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Machine learning will become a reality in the near future, according to ACCA global survey

Vlad Poptamas

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The findings are published in a new report from ACCA (the Association of Chartered Certified Accountants) Machine learning: more science than fiction which highlights how new tech developments have a massive potential for the accountancy profession. The report focuses on machine learning, which is the ability of computers to learn and make decisions or predictions based on analysis of large sets of data.

Narayanan Vaidyanathan, the report’s author and head of business insights at ACCA says: Machine learning is a critical area of development for accountants. Looking ahead it will be crucial to understand its value and benefits, as well as the ethical challenges it presents. In all this, the starting point has to be a legitimate business need with a clear understanding of what it can bring to the organisation.

AI and machine learning can add value to the work accountants do  from generating valuable insights for business decision-making, to fraud detection, risk assessment, understanding complexities in taxation and also with more effective non-financial reporting. So the accountancy profession needs to understand how AI and machine learning works, especially given its role in influencing the trust we have in the decisions of these systems.”

Reuter Chua, head of ACCA Singapore adds: Singapore prides itself on its tech capabilities, and is a thriving global tech hub. But when it comes to AI, accountants are trying to see through the hype to understand the realities. As with all technology, with power comes responsibility and in the case of machine learning ethical considerations are never far away. Accountants need to consider and manage potential ethical compromise from decision-making by algorithm, such as the risk of bias in the data set that feeds them and the issue of accountability for decisions made.

The results for Singapore show that 27 per cent are having initial discussions or exploring concepts of machine learning, compared to 24 per cent globally. Six per cent, one of the highest percentages compared to other markets, are at advanced testing stage, with go live in three to six months, and six percent are at full production mode dealing with live data.

The report also found that 35 per cent of those surveyed in Singapore have no plans to adopt machine learning in their organisation, while 13 per cent are undecided about it.

Locally, the main barriers to adopting machine learning are lack of skilled staff at 57 per cent, with 48 per cent citing cost as a barrier. Nearly a fifth admits they see no clear benefit from using machine learning.

The report emphasises that at a minimum all finance professionals should know how AI is evolving and be alert to how the developing capabilities could overlap with their impact on their roles. To prepare for the digital future, ACCA already examines a range of digital topics within its Masters level ACCA Qualification. It has also enhanced the digital content across many of the exams for students, while also ensuring digital is weaved into members’ continuous professional development.

Reuter Chua concludes: “Machine learning’s entrance into the accountancy mainstream is a huge opportunity here in Singapore, but also globally. This is an area where professional accountants have the chance to develop a core understanding of emerging technologies, building their digital skills alongside their communication skills so they can explain the results really well. They can then truly benefit from the ability of technologies like machine learning to support them with intelligent analysis of vast amounts of data.”

 

Source: ACCA

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Artificial Intelligence

Kountable CEO Talks with UNOPS Head of Global Innovation and Technology about Its Vital Role in Improving Supply Chain Access at BootstrapLabs AI Conference

Vlad Poptamas

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BootstrapLabs Applied Artificial Intelligence Conference featured entrepreneurs and innovators who shared the newest developments in the field of AI from research and business development to investing and business transformation.

One of several distinguished speakers was Chris Hale, CEO and Co-founder of Kountable, a managed marketplace for global trade, which focuses on collaboration in the supply chain, bringing together SMEs, multinational suppliers and end customers onto a single platform.

In a conversation with Jonas Svensson, Head of Global Innovation and Technology, Hale demonstrated the role Kountable can play in accelerating progress of the world’s biggest organizations towards equipping people for success in underserved markets.

Kountable focuses on aggregating the demand side in trade by partnering with high quality entrepreneur owners of small and medium enterprises (SMEs), bringing access to world class goods to underserved markets and accelerating progress towards the United Nations’ Sustainable Development Goals (UNSDGs).

“The Global South is home to some of the fastest growing economies on the planet, despite being challenged by a general lack of traditional infrastructure, scarcity of information, trade frictions, political and currency risks or even corruption,” said Hale.

“Nevertheless, the benefits to bringing the next billion people into the global trade economy outweigh the risks and massive investments are being made in infrastructure, healthcare, IT, and transportation by governments, and other global organizations like the UN, Red Cross, World Bank, The Gates Foundation, or Buffet Foundation.”

Kountable is making this possible by building a data acquisition, normalization, and scoring platform that measures the behaviors of the best trades and their traders in these emerging markets. With unique data describing the last mile of the supply chain and unique data on the traders in these developing markets, Kountable is building behavioral analysis for historical and live-updating trader behaviors, NLP to analyze the type of goods being requested/provided, matching algorithms to identify best-fit for traders and trade opportunities, time-series analysis on historic FX rates and fluctuation patterns, image recognition to automatically recognize and categorize key documentation, as well as SNA to assess reliability and competency of traders and buyers without traditional “scoring” mechanisms.

“We’re leveraging machine learning and artificial intelligence to help us find, resource, train, grow and promote these traders who are generally small and medium enterprises (SMEs),” said Danielle Russell, Head of Product at Kountable. “These traders are the engines of growth in these rapidly growing economies and connect the largest buyers in these economies to the top suppliers and brands in the world and are literally the point of access to global commerce for their respective countries.”

 

SOURCE Kountable

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Artificial Intelligence

BMC Named A Strong Performer in Intelligent Application and Service Monitoring by Independent Research Firm

Vlad Poptamas

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BMC, a global leader in IT solutions for the digital enterprise, today announced that Forrester Research Inc. recognized the company as a Strong Performer in The Forrester Wave™: Intelligent Application And Service Monitoring, Q2 2019. BMC received the highest score possible in the product innovation road map criterion.

According to the Forrester Wave, “BMC Software has continually advanced its product portfolio over time through organic innovation and acquisitions. Recent releases have introduced AI/ML-driven monitoring for data center and multicloud environments and rebuilt the solution from the ground up in a modern, portable, and scalable architecture leveraging containers. This allows the product to deploy into a number of environments (e.g., hybrid cloud or on-premises) to meet the needs of a large cross-section of customers.”

“We believe that the TrueSight platform’s position as a strong performer in this Forrester Wave reflects the capability of the solution to deliver robust, enterprise-class service and application-aware monitoring,” said David Cramer, President, Digital Service Operations, BMC. “In addition, earning the highest score possible in the product innovation road map criterion validates, in our opinion, our ongoing strategy to both deliver more advanced analytics and intelligent automation capabilities into the TrueSight platform, as well as continuously modernize our solutions to make them faster to deploy, easier to manage, and provide more rapid time to value for our customers.”

The BMC solution evaluated in this report, TrueSight Operations Management, offers a holistic monitoring and event management solution that ingests data, events, logs, and metrics from many sources. It applies machine learning and advanced analytics combined with application and service aware context to help IT Ops teams predictively find and fix problems faster to reduce risk, increase efficiency, and drive down costs across IT Ops processes.

“BMC Software’s TrueSight suite will assuredly benefit enterprises that are starting their journey into modernizing their applications yet also have a large number of legacy and commercial off-the-shelf (COTS) systems to support,” stated the Forrester Wave.

In this report, Forrester also recommended that customers should look for IASM solutions that offer ‘intelligent root cause analysis and remediation’. The TrueSight platform helps customers significantly reduce time to identify root cause and remediate issues faster with advanced correlation of millions of operational data points and log analytics deployed across complex infrastructure and application environments.

Digital transformation is forcing IT organizations to reconsider how to ensure infrastructure and application performance. Growth in complexity of IT environments and data volume that IT Ops teams need to manage makes maintaining the health and performance of infrastructure and applications very difficult. Intelligent monitoring tools are needed as part of a holistic IT Operations Management (ITOM) strategy to minimize costs without compromising the health and performance of increasingly complex, diverse infrastructure and applications.

“The artificial intelligence is really going to help us move from the reactive service model to proactive, and ultimately to predictive, where we’ll be able to see signs that there’s an impending failure and maybe remediate it before it happens, really saving our customer a lot of downtime. Without the TrueSight solution, we have no way of getting there,” said Chris Adams, President and Chief Executive Officer, Park Place Technologies.

Forrester Research employed a rigorous process to create the Forrester Wave. Its evaluation of this report included a review of the 13 most significant vendors in the IASM market across 29 criteria.

To read the Forrester Wave™: Intelligent Application And Service Monitoring, Q2 2019 report, visit here. The report is available to Forrester subscribers or for purchase.

 

SOURCE BMC

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Artificial Intelligence

Kavout Releases K Score for United Kingdom and Germany Stock Markets

Vlad Poptamas

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Kavout announced today the launch of K Score for the United Kingdom and Germany stock markets. Used by buyside firms, K Score is a Quantamental stock rating score of 1 to 9 that generates predictive analytics using AI (artificial intelligence) and machine learning. K Score serve as buy/sell signals, or as an effective input to investment firms’ privately developed models.

K Score are now available for publicly traded companies included on UK’s FTSE 350 and FTSE 100, and Germany’s HDAX and MCSI small-cap ETF. This is an expansion on the K Score current availability for stocks traded on the US exchanges, and A-share stocks on the China market.

“K Score has been well received by forward-looking quantitative and fundamental investors,” said Kavout’s Chief Commercial Officer, Isabell Sheang. “Our mission is to enable more investors globally to take advantage of AI solutions, and to find an edge. The decision to make K Score available for the UK and European markets aligns well with our expansion roadmap.”

K Score are ratings built by the Kavout Intelligence (KAI) engine. By taking in fundamental data, pricing signals, technical indicators, and alternative data, our machine learning models and algorithms rate and rank stocks between 1 to 9. A higher K Score assigned to a stock indicates a higher probability of outperformance over the next 1-3 months, whereas a lower K Score indicates a lower probability of outperformance.

Those interested in finding out more about K Score for markets in US, ChinaGermany and United Kingdom, please contact marketing@kavout.co.

 

SOURCE Kavout

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