certain types of transactional data via smart contracts and in managing custody transfer. We anticipate that blockchain, given its inherent latency in capturing and recording transactional data, will remain somewhat of a niche technology deployed in a small percentage of applications supporting after the fact recording of commodity trading and management activity in the near to mid-term future. Aside from its established (though perhaps improving) latency issues, an additional aspect of blockchain that will likely hinder its uptake, is the need to establish process rules, standards, and governance for its use. In order to gain broad acceptance as an enabling technology or platform, this often requires the creation of a consortia of industry participants to own and operate the initiative. Anyone familiar with the history of commodities knows very well that consortia, standards and working together do not have a particularly successful track record in this industry, particularly as the markets have increasingly become more global in their reach. As indicated in Figure 9, the survey respondents appear to echo this sentiment as they do not consider consortia to be among the leading candidates for promoting disruptive technologies.

Disruptive Technologies – A 2021 Update

Given that most blockchain initiatives to date in the commodities industries have been driven via consortia, their lack of broad success might be more a result of their inability to overcome competing agendas in terms of business processes and proposed standards, and less so any shortcoming with the technology itself. It is also interesting to examine perceptions as to where the impetus for adoption of disruptive technologies is coming from. Our respondents point squarely to those technology vendors that are focusing on cloud delivery of AI and ML tools, and to data and data management

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solution providers. The availability of these platforms that have embedded these technologies seems to be driving additional adoption as opposed to users having to invest in the basic technologies and develop their own solutions from them. Other technologies like VR remain on the edge of perception it would seem; yet our research indicates there does seem to be evidence that augmented reality is getting closer to practical usage as there are a few emerging use cases that will be covered later in this report.

Disruptive Technologies – A 2021 Update

In summary, it appears the drive to digitalize, supported by the broader trends of work-from-home, and the need for greater efficiencies and improved control are driving people’s perceptions of disruptive technologies. This in turn makes investments in cloud, automation, AI and ML, improved data analytics tools, and (based on events in 2021) security more attractive or even pressing. Further, when it comes to security considerations, perhaps blockchain will have a future role by helping to improve trust and verification, particularly in sensitive areas such as critical infrastructure. Of course, each technology has its own adoption curve and there are early adopters and laggards across the industry for each technology. However, the overall push for adoption of these emerging and advanced technologies does appear to be catalyzing the movement away from monolithic systems to ecosystems comprised of numerous specialized applications; and, from traditional on premises to SaaS or at least subscription priced. For example, SAP’s S4/Hana and Industry cloud approach is a somewhat dramatic shift for many market participants who have relied on the company’s traditionally installed ERP solution and may herald the ultimate end to any continuing resistance to cloud solutions for mid and

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large companies. Other examples of vendors that have moved from being providers of traditional monolithic applications to providers of cloud-enabled ecosystems of specialized applications (or apps) include Eka and Gen10. Even SAP has adopted the idea of an ecosystem of web-based apps and other more recent market entrants, including Previse Systems and CTRMCubed, have made this their initial go-to-market model. Still others, such as Beacon, have moved into the space with a platform model which allows users to leverage a sophisticated trading data model to build-out those capabilities specific to their unique mix of assets, processes, and markets. It should be noted that despite the growing availability and adoption of these emerging technologies, the reality is that commodity firms are often laggards overall when compared to other markets such as financial services or those that are more consumer oriented. Given the complexities of producing, managing, processing, trading, marketing and transforming commodities, it is perhaps understandable that there is still a long way to go in terms of digitalization and broad adoption of these technologies in this space; and why, for now at least, Excel remains the tool of choice for many.

Disruptive Technologies – A 2021 Update

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DISRUPTIVE TECHNOLOGIES IN THE COMMODITY MARKETS As the results of our survey indicate, there continues to be significant interest and investment in many new and emerging disruptive technologies. Though we have included Cloud and SaaS in our survey, the reality is that cloud-delivered software has now reached the point that it could be considered mainstream and well past peak adoption. Few companies operating today have not adopted and/or are using at least one or more cloud/SaaS applications - either by choice or by being essentially “forced to” to operate effectively with industry partners or service providers. Other of the examined

technologies, such as Blockchain, have been available to industry participants for several years, but their take-up as enablers of applications and processes in everyday use by most industry participants have clearly lagged the expectations that were held when they were

Disruptive Technologies – A 2021 Update

first introduced to the space. In this section, we examine the current state of the various disruptive technologies and use cases to which they are being applied. This is in no way intended to

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be an exhaustive listing of each vendor or product that might fall under each technology category but is more intended to provide a brief snapshot of the state of play for each and provide a glimpse into how they are being applied and a sense for their future potential.

Artificial Intelligence and Machine Learning An excellent definition of AI can be found at IBM’s website1 where AI is described as “enable(ing) computers and machines to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind.” Machine learning is also defined there as a branch of AI that “focuses on applications that learn from experience and improve their decision-making or predictive accuracy over time.” Deep Learning is a type of ML in which the application teaches itself to perform a task with increasing accuracy without human intervention. AI and ML use across the commodities complex seems to have expanded rapidly in the last couple of years or so. Often combined with workflow or automation, AI

and ML can form a later component of the digitalization activities taking place across the industry or, in an ad hoc mode, to help optimize specific activities, increase efficiencies and reduce costs. In some instances, it is used as a first pass attempt to automate routine tasks or in data reconciliations, leaving exceptions for human intervention. The move to this form of exception management has obvious benefits in time savings and improved process efficiencies, as well as making better use of staff’s time. Although by no means an exhaustive list, the following use cases are among the most common examples of the deployment of AI in commodities that we are currently aware of.

Short-term market forecasting In fact, demand and price forecasting is rapidly becoming an overcrowded market with suppliers of AI and ML enhanced short-term market data seemingly cropping up everywhere. These vendors, by using various sensing imagery such as arial and/or satellite 1

images, and bringing together other data including macroeconomic, econometric, production and inventories data, and even social media data, can offer AI enhanced price forecasts across several classes of commodities, ranging from agriculture to electric

https://www.ibm.com/cloud/learn/what-is-artificial-intelligence

Disruptive Technologies – A 2021 Update

power. Kyos also makes use of AI when tackling forward curve models and to develop good hourly shapes. Indeed, this is where it started using AI initially. However, these AI enhanced forecasts do rely on advanced data collection and the availability of key data will vary across the commodities complex. For example, satellite images can be useful for mapping of mines and mine inventories for major metals commodities produced in open-cast mines. A similar approach can also be used in oil and petrochemicals and agricultural production. However, for other commodities where the amounts produced and shipped are small, such tools may not offer much utility, particularly if producers wish to conceal such information by hiding stock or otherwise refusing to cooperate with data collection efforts. Nonetheless,

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even in markets or commodities with data gathering limitations, artificial intelligence can be used to more efficiently aggregate research, market sentiment, and historical data to arrive at more accurate predictions for commodity prices, estimate inventory drawdowns, forecast vessel movements/port activities and so on. An example of one company using AI tools to develop improved forecasts is Enverus, the US-based data services company. The firm is utilizing ML in their short to mid-term price forecasting for power markets and has demonstrated the value ML enabled tools by apparently producing more accurate forecasts of market prices than other sources and services during the historic disruptions in the ERCOT power markets in February of 2021.

Optimizing supply chains Efficient movement of commodities through the supply chain is crucial to profitability and is an area of application for AI that can show a quantifiable return on investment. An artificial intelligence enabled system capable of consuming and optimizing real-time logistics and pricing data can be a tremendous asset for these companies, not only in managing supply chains, but in helping make critical trading decisions. We have seen many examples of the use of AI and ML in this area including but not limited to the following functional processes: • Route optimization taking into consideration transport mode, locations, costs, time, commodity

specifics like need for refrigeration, for example, carbon footprint and so on, • Automation of nominations, balancing and scheduling using management by exception where most transactions are scheduled automatically while a smaller number of more difficult to manage transactions are identified for manual set up or checking, • Gaining insights and greater visibility into supply chains by using imagery of inventory and shipping routes/ports to predict potential issues and/or opportunities, and • Reducing the complexity around supplier

Disruptive Technologies – A 2021 Update

onboarding and collaboration using techniques like anomaly detection, cycle time prediction and nextbest action recommendations. One good example we have seen of employing such technologies in supply chains is the initiative by Polestar, Vasanda and Carbon Chain to

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combine environmental, safety and governance (ESG) auditability with supply chains optimization around ESG impacts, including the carbon footprint of the transaction. In this application, the Vasanda component utilizes technologies to examine the ESG impact of commodity production activities, for example, using a variety of different data types including imagery.

Trading The use of bots to perform automated and algo trading is now quite common particularly in real-time, intra-day power markets. However, this technology has been in use across many other commodities and markets to optimize and automate trading activities, particularly in financially traded commodities. In fact, an entire subcategory of ETRM software has emerged to help automate short-term power and gas trading, particularly in the European markets, specifically the software allows the use of AI/ML to trade automatically and often also to optimize asset dispatch. Vendors like Volue (Likron), Trayport, eZ-nergy, FIS, Brady, NavitaSoft, Igloo and others, are all marketing such solutions. These solutions have also begun to extend into scheduling and data visualization to support intraday trading activities. Other vendors like Enegen and eZ-nergy have gone further and innovated asset dispatch optimization solutions while others plan to do so. Venus Technology Ventures’ Mistro, created by former traders, is another example of an AI enabled solution in that that uses natural language processing

(NLP). The product is designed to understand commonly used trading language terms and, with its ML capabilities, learns quickly what types of deals a trader would typically perform. Admins and/or users can also add specific language used on their trade floor into its dictionary. Once configured, the internal dictionary picks up on keywords and phrases and translates them into something that can be leveraged for other processes and applications. One advantage of incorporating AI solutions within commodity trading is to help increase productivity and save time through automated deal capture. Traders often use multiple forms of communication—sometimes simultaneously—to execute deals. Whether it’s through messaging platforms, emails or phone calls, it can be difficult for a trader to remember all the details of any specific deal. AI enable NLP and ML systems can help facilitate the process of gathering information from all these sources and take appropriate actions based on this information. Techniques like NLP and ML can also be used to scan,

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listen, and watch across communications, social media, and other sources to help provide early indications of market imbalances to inform trade decisions, and once acted upon, can help ensure more accurate trade capture (many transactions are entered after the fact).

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In this latter use case, it can also be used to help fill out additional trade data based on an understanding of the trader’s typical activities, reducing time spent entering data.

Other Areas There are many areas that AI can, and has, been deployed in commodities. These include functions like predictive maintenance, asset management and optimization, inventory management, back office for reconciliations, settlements, invoice matching, and even in relatively obscure operational areas like optimizing fish feeding and improving crop management. SAP demonstrated a solution to reconcile invoices at a recent Commodity Management Forum that utilized AI, for example. Increasingly, we also see a trend to manage by exception where processes are automated, and AI identifies those where human intervention is needed. Event-driven reporting, where events drive calculations, processes, reporting aided via AI, is also quickly gaining traction. Risk Edge has been developing AI based products for some time and offers a couple of additional use cases. For one Singapore-based Agri-business that operates in over 70 countries, and supplies food and industrial raw materials to over 22,000 customers worldwide, Risk Edge delivered a web-based Planning & Analysis (FP&A) solution. Their product utilizes advanced ML algorithms to simulate its P&L and predict crop yields

based on historical data. In the metals and mining industry, Risk Edge designed and built Journal Entry anomaly detection solution using machine learning algorithms and a statistical filter. AI and automation have also been proposed and used to help users navigate through multiple systems or screens to complete working on various business processes. This is particularly useful in entities that have deployed multiple different solutions to support their operations and where managing a business process requires complex systems knowledge. As previously mentioned, it can also be used to help automate and manage by exception complex or data voluminous processes and, help to migrate to event-driven solutions whereby a specific event triggers a set of calculations (e.g., valuation based on change in price). Customer service is another where AI is proving valuable. For example, as early as August 2015, Shell launched an AI assistant for customers of its lubricants business. Shell uses its avatars, Emma and Ethan, to help customers discover products using natural language. The Shell Virtual Assistant functions through an online chat platform through

Disruptive Technologies – A 2021 Update

the company’s website. Examples of information that the system can provide include where lubricants are available for purchase, range of available pack sizes and general information regarding the technical properties of specific products. The company has also reportedly integrated a virtual assistant called Amelia into its business model to respond to inquiries more efficiently from suppliers regarding invoicing and it believes the future of AI in its industry will see a significant increase in unmanned and automated facilities. Sinopec has a long-term plan to roll out construction of 10 ‘intelligent’ plants as part of an objective to achieve a 20 percent reduction in operation costs. In April 2017, Huawei and Sinopec announced a collaborative effort to design a “smart manufacturing platform.” AI is one of eight core capabilities of the platform which will deliver a centralized method of data management and support

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integration of data across multiple applications used to manage factory operations. AI would serve to establish the rules and models that would inform how data is interpreted and offer opportunities for improvement in factory operations. Kyos also uses ML in areas like renewables and PPAs where it creates simulations for price with volumes of production using ML. It also uses ML techniques to look at historical data and project that forward, finding ML to be a robust method to handle large quantities of historical data efficiently. AI and ML, especially combined with automation, do appear to be attracting a great deal of interest and investment and we do expect to see it deployed with increasing frequency across all areas of a commodity business.

Robotic Process Automation (RPA) and Automated Workflow According to Investopedia, Robotic process automation (RPA) refers to software that can be easily programmed to do basic tasks across applications just as human workers do. The software robot can be taught a workflow with multiple steps and applications. RPA software is designed to reduce the burden of repetitive, simple tasks on employees and is seen as having benefits such as reduced costs and fewer errors. While there has been significant interest in RPA for areas like financial

settlement, scheduling, risk management and so on, ComTech hasn’t seen much evidence of its use beyond automations of various aspects of workflow via a few select RPA based tools. However, RPA and automated workflows are taking off in many industries and as an example, an Accenture study2 determined that over 43% of consumer-packaged goods (CPG) executives indicate their firms already employ automation to cut costs and promote efficiency.

https://www.accenture.com/t20170926T105943Z__w__/us-en/_acnmedia/PDF-61/Accenture-Strategy-Consumer-Goods-Workforce-POV.pdf

Disruptive Technologies – A 2021 Update

Though anyone who has ever worked in a commodity trading organization or business unit knows that there are many examples of highly repetitive and labor-intensive areas that might seem to benefit from automation and RPA, often these processes are also prone to exceptions that would require frequent human intervention. Nonetheless, it does seem that trading could be an area is ripe for automation and the widespread use of software robots. The application of RPA first requires the business process first be digitized. By looking for those highly repetitive and labor-intensive areas of the business process, opportunities for RPA can be identified and acted upon. While this may include specific trade office business processes, it can also be used to automate

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application interoperability at the desktop and other such activities. Despite the fact the market continues to digitalize and there is promise for additional adoption of automated tools, Comtech’s research did not find massive uptake of RPA in the industry. Further, it seems that some of the early vendors interested in marketing to the space have now largely backed away as projects have been sparser than anticipated. Despite that, advanced workflow solutions have found widespread adoption usually as a part of other solutions like CTRM and CM. Many CTRM and CM solutions now come complete with programmable and configurable workflow and approvals, and it has arguably become a standard feature of this class of software.

Settlement Processes Settlement is an area where RPA has been used and one case was noted in a press announcement in late 2017 by Pioneer (now Hitachi) to announce that it had joined forces with its longstanding customer Essent, in a POC to apply RPA to settlement processes in the Retail Energy Management group. “Innogy’s Essent is focusing strongly on digitization in the energy transition. For REM we accomplished that task with TRMTracker, and its automation enables us to now

apply RPA, gain experience with the concept, and prove the added value for Essent Finance,” said Pim Flink, Senior Controller at Essent. “This is pioneering work, and our results have been very promising in how it will increase our operational excellence.” This is now implemented and in production at Essent in the areas of generating a settlement report and running calculations where it saves manual work and frees up workers to work on more creative activities.

Disruptive Technologies – A 2021 Update

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Utility Uses RPA is often used in what may be termed a utility-type function – much like that presented above, where it can be used to assist a user navigate many systems when managing common business processes. Some of the most common examples include, • Web Site Scraping Energy and commodity firms have access to and require a lot of data from a variety of sources like price and weather services, SCADA and operational feeds from various assets, inventory systems and so on. Often much of this data is available on web sites but accessing that information on a regular basis can be a time-consuming process. RPA software can be used to scrape those web sites on a regular basis (such as finance-related trading sites, futures trading sites, commodity trading sites, news media sites) and extract specific information, summarize it and present it to those who need it. • Email processing Assisting with the processing of large numbers of incoming customer e-mail is an area where RPA can be used to sort out the most common queries and route them. It can also respond to the sender with an interim message of receipt. • Data Transfer Using RPA to transfer data between different solutions

is another area of use that is in fact like helping users navigate between different systems in order to do their jobs more efficiently. A similar use case is to extract data from paper forms using character recognition. Other areas that show promise for RPA and workflowtype tools are in a traditional back-office context as well as in core business processes, particularly in retail energy, such as: • Automated tariff adjustment calculation and posting • Customer onboarding – checking and validating customer data • Fast meter take over using automatic termination with other providers • Meter data and bill data processing – meter data validation • Order management • Complaint’s resolution Given the impacts of the pandemic and the resultant work from home requirements, workflow and automation has been increasingly used to provide an extra level of control over key processes. Many CTRM and CM vendors embed definable and customizable workflow/approvals within their solutions to help users model and manage business process administration within the solution. This is then used to ensure that critical activities are undertaken and completed by users through the solution.

Disruptive Technologies – A 2021 Update

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Blockchain There are new blockchain initiatives announced almost daily, yet it doesn’t appear that many commercial applications that rely wholly on blockchain are yet in widespread use in the commodities industries. Further, and particularly over the last year, there have also been a growing number of more critical commentaries noting an apparently growing belief in the industry that blockchain has been over-hyped. In all, the jury is still well and truly out as to if and when blockchain will find its potential in energy and commodities. Despite this ongoing negativity toward additional investment in Blockchain, there has been no lack of initiatives, consortia and POCs announced many of which come to nothing. There are so many blockchain initiatives targeting energy and commodities that it is impossible to cover them all and so the narrative below uses examples and is not a definitive list. There are some notable blockchain efforts in the market like Vakt and Komgo that have resulted in at least some adoption in specific parts of the industry. However, when you press Vakt about blockchain, its role in their solution is suddenly diminished and is described as a just a small aspect of the entire solution. In fact, Blockchain appears to be less than 20% of the Vakt solution. As previously noted, Blockchain requires standardization and consortia (market agreement) to work and to be attractive to new players - two things that have historically not worked well in the commodities markets: 1. There have been many standardization attempts in the industry and none have really ever produced

what was intended, but rather ended up as a compromise between a standard and extensions or customizations. While there have been numerous calls for greater standardization in the industry, and with increased frequency, the fact remains that standardization often gets in the way of differentiation and the potential for competitive advantage in the industry. As a result, it is often given lip service and does not, in the end, result in little more than some type of standard reporting. However, as the industry seeks greater efficiencies and reduced costs via digitalization and automation, standards will need to emerge even if it means that the competitive and innovative side of the business, commodity trading (often where the true complexity is) remains non-standard. 2. While there are many industry bodies and affiliations, this has also been an industry in which working as consortia has not proven to be particularly successful either. This failure to reach agreement is primarily because the establishment of a blockchain platform really requires that each participant gives up some control to a ‘central authority.’ This is why most blockchain initiatives have depended on a consortia structure in which the overall solution is owned by an entity that is subsequently co-owned by the participants. Again, whether this model can really work in an industry that has mostly been cutthroat, highly secretive and competitive remains to be seen as the results of such efforts to date have fallen well short of their founding goals.

Disruptive Technologies – A 2021 Update

For blockchain initiatives to take off commercially, they not only have to offer the promised business efficiencies and benefits, but they also require new ways of thinking and doing. It may be this that is impeding real progress as much as anything now. Another issue with blockchain is simply the hype. The simple mention of blockchain has, in the past, created sufficient market hype to inflate a public company’s stock price. Unfortunately, knowing this, some companies have very publicly announced their intentions to make significant investments in the space, only to provide little or no follow-up on the results of those efforts. This means that parsing the various initiatives and announcements needs to be done carefully with half an eye of the hype

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involved. Unfortunately, it is still somewhat true that any application that involves a hint of blockchain will likely be marketed as a ‘blockchain’ application, leading, even today, to out-sized press coverage and hype… even if the blockchain aspect of it is nothing more than window dressing. As such, in this market, it continues to be buyer-beware! All that said, Blockchain is still being proposed and pursued for many use cases in the industry. Below we mention a few of the use cases we are aware of. Trying to categorize them is often an issue because the blockchain initiatives also tend to claim they will extend into a myriad of areas that often overlap with each other.

Inventory Using blockchain to securely record ownership of commodities is certainly an area where many initiatives have already been announced. For example, the Dubai Multi Commodities Centre (DMCC) announced plans recently to create the first precious metals refinery and storage facility in the Gulf region enabled by blockchain technology. The facility will refine and store precious

metals including gold, silver, platinum, palladium and rhodium, which will be optimized on goldexchange.com, a secured trading platform. The refinery and storage facility will create an optimized record of transactions, making it possible to track all precious metals that are refined and eventually sold internationally to more than 150 countries.

Trading, Trade Back Office and supply chain support In commodities, one of the most visible initiatives is the Vakt consortium. Using blockchain technology, Vakt helps to manage physical oil transactions, eliminating reconciliation and paper-based processes. It’s a consortium of oil companies and banks (BP, Gunvor,

ABN-AMRO, Equinor, Koch, ING, Shell, Mercuria, Chevron, Total, Reliance and Societe Generale) focused on developing and deploying solutions for post-trade processing. It has been designed to help ‘eliminate reconciliation and paper-based processes,

Disruptive Technologies – A 2021 Update

enhance efficiency and create new trade finance opportunities.’ Recently, the platform went live for the physically traded BFOET crude oil business and is arguably the world’s first fully operational, enterprisegrade blockchain platform to enter the market. Vakt can also offer blockchain-based financing solutions to its users via its alliance with komgo. BHP Group has completed a first blockchain trade in iron ore with China Baoshan Iron & Steel Co Ltd, in a transaction worth around $14 million. BHP said that the trial transaction using the MineHub platform was worth about $14 million and was delivered in June. The platform processed contract terms, exchanged digital documents and provided real-time cargo visibility, it added. The Minehub platform is designed to improve efficiency in trading operations and environmental and social governance (ESG) compliance in mining and metals supply chains. Another area where blockchain is being proposed is in support of supply chain. For example, Trames, a Singapore-based supply chain orchestration platform, recently launched a software-as-a-service (SaaS) solution that it claims will help small and medium enterprises optimize supply chain operations and improve overall profitability. Running on R3’s Corda, the blockchain-based platform enables collaborative drafting and confirmation of shipping documentation and advanced analytics to help optimize decisionmaking as well as speed up shipping processes by reducing physical paperwork.

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Covantis blockchain platform. It caters for post-trade processes and has moved into full production two years after being created by a group of major agribusinesses to digitalize agricultural shipping transactions. The platform recently went live with more than 30 entities, including – Archer Daniels Midland (ADM), Bunge, Cargill, Cofco, Louis Dreyfus Company and Viterra. It will initially cover bulk shipments of commodities such as corn and soybeans from Brazil to destinations globally, and will seek to connect shippers, traders and charterers involved in these trade flows and is aimed at eliminating post-trade paper-based processes. After this initial use, Covantis intends to bring in additional post-trade processes, including trade confirmation, contract management, as well as laytime calculation. The firm also has stated their intention to explore other markets and commodities, including the remaining grains and oilseeds, beyond the existing offering of corn and soybeans. TradeTrip, is another blockchain initiative that involves digitalization of documents including Bills of Lading, Certificates of Origin, Warehouse receipts and Letters of Credit. TradeTrip markets the solution as being designed to work via API’s with a client’s existing ecosystem of commodity-focused applications to provide greater transparency, trust and fewer transactions around documentation through the supply chain – particularly those documents around custody transfer. The solution uses blockchain as well as 2D QR codes to identify scanned documents and deep learning-based text recognition to aid in transfer of document data to systems.

Disruptive Technologies – A 2021 Update

GrainChain, is marketed as a blockchain-based supply chain management firm seeking to enhance visibility for producers and consumers in the commodity supply chain in Latin America and North America. The partnership is aimed at empowering suppliers and farmers to protect their brand reputation through adherence to supply chain standards in a bid to create trust with the final consumers. The supply chain management will be provided by the Mastercard Provenance Solution, and together with GrainChain, trusted end-to-end visibility will be given to products, ranging from coffee to sorghum, from the farmers or producers to the final consumers. This visibility will afford everyone in the supply chain to track each product and authenticate its origin, thus providing room for trust in the industry. Cargill, Agrocorp, Rabobank and other logistics partners used a blockchain platform provided by Singapore-based dltledgers to settle a $12 million shipment agreement on April 1. The dltledgers blockchain solution is built on the open-source Hyperledger Fabric platform. The blockchain platform provides a repeatable framework for end-to-end digital trade executions, digitalizing the document and trade execution process. The trade took a total of just five days to settle, whereas traditional trading processes can take up to a month. The platform created a shared, unchangeable record of the transaction. According to dltledgers, cross-border commodity trading is one of the most promising sectors for blockchain, which allows for real time monitoring by multiple parties, dispenses with concerns about data

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ownership, and simplifies the exchange of documents in a digital, secure and decentralized manner. The solution is a way to continue operations within the global constraints of the pandemic. Dutch bank Rabobank, commodities trader Concord Resources, software developer Gen10, insurer AON and warehousing firm PGS formed a blockchain consortium and in November 2019 the group executed a physical sale and repurchase (repo) trade using blockchain. Repos are a type of financing, in which the lender temporarily owns the goods instead of getting a lien or charge over the assets. The original asset owner repurchases the commodity at an agreed time and slightly higher price. The consortium aims to drive efficiency, traceability and transparency in metals trading and repo financing using the blockchain platform. It tracked the metal from the point of trade to delivery and provided real-time confirmation of completion without manual intervention. The trade took less than five minutes to complete using a mobile phone. Perlin, large companies in Singapore, and the government have teamed up to develop an opensourced blockchain trade platform (ICC TradeFlow platform). DBS Bank and Trafigura, in collaboration with Infocomm Media Development Authority (IMDA), the International Chamber of Commerce (ICC), Enterprise Singapore, and Tradetech Perlin aim to connect trade partners across borders and streamline manual paper-based trade processes to improve trade flows. Built on IMDA’s TradeTrust network infrastructure and powered by Perlin’s

Disruptive Technologies – A 2021 Update

blockchain technology, the platform is designed to be interoperable with existing and future digital trade platforms. The Ricex platform is a blockchain-based rice trading exchange developed by Fujitsu. The platform is designed to specifically address the problem of managing trading across a wide variety of strains, each with differing quality, taste and fragrance, all of which determines the price of rice. The Ricex digitalizes rice trade using blockchain and provides a transparent ecosystem of importers, exporters, wholesalers, producers, regulators and other stakeholders. The platform claims to streamline the trading process by providing insurance, shipping information, inspections, and automated settlement to participants. With the blockchain platform, traceability is also enabled, allowing buyers to identify rice certified as sustainably grown. Even traditional CTRM is seen as a candidate for blockchain and EnHelix®, an oil and gas commodity trading and logistics management software marketed as having embedded artificial intelligence and blockchain capabilities, recently announced its Marketplace Blockchain software for commodity trading companies. The company claims its software is an advanced blockchain solution for trading companies which helps to standardize and automate its system of physical trades. They note they believe their solutions reduces fraud and operational risks and expedites payment and provides other benefits like automated trade execution via a distributed blockchain enabled application to reduce trade discrepancies and can

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integrate with existing ETRM systems. Another trading area that has been touted as ideal for blockchain is at the retail end of power and gas trading. Distributed power generation and small local grids which can function independently have been identified as an area for blockchain to provide peer-to-peer online platforms to trade energy. Various initiatives exist in this space including one by Transactive Grid in April launched a peer-to-peer (P2P) transaction platform that enables Brooklyn Microgrid members to buy and sell electricity produced from residential PV solar installations. Other examples include Germany’s GridX and Australia’s Decentralized Energy Exchange (deX) and numerous other examples exist and this area does seem ideal for blockchain. Finally, TradeCloud is an initiative started by several ex-commodity traders in Switzerland. Its initial focus was on a communications platform for metals commercial users and, based on the success of developing that, a similar platform for energies like coal, oil, refined products, and so on. It has also released a post-trade component that utilizes the blockchain and intends to connect to a wide range of third-party services and develop an API to connect to commercial CTRMs prior to the end of the year. In trade negotiation, the solution uses several setup configurations like a workflow application to allow appropriate communications, and a number of other setup and configuration items to define various contract terms and conditions. Users can set up sales and purchase proposals and share them as broadly or as

Disruptive Technologies – A 2021 Update

narrowly as they wish while others can explore the sort of deal, they may be interested in. Once both sides of a deal are moving forward, each step is recorded and captured whether it be a contract or deal changes via conversation or edits and it is all done in a way to highlight what has changed and what needs to get done next. Once accepted, a legally binding contract is created. The solution also covers the KYC process in a similar way such that parties can exchange documents and go through an organized process securely and have a complete audit trail at the end of that process.

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The post-trade aspect also has a bit of permissioning and set up to configure of course though nothing so very complex. It seems straightforward to achieve this. The trade is then imported, and the system shows the work that each person and organization need to do following it through to completion. Amendments can be made to the contract, parties notified of events like insurers, warehouses, logistics firms, banks, and so on and everything is auto filed as the processes are worked through. All are written to the blockchain for security, trust, and confidence. The highly complex and often manual steps are digitalized as a result.

Sourcing The Responsible Sourcing Blockchain Network (RSBN) is a network aimed at supporting responsible sourcing and production practices from mine to market. Several mining and metals producers have joined the platform to participate in a circular value chain, tracing commodity flows in near real time as well as replacing cumbersome paperwork. Built on IBM Blockchain technology and powered by the Linux Foundation’s Hyperledger Fabric, the RSBN platform aims to improve transparency in the mineral supply chain by providing a highly secure and immutable record that can be shared with specified members of the network. RSBN is designed to be adopted across industries by original equipment manufacturers (OEMs) in

automotive, electronics, aerospace and defense, as well as their supply chain partners such as mining companies and battery manufacturers. Atomyze LLC is the US branch of a global fintech platform that claims to digitalize and modernize the trading experience for products, assets and commodities by enabling investors to invest in the actual underlying commodity directly and safely. Using technology powered by blockchain, Atomyze provides a marketplace for investors to buy digitized assets of any kind, including commodities, for issuers to trade their assets on blockchain, and for the management of supply chain contracts between issuers and commercial users.

Disruptive Technologies – A 2021 Update

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Trade Finance Komgo is a blockchain trade finance platform specifically targeting commodities in which Rabobank is a member alongside other prominent Dutch banks ING and ABN Amro and several other international financial institutions. To date, the focus of the initiative has been on oil and gas. The platform is said to provide a wide range of solutions that facilitate trade finance between participants and increase the speed of transactions. According to the company, the blockchain technology allows stakeholders to control a deal in real time and offers improved transactional transparency. Currently the company offer two products: 1) a digital letter of credit (LC), which allows commodity players to submit digital trade data and documents to their banks, and 2) a know-your-customer (KYC) solution

to standardize and facilitate the KYC process enabling exchange of documents on a “need to know basis” without a central database. dltledgers has also launched a platform called SmartFin for small and medium enterprises (SMEs) to access trade financing from alternative financiers. SmartFin is a blockchain-based system that matches SMEs that are seeking finance to funders who can provide it. According to dltledgers, over 400 companies have already signed up, and can currently access financing from a handful of non-bank financiers, including TradeFlow, Drip Capital, Funding Societies, Crowd-Genie, Stenn International and Capital Match.

Document Management TradeTrip is a blockchain initiative that involves digitalization of documents. Currently those documents include Bills of Lading, Certificates of Origin, Warehouse receipts and Letters of Credit. More document types will be added. The TradeTrip solution is designed to work via API’s with a clients existing ecosystem of commodity-focused applications to provide greater transparency, trust and fewer transactions around documentation through the supply chain – particularly those documents around custody transfer. The

solution uses blockchain as well as 2D QR codes to identify scanned documents and deep learning-based text recognition to aid in transfer of document data to systems. Currently the solution is being piloted by a company in Singapore and is part of a couple of accelerators in Singapore as well. The company sees the solution growing not just in terms of documents but also in terms of tracking cargoes and via the use of smart contracts, which could facilitate event-based activities like automating a payment on receipt of cargo.

Disruptive Technologies – A 2021 Update

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Will Blockchain Break Through? There are any number of initiatives around blockchain and new ones are announced almost weekly. Though this level of activity has been going on now for 3-4 years, we still see very little blockchain being used in practical application across the broader commodity markets. And in fact, the murmurs of discontent and projects that never really took off far outnumber the applications that could be viewed as successful. A recent thirdparty review3 of 33 blockchain projects involving large companies announced over the last 4-years showed that at least a dozen of these projects, which involve major banks, exchanges and technology firms, have not gone beyond the testing phase, and those that have made it past that stage are yet to see extensive usage. In 2019, Lauren Manning, founder of GCTA, an organization found to improve the trading process for the commodities industry through the adoption and standardization of technology, said she felt blockchain was at least a decade away4 even while touting it for many processes in commodities. And, despite the

various initiatives previously noted, there are truly few commercial applications in widespread use. That said, blockchain is likely poised for further adoption, those it’s broad use may on be in certain application areas, such as an adjunct for clearing and settlement process. However, for even limited usage to occur, transaction speeds and power requirements likely must continue to improve. Blockchain will need to move beyond the hype to the point where it is a technology that has a real business case, and its use offers superior results when compared to competing and more mature technologies. Moving from hype to reality, that point when Blockchain can quantifiably demonstrate its true value as a broad solution in a complex market will take some time. In our opinion, widespread use of blockchain remains years away.

Augmented and Virtual Reality Despite the lack of interest in these technologies within our survey, continuing investment in applications and equipment across various industries, and investigative spending within some segments of commodities industries indicate they do hold some potential to have an impact in the coming years.

For example, Citi released a proof of concept5 for an augmented reality trading application for stock trading, back in early 2019. Using the Microsoft HoloLens headset, Citi worked with a virtual reality design firm and the results can be seen in a You Tube demo where a Citi trader “Jason” checks the

https://www.reuters.com/article/us-blockchain-finance-focus-idUSKCN1UB0YV

https://agfundernews.com/the-lunacy-of-blockchain-drove-commodities-veterans-to-launch-new-technology-association.html

https://qz.com/650872/citigroup-wants-to-bring-microsofts-hololens-and-augmented-reality-to-stock-trading/

Disruptive Technologies – A 2021 Update

news on the traditional 2D monitors. It features voice commands and holograms of other traders. “The trader is no longer confined to the trading desk and could project graphs and maps the size of the room in the AR space, enabling the more intuitive input and analysis of information,” according to Citi GPS in the October 2016 report6. In that report, Citi predicted that VR/AR will be used extensively across a range of applications with growth in VR/AR equipment,

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content and services going from $80bn in 2020 to $569bn in 2025. Banks maybe moving forward with the technology. Millennials are more accepting of the technology and a growing part of the workforce. However, the trading floor application may yet be some way off. However, there are several potential use cases emerging.

Virtual Desktops Traders do like a lot of screens and devices, and the ability to put that in a VR office to have more space maybe attractive. In 2017, FlexTrade demonstrated an augmented reality trading application with Microsoft HoloLens for FX. Using existing technology and application programming interfaces (APIs) within its EMS software7, its FlexAR application offers an interactive order blotter, trade ticket and charting in the virtual space. However, while initially delivered as VR it was found that this made it very difficult to work by

cutting off the outside world and so the application was moved into augmented reality where it worked much better. The trader uses hand gestures or key words to interact with virtual objects. AI can be combined with VR/AR to add in contextual information and for image recognition. Realistically, the technology is some way off, but it may find use in some of the following areas.

Data Visualization Being able to visualize ever increasing types and volumes of data is a continuing and growing issue and AR and VR may make it easier and faster to visualize and organize large amounts of data. Today, for example, Salesforce uses Oculus Rift to create an immersive 3D environment for analyzing data and Fidelity Labs, a

part of Fidelity Investments, has also taken advantage of the technology behind Oculus Rift. In commodities related industries, the oil and gas exploration space has been the earliest and longest running example of a practical use of data visualization

https://www.citi.com/commercialbank/insights/assets/docs/virtual-and-augmented-reality.pdf

https://flextrade.com/buy-side-flextrade-products/

Disruptive Technologies – A 2021 Update

using VR/AR. Dating back to the 1980’s, service companies such as Halliburton and E&P companies such as Exxon, ARCO and many other majors have employed data visualization rooms, or immersive environments, to enable better collaborative visualizations and interpretation of 3d and 4d seismic data. Though some of these environments are still in use today, advances in processing power and desktop capabilities have moved most of these data visualization techniques onto desktop machines and large display screens that utilize active 3D glasses worn by users.

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Other uses of 3D visualizations being used today include mine planning, stockyard management for bulk commodities (such as that available from Eka’s bulk terminal operations system) and modeling complex processing facilities for planning and operations. In commodities trading, simple 3D visualizations are used today for modeling volatility surfaces for analyzing price and market risks – a capability embedded in a few commercially available CTRM solutions.

Trading As mentioned, although this may be some way in the future, the ability to better organize vast numbers of screens and data, and conduct business with holographic versions of counterparties may well be one

area where this technology takes off, and most likely in the financial and equities markets. However, there is little demonstrable progress in this area in the physical commodities markets.

Training & Education This type of use is probably the most obvious as both VR and ER technologies are in use in industries such as airlines for pilot training, oil field services firms for equipment training, and various other industries where

training on large industrial equipment can be difficult, expensive or pose HSE risks. That said, there are yet to be any high value use cases for training identified in a commodity trading-type environment.

Disruptive Technologies – A 2021 Update

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DISRUPTIVE TECHNOLOGIES AND THE IMPACT ON CTRM AND CM It could be argued that the pace and level of change in commodities related industries is unprecedented and the technologies that enable is market is both driving and being driven by those changes. In the end, the industry is evolving towards a more integrated supply chain orientation with an emphasis on optimization, collaboration, efficiency and better controls, and all of this does and will continue to impact CTRM and CM software. As analysts, we have been observing the move away from large monolithic and siloed applications towards ecosystems of more agile and focused applications that use rich API’s to tie them together. Increasingly, these specialized applications are being deployed in the cloud and on cloud infrastructures that provides controllable scalability and improved performance and security. Microservices are increasingly being used within this context. Digitalization is also helping with the elimination of the more obvious manual repetitive processes that plague the industry. Increasingly workflow solutions, RPA, AI and ML are also being deployed to ensure process flow adherence, better operational controls and more streamlining by reduction/automation of common manual processes, with provisions for better identification of exceptions requiring human intervention. We also note a trend towards event-driven calculations and processes. Yet another area of CTRM/CM impact is in enhancing the user experience and provision of advanced data

visualization. While VR and augmented reality may still be a way off in terms of everyday use on the trading floor, innovating better ways to view and analyze data is increasingly becoming a key attribute of the modern CTRM and CM solution. Some vendors, such as FIS, have included 3D visualizations of risk surfaces as part of their native capabilities, more often advanced risk analysis techniques have been accomplished via data integration to solutions such as Matlab which provide more advanced and powerful data visualization tools and capabilities than one might find in most CTRM solutions currently available. Natural language processing (NLP) is being used today in some CTRM solutions, such as Molecule’s ETRM/ CTRM platform, to enable users to more quickly capture deal data. Though perhaps some way off, we may see other, potentially more efficient ways of interacting with CTRM software made available, such as use of voice commands supported by AI. AI and advanced workflow automation may also be used to better enable users to more efficiently navigate multiple screens and applications in order to complete tasks and activities.

Disruptive Technologies – A 2021 Update

AI has also demonstrated utility in document processing in the commodity trading space, though its value to date has been limited given the highly structured nature of most physical/electronic documents exchanged in these markets. Nonetheless, as more companies continue to move to a fully digital environment, we might expect to see greater use of AI-enabled document management as a native CTRM function. It is unlikely that blockchain will ever be embedded as a native capability in any CTRM/CM application, though certainly as blockchain solutions gain traction in energy and commodities, CTRM/CM will need to interface with them. The most likely points of interaction will be in blockchain managed custody transfer records, smart contracts, and aspects of settlement where confidence and trust are key. Given the increasing market interest in many of the disruptive technologies examined in our research, and

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their use cases to date, it is clear is that the future of CTRM and CM must be one of innovation and improvement from architecture to user experience. This will certainly pose a challenge for both smaller, niche vendors who lack access to funds as well as to larger vendors with legacy software and large installed bases that must be managed, guided and moved through iterations of complex software that supports years of business-critical information. Newer vendors will undoubtedly hold something of an advantage relative to being able to leverage these technologies, but they will probably lack depth of functionality, financial security and brand recognition possessed by the larger legacy CTRM/CM providers. That said, if the future really is ecosystems of solutions, perhaps there is room for all in best of breed type ecosystems constructed by the users themselves, one in which these emerging technologies can live alongside the narrowly focused but functionally deep traditional solutions and agile components?

ABOUT INVENSOFT Invensoft Technologies is an IT Company providing Commodity Management Software Solutions for business in Agricultural Commodities, Metals, Minerals and Concentrates. Since year 2000 Invensoft is supporting top global commodities companies including Fortune 500 companies in Asia, Africa and Latin America covering India, Indonesia, Singapore, Malaysia, Vietnam, Kenya, Tanzania, Uganda, Ivory Coast, USA, United Kingdom, Peru, Mexico, Honduras and Colombia. Invensoft-XBS© popularly called as XBS is a Unified Commodity Management Platform offering Commodity Management (CM), 3rd Party Commodity Warehousing & 3rd Party Logistics (CW3PL) and Commodity Trade Risk Management (CTRM) covering End-to-End needs of Commodity Business. XBS is an enterprise Web App with an integrated Mobile App called XBS Apps© available on Apple iPhone, iPad, Android Mobile phone and Tablets, offers users seamless operational, reporting experience with business controls on real time. Integrated with Digital technology and AI, our solutions transform the commodity business to the next generation digital business. Starting from commodity purchase throughout the life cycle including warehousing, processing and logistics, Digital technology and AI has been integrated to enable intelligent traceability even after multiple cycles of blending and bulking. AI based solutions are available for purchase price intelligence, quality analysis, processing yield prediction and QR code based smart warehousing of commodities.

implementation are tailored to fit every business ranging from 5 user companies to 500++ enterprises. Contact less and remote implementation enables go-live in few weeks. XBSCloud offering includes: • Invensoft-XBS© CM provides extensive features with out of the box localization for Commodity Origin Business, Procurement, Quality Management, Processing, Warehousing, Certification, End-to-End Bi-Directional Traceability, Sustainability Certification, Trading, Hedging, Risk Management, Positions, Exposures, Daily P&L and reporting. • Invensoft-XBS© CW3PL provides innovative features for commodity 3rd party warehousing, processing services and logistics business covering commodity intake, quality management, warehousing, collateral management, processing, packing, container stuffing and shipping. Innovative Customer Center module enables customers, bankers to be a part of business process. • Invensoft-XBS© CTRM provides end to end features for commodity trade risk management involving in Contract Management, Trade Management, Warehousing, Traceability, Hedging, Risk Management, Positions, Exposures, Daily P&L and reporting. • XBS APP© is an integrated Mobile App for a seamless commodity business management on iPhone and Android devices. Users can access real time information on inventory, position, intakes, shipments and approve purchases and sales contracts on the go. Website: www.invensoft.co.in

XBSCloud is an End-To-End Cloud SaaS offering by Invensoft providing Web Apps, Mobile App, including serviced and self-serviced BI with no up-front license fees, lower initial and operating costs. Subscription fees and

ABOUT KYOS ENERGY ANALYTICS KYOS offers analytical services to energy market players. Since its establishment in 2008, KYOS has developed software for power, gas and other commodity markets. To support day-to-day operations, our analytical software combines innovative mathematical solutions with a user-friendly interface. Furthermore, KYOS supports energy market players by performing advisory projects, mainly focusing on flexibility questions. Based on a solid analytical framework, KYOS offers: • Software to optimize, value and manage flexible energy portfolios • Advisory services to support decisions in energy markets • Training courses for energy professionals

KYOS offers expert in-depth knowledge on identifying, unlocking and hedging the value of flexibility of energy assets and is widely used by clients in various advisory projects. Projects include advisory work for national regulators, major electricity producers, project developers and utilities. Topics range from risk assessment of power purchase agreements for new wind generation projects, impact of transport costs on gas storage economics, to expert views during arbitration cases on the value of gas storages. KYOS’ clients can be found across Europe, most notably in the UK, Ireland, Germany, France and the Netherlands. In addition, our services are used in Japan. We also serve major players in the commodity markets with our PRM (Portfolio and Risk Management) System.

KYOS’ main software solutions are focusing on identifying and valuing the flexibility of the assets of our clients: • KyPlant: valuation and optimization of power plant assets • KyStore: valuation and optimization of gas storage assets • KySwing: valuation and optimization of swing contracts • KyPPA: valuation and risk management of renewable PPAs

ABOUT COMMODITIES PEOPLE Since 2009 we’ve worked across all facets of global trading, creating an effective global communication and information channel for everyone involved in the world’s Commodity and Energy sectors. We bring the right people together, for networking, knowledge-exchange and doing business.

Our clients value our independence, understanding of the complexities of commodity and energy trading and the way we bring the community together. Keen to learn more? Drop us a line on ben@commoditiespeople.com

Commodities touch every single person on the planet, and we communicate to everyone in the production, trading, transporting and consuming of commodities and energy – from a simple coffee bean, to rocket fuel, to alternative energy. We provide the vital physical and online forum for the participants in energy and commodity markets to exchange ideas and knowledge, find out about innovations in their market sectors, and learn from market experts.

ABOUT Commodity Technology Advisory LLC Commodity Technology Advisory is the leading analyst organization covering the ETRM and CTRM markets. We provide the invaluable insights into the issues and trends affecting the users and providers of the technologies that are crucial for success in the constantly evolving global commodities markets. Patrick Reames and Gary Vasey head our team, whose combined 60-plus years in the energy and commodities markets, provides depth of understanding of the market and its issues that is unmatched and unrivaled by any analyst group. For more information, please visit:

www.comtechadvisory.com ComTech Advisory also hosts the CTRMCenter, your online portal with news and views about commodity markets and technology as well as a comprehensive online directory of software and services providers. Please visit the CTRMCenter at:

www.ctrmcenter.com

19901 Southwest Freeway Sugar Land TX 77479 +1 281 207 5412 Prague, Czech Republic +420 775 718 112 ComTechAdvisory.com Email: info@comtechadvisory.com

Disruptive Technologies – A 2021 Update

Articles inside

About Commodity Technology Advisory LLC

About Commodities People

About Kyos

Disruptive Technologies in the Commodity Markets

Introduction and Background

About Invensoft

Blockchain

Disruptive Technologies and the Impact on CTRM and CM

Artificial Intelligence and Machine Learning

Survey Results

Robotic Process Automation (RPA) and Automated Workflow