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Is It You Or An ID Thief? How AI Uses Document Verification To Keep You Safe.

verification

Is It You Or An ID Thief? How AI Uses Document Verification To Keep You Safe.

It’s a moment most people have experienced.

You’re required to show your ID for something and you wait as the person studies both your face and the photo on the driver’s license, passport, or another document, making sure you’re not an impersonator trying to pull a fast one.

These days, artificial intelligence is playing a role similar to that security person, with software that allows validation of IDs remotely through digital document verification. This way you can do business through your smartphone, and someone on the other end can make sure you’re who you say you are and that a thief hasn’t stolen your identity.

And that’s especially important at a time when identity theft has been on the rise, says Stephen Hyduchak, CEO of Aver (www.goaver.com), an identity-verification service.

“Fraudsters are getting creative, but so is technology,” Hyduchak says. “It’s important to keep up because there are so many ways to create fake documents that allow someone to claim to be you and maybe even get away with it.”

Hyduchak says there are a few categories of document fraud:

Illegitimate documents. These documents are completely false. They have characteristics such as missing holograms or other current standards that are essential parts of a legitimate version of that document.

False documents. This is a document that belongs to one person, but that another person tries to use in an effort to authenticate himself.

Modified documents. This is when an original document is altered. Hyduchak says the alterations can be caught with software that detects whether fonts and text match the originals.

How do fraudsters even get the ID documents to start with? Hyduchak says it’s a matter of data security breaches – and often a combination of more than one breach. He gives this example. Just recently, the cryptocurrency exchange Binance, using a third-party Know-Your-Customer (KYC) provider, was the victim of a hack that leaked over 10,000 photographs of purported Binance KYC data. This breach affected up to 60,000 people.

“On Binance, users buy and sell cryptocurrency, something that is privacy-centric by its very nature, but still vulnerable,” Hyduchak says. “Coupling leaks like this with major data breaches like Equifax and Target, our personal information can be manipulated for the fraud with some basic photoshop work.”

A digital verification process is one way to head off any subterfuge, Hyduchak says. For example, his company has a program that works this way: The user captures a picture of their ID or passport using their smartphone. The user then takes a selfie to verify they are the same person pictured on the ID or passport. Facial recognition software compares the images through algorithms.

“As time goes on,” Hyduchak says, “I think you are going to see digital facial checks become the standard for ID verification, and that will eliminate most types of fraud.”

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Stephen Hyduchak is the CEO of Aver (www.goaver.com), an identity-verification service. Hyduchak worked in corporate finance for companies such as PRA Health Sciences before finding the entrepreneur bug. He began working on media and design for small businesses, which led him to consulting projects in the blockchain space, and eventually to founding Aver.

logistics

Global Trade’s Annual Logistics Planning Guide Reveals the Year’s Top Trends

Sometimes buying your business into the latest trends isn’t the best idea. Saddled with high costs and incompatible programs, trendy new technology can often make business processes more difficult for your business, not less. But there are some industries where the latest really can be the greatest, and one of those industries is the logistics industry.

Let’s face it: Logistics make the world go round. Whether it’s shipping perishables to community markets or lifesaving machinery to medical clinics, there’s a lot riding on the shoulders of logistics providers. That’s why it often pays to rely on cutting-edge technology. From tracking and tracing to locating items in your warehouse, new technology can often get the job done faster and more accurately. Plus, with the growing e-commerce market, logistics is more important than ever before as businesses push to get their products into customers’ hands at the speed of retailers such as Amazon.

So, what’s on the horizon for the logistics industry this coming year? Here’s what’s on our radar—and should be on yours—for the best (and one troublesome) new innovations and trends in logistics in 2020.

LOGISTICS IT

When it comes to logistics, information technology (IT) may arguably be the most important innovation of 2020. That’s because without a solid tracking system in place you’re not only causing potential backlogs for your workers, but you could be causing frustration for your clients, too. After all, if your customer can’t see where their merchandise is in the supply chain, they may bring their business to someone else who can. This is where an excellent Warehouse Management System (WMS) comes in. Using RFID and GPS, warehouse management systems can now monitor and trace every piece of inventory in your warehouse, providing real-time data to both you and your customer.

Other systems expected to be used with increased frequency in the new year include order entry systems and transportation management systems (TMS).

But logistics IT isn’t just what the customer sees, or even what your employees interact with. It goes well beyond that. Logistics IT also encompasses the back end of your IT solutions—not just the IT product itself but also the customer support that goes along with it.

We all know the logistics industry doesn’t just run from nine to five. When there’s a problem like a software bug or outage, is your IT provider available to offer technical support when you need it? Does your provider strive to make software updates that are meaningful to your business, and that integrate seamlessly into your other systems? Does your provider notify you when there are new versions of your system that could benefit your business? These are all signs of a good IT provider—a trend you definitely don’t want to miss the boat (or train, plane or truck!) on.

Logistics providers are using the latest technology, such as Collaborative Planning, Forecasting and Replenishment (CPFR) and Vendor Managed Inventory (VMI), to satisfy ever-changing customer requirements. DHL Express introduced a fresh TC55 technology that works on the Android platform and is simple to use, as well as the navigation skills in the global positioning system (GPS).

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

Artificial intelligence, or AI, is another way technology is streamlining the logistics industry. Currently, the biggest benefit of AI is arguably its ability to automate many of the processes logistics providers provide every day, including repetitive tasks that exhaust human capital and don’t challenge workers. Though many workers worry that AI will someday replace human workers, currently the technology is actually assisting them.

Another use for AI in the logistics industry relates to the driving of vehicles. As many are aware, initiatives from companies like Google have in recent years invested time and resources into developing self-driving cars, i.e. autonomous vehicles. These vehicles may be manned by a human driver, but they allow the driver to take breaks from driving while still traveling. This in turn gets deliveries to their destinations quicker, a fact that is projected to save logistics providers a lot of money. In fact, according to Mckinsey, autonomous vehicles could save logistics providers up to 45 percent, a savings providers can then pass along to their clients. These savings could then be passed to the consumer in the form of lower prices or lower shipping rates.

ENVIRONMENTALLY CONSCIOUS LOGISTICS

With many seaports developing green initiatives and land- and air-based logistics providers initiating a greater push for a reduced carbon footprint, 2020 is set to be a big year for reducing carbon emissions. Some land-based initiatives include more efficient route mapping, video conferencing and net-zero emissions.

Route mapping works by eliminating excess travel on longer routes. The idea is that a more direct route cuts fuel waste as well as carbon emissions. Video conferencing saves both money and the need for travel to meetings. As for net zero emissions, many logistics providers are investing in low or zero-emission vehicles and alternative fuels that emit less carbon into the air.

Logistics companies with warehousing services are also increasing their push toward a lower carbon footprint, using sustainable packaging and ramping up recycling efforts with the packing, shipping and packaging of products.

Maritime initiatives include the restoration and protection of wetlands as well as the planting of trees at some ports. Strategies also include the use of more efficient photosensitive lighting, such as the switch to LED lighting. Some ports have even switched over to the use of electric equipment instead of diesel fuel equipment, the establishment of fuel efficient requirements for ships which frequent the port and much more.

BLOCKCHAIN

If you’re in the logistics world, you’ve likely been hearing about blockchain for several years now. But what is it? Simply put, blockchain is a way of recording data which cannot be altered, using a technology called cryptology. Blockchain data is nearly unchangeable. The “chain” in blockchain refers to the chain of messages that originate from a single entry. To edit the chain, all members who posted to the chain must be willing to alter their own data to support the potentially edited data. This reduces the risk of that data being falsified or otherwise compromised along the way.

Blockchain data can be used to do everything from order tracking to payment issues. Blockchain also streamlines the way we communicate, reducing the need for time-consuming paperwork. Blockchain works in real-time, so shippers can trace every detail of their shipment as it progresses and make necessary adjustments to their route and load temperatures as needed. This can save time and money, preventing delays or rejected shipments.

Blockchain can also aid in financial decisions regarding fleet vehicles. Similar to a Carfax report, blockchain can show whether a pre-owned logistics vehicle has been maintained as well as the previous owner claims, and can help the potential buyer make decisions that could cost them—or save them—significantly down both the literal and figurative roads.

Indeed, blockchain has become so big that an organization has been founded to monitor the industry. The Blockchain in Transport Alliance, or BiTa, was founded to help advance the Bitchain industry, developing rules and regulations and providing education for new and veteran Bitchain users. The organization already boasts an impressive member list, including representatives of UPS and FedEx.

TECHNOMAX

In the maritime sector of the logistics industry, one revolutionary service that is “making waves” is TechnoMax, or TMX. TechnoMax works to streamline maritime operations by working with AI and the Internet of Things (IoT). The system provides risk and compliance data, app development, infrastructure development and data management. Some of TechnoMax’s capabilities include monitoring a ship’s emissions, analyzing cargo information and guiding navigation.

TRADE TARIFFS

Now for some bad news. With trade deals between the United States and China again delayed, there remains a lot of uncertainty among retailers and manufacturers. Though there is no crystal ball to predict the future or what it holds for these industries, the potential for raised prices on goods is of big concern. Price increases would inevitably be passed down to consumers, who could cut out or cut back on goods, causing sales to plummet. This could in turn negatively impact the logistics industry, as fewer products will be warehoused and transported.

For now, the industry seems to be holding its own, with some businesses preparing for the looming tariffs by shipping larger amounts now to avoid elevated costs later. Whether this bulking up will cause a dramatic drop in shipments in the first few months of 2020 remains to be seen.

LOOKING TO THE FUTURE

All things considered, 2020 seems to be gearing up to be a great year for the logistics industry, with many new technological and environmental advances on the horizon. From AI to blockchain, the industry is poised to become more efficient than ever, saving providers money which they can pass along to their clients, and in turn potentially to the consumer.

Even with the potential for steep tariffs on China (and vice versa) on the horizon, these positive advances should still make an impact on the industry in the coming year and decade.

quantam computing

GlobalData Discusses Quantam Computing and its Impact on Auto Manufacturing

As artificial intelligence continues making news headlines in a variety of industries, GlobalData experts released statements from Volkswagen’s Data Lab team lead, Dr. Marc Hilbert about the risks and opportunities presented. In his statements, Dr. Hilbert addresses specifics relating to quantam computing in the automobile manufacturing sector.

“Security is definitely necessary. I think it’s very important specifically for Volkswagen because I think if you’re not compliant, if you cannot say that our things are safe, you will lose the trust of the consumer. So compliance is something that we are working on also with machine learning, and anonymization, so hiding your personal data within the car. So there’s nobody who can say that this is you, but we still have enough information to understand.”

Quantam computing is on the radar for many industry players as a potential emerging trend. Technology innovations and game-changers alike pose unique sets of challenges and potential solutions, and of course, associated risks.

“Traffic optimization is one of the use cases we’re looking at in terms of quantum computing. Because we think that quantum computing will be one of the emerging technologies which will have a big step in terms of machine learning, in terms of data analysis, and so on. And there are companies like D wave, IBM and Google, which tried to build the computer. So this is one aspect to actually get closer to a solution,” he adds.

“The Volkswagen group is coming from a different point of view. What we try to do is find problems in the real world. What we have today with our customers is traffic jams. We tried to translate this kind of questions in a way that a quantum computer can understand it. And we try to bring those two things together to identify aspects where we can use quantum computing in the next step. So this is our task in the data lab,” Hilbert concluded.

To read the full article, please click here.

2020

Survey: Business Leaders Start 2020 with Lingering Concerns About Talent Shortages & Recession Risk

A new survey reveals that the world’s chief executives view the risk of a recession as their biggest external concern in 2020. Attracting and retaining talent ranks as their top internal concern. They also feel unsettled by trade uncertainty, political instability, and more intense competition from disruptive technologies. However,
they plan to counter such forces by developing more innovative cultures and new business models.

Conducted annually since 1999 by The Conference Board, this year’s survey gauged nearly 750 CEOs and nearly 800 other C-Suite executives from mainly four regions: Europe, Latin America, Asia, and the United States. As part of the survey, participants weighed in on which external and internal issues warrant the most immediate attention in 2020.

External Concerns in 2020

Recession fears top the list

Global: For the 2nd year in a row, CEOs and other C-Suite executives globally rank a recession as their top external worry
in the year ahead.

US: For US CEOs, a recession rose from being their 3rd biggest concern in 2019 to their top one in 2020. The issue surpassed cybersecurity, their top concern in 2019.

Elsewhere: A recession also tops the list of concerns of Chinese and European CEOs, and is the runner-up for Latin American and Japanese CEOs.

Widespread concern over trade uncertainty

Global: CEOs globally rank uncertainty about global trade as their 2nd biggest external worry in 2020.

US: It ranks as the 4th biggest worry of US CEOs, tied with its affiliate issue: global political instability.

China: Chinese CEOs rank trade uncertainty as their top worry, tied with their fear of a recession.

Latin America and Europe: CEOs there rank it 1st and 3rd, respectively.

Chinese CEOs feeling the effects of economic sanctions

China: Chinese CEOs rank the effects of economic sanctions as their 5th biggest external worry, tied with the issue of more demanding customers. Their concern about sanctions is the highest-ranking by any country by a big margin.

What it reveals about US-China trade tensions: The role technology plays in this conflict is deep and enduring. Tariffs are likely to be temporary and easily subject to negotiation, but technology blockades, via economic sanctions, are not.

Competition intensifies

Global: For CEOs globally, fiercer competition rose from being their 4th top external worry in 2019 to their 3rd in 2020.

US: For two years in a row, US CEOs cite the issue as their 2nd top external worry.

China: For Chinese CEOs, concerns about fiercer competition rose from being their 7th in 2019 to their 3rd in 2020.

Cybersecurity budgets increase, but strategy remains elusive

Bigger budgets: More than 70% of responding CEOs globally plan to increase their cybersecurity budgets in 2020.

But unclear strategy: Almost 40% of responding CEOs globally say their organizations lack a clear strategy to deal with the financial and reputational impact of a cyber-attack or data breach.

Climate change heats up

Global: For 2020, CEOs globally ranked the impact of climate change on their business as 9th, up from 11th in 2019.

Driving the momentum: CEOs in Latin America (4th, up from 10th in 2019) and Europe (8th, up from 13th in 2019).

“The ongoing concerns about recession risk among business leaders reflect the slowing economy of the past year and the uncertainties about the outcome of the trade disputes and other policy concerns,” said Bart van Ark, Chief Economist at The Conference Board. “However, given a slightly better outlook for the global economy and an easing of trade tensions, we anticipate that a drumbeat of negative sentiment – which can become a self-fulling prophecy – can be avoided, and that we  will see more confidence about business prospects in 2020.”

Internal Concerns in 2020

The number-one priority: attracting and retaining top talent

-Widespread agreement: Regardless of a company’s location or size, attracting and retaining top talent ranks as the number-one internal stressor for CEOs and other C-Suite executives globally in 2020.

-What’s intensifying the talent battle? A tight labor market, among other issues. CEOs globally, for example, cite the tight labor market as their 5th biggest external worry in the year ahead.

Developing innovative products and cultures are a key focus

Create new business models because of disruptive technologies: CEOs and other C-suite executives globally rank it their 2nd top internal priority.

Create a more innovative culture: CEOs and other C-Suite executives globally rank it their 3rd top internal priority.

Widespread commitment to cultivating leaders for the future

Global: CEOs and other C-Suite executives globally rank developing “next-gen” leaders as their 4th top internal priority.

Japan: Japanese CEOs rank this issue as their number-one internal priority, ahead of all other internal issues.

Women C-Suite executives more concerned about equal pay for equal work

Women: Globally, implementing equal pay for equal work ranked as their 6th top internal priority.

Men: Globally, the issue ranked as their 15th top internal priority.

“The global challenge in acquiring and retaining talent requires companies to be more strategic – knowing not only what qualities and skills to recruit for, but also how to recruit more efficiently and effectively,” said Rebecca Lea Ray, Ph.D., Executive Vice President of Human Capital at The Conference Board. “To support such efforts, they can consider leveraging artificial intelligence, a valuable tool when used with the proper understanding and safeguards.”

Mature-Market CEOs vs Emerging-Market CEOs

The survey results reveal much agreement between CEOs in mature economies (436 respondents) and emerging markets (304 respondents). But, some stark differences exist when it comes to which issues they plan to prioritize in 2020.

3 External Differences

Tight labor market
-Mature-market CEOs rank the issue as their 3rd biggest external concern. Emerging-market CEOs rank it 10th.

Uncertainty about global trade
-Emerging-market CEOs rank the issue as their number-one external concern. Mature-market CEOs rank it 4th.

Declining trust in political and policy institutions
-Emerging-market CEOs rank the issue as their 5th top external concern. Mature-market CEOs rank it 8th.

3 Internal Differences

Create new business models because of disruptive technologies
-Emerging-market CEOs rank the issue as their 2nd top internal priority. Mature-market CEOs rank it 4th.

Manage mergers and acquisitions
-Mature-market CEOs rank the issue as their 7th top internal priority. Emerging-market CEOs rank it 12th.

Build a more inclusive culture
-Mature-market CEOs rank the issue as their 8th top internal priority. Emerging-market CEOs rank it 16th.

“When it comes to creating new business models because of disruptive technologies, there is more urgency among  emerging-market CEOs than those in more mature economies,” said Chuck Mitchell, Executive Director of Knowledge,  Content, and Quality at The Conference Board. “This should raise a warning flag about possible complacency considering the current speed of disruption. The truth is that, today, companies no longer enjoy the luxury of a decades-long lead time to adapt to the digital revolution.”

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Media can contact The Conference Board for a copy of the full survey results.

The Conference Board is the member-driven think tank that delivers trusted insights for what’s ahead. Founded in 1916, they
are a non-partisan, not-for-profit entity holding 501 (c) (3) tax-exempt status in the United States. www.conferenceboard.org

Republished with permission

production

The Countries Leading the Way in the Future of Production

The First Industrial Revolution dates back to the 18th century, with the manufacturing and production process evolving significantly to improve efficiency. Since then, the world has gone through a series of changes with the present-day seeing us in full swing of the world’s Fourth Industrial Revolution. 

Using data from the World Economic Forum’s ‘Readiness for the Future of Production’ report, RS Components have taken a look at the countries that are leading the way when it comes to driving production forward. The six main drivers are ‘Technology & Innovation’, ‘Human Capital’, ‘Global Trade & Investment’, ‘Institutional Framework’, ‘Sustainable Resources’, and ‘Demand Environment’. See how each country compares when it comes to being ready to produce more products, technologies, and goods here.

The 21st century is a truly digital age, with technology now intertwined and cemented into both our personal and professional lives. Over the last two decades, in particular, technology has become increasingly advanced and has seen the emergence of the Fourth Industrial Revolution. Complicated and impressive technologies such as artificial intelligence (AI), robotics, the Internet of Things (IoT), 3D printing, genetic engineering, and quantum computing have all emerged and are being used across the globe in a variety of industries, businesses and processes.

As a result of the new technological age, the speed, efficiency, and accuracy of production levels have improved astronomically, with less room for human error as machinery takes over, making production levels much faster and hassle-free.  

With the rise of these advancements, it is important for countries and businesses across all industries to be tapping into these changes to keep up with the future of production. But which countries are leading the way?

RS Components have produced a graphic analyzing data from the World Economic Forum’s Readiness for the Future of Production report, to reveal the countries leading the way when it comes to driving production forward. With each country analyzed by a series of metrics including global trade and investment, institutional framework, sustainable resources, demand environment, and emerging technologies, the top 10 countries leading production levels forward have been scored out of 10.

The top 10 countries driving the future of production include:

The US takes the crown as the leading country in the world driving the future of production forward. Scoring at the top of the leaderboard across all metrics excluding Sustainable Resources and Institutional Framework, the US holds an overall score of 8.16 out of 10. The US is renowned for its innovation and holds an advanced, connected and secure technological platform that allows production to drive forward in the most efficient way possible.

Singapore ranks as the second country driving the future of production and the UK sits at fourth place with a score of 7.84. Singapore sits as one of the world’s leading chemical manufacturing sites, with over 100 global petroleum, petrochemical and specialty chemical companies situated on 12 square miles of land. Singapore today sits as the world’s fifth-largest refinery export hub and amongst the top 10 global chemical hubs by export volume. Involved in these systems includes advancements in manufacturing from robots, to predictive analytics and artificial intelligence. Singapore, like the US, is a key driver in testing, experimenting and trialing the latest technologies. In addition, manufacturing continues to contribute around 20% to Singapore’s GDP.

The importance of having the right technological foundations 

In order for production levels to thrive, it is crucial that technological foundations are cemented in supply chains across the globe. For example, in a warehouse, the speed and availability of the internet is crucial when the Internet of Things is being adopted on the factory floor. In addition, it is also greatly important for businesses and industries to have strong, connected cybersecurity systems to ensure digital security is maintained to a high standard. Having the technological foundations of this, like the US, allows the nation to drive forward technologies to increase production levels.

In addition, in order to ensure these new innovations are implemented effectively, it is crucial that employees have a good understanding of the technology they are interacting with on a daily basis, as the skills required of workers will evolve with the new advancements.

Combined, industries and countries will be able to adapt rapidly emerging technologies into their production lives, which will have a global impact on both businesses and consumers across the world.

AI

Ethics And AI: Are We Ready For The Rise Of Artificial Intelligence?

No job in the United States has seen more hiring growth in the last five years than artificial-intelligence specialist, a position dedicated to building AI systems and figuring out where to implement them.

But is that career growth happening at a faster rate than our ability to address the ethical issues involved when machines make decisions that impact our lives and possibly invade our privacy?

Maybe so, says Dr. Steven Mintz (www.stevenmintzethics.com), author of Beyond Happiness and Meaning: Transforming Your Life Through Ethical Behavior.

“Rules of the road are needed to ensure that artificial intelligence systems are designed in an ethical way and operate based on ethical principles,” he says. “There are plenty of questions that need to be addressed. What are the right ways to use AI? How can AI be used to foster fairness, justice and transparency? What are the implications of using AI for productivity and performance evaluation?”

Those who take jobs in this growing field will need to play a pivotal role in helping to work out those ethical issues, he says, and already there is somewhat of a global consensus about what should be the ethical principles in AI.

Those principles include:

Transparency. People affected by the decisions a machine makes should be allowed to know what goes into that decision-making process.

Non-maleficence. Never cause foreseeable or unintentional harm using AI, including discrimination, violation of privacy, or bodily harm.

Justice. Monitor AI to prevent or reduce bias. How could a machine be biased? A recent National Law Review article gave this hypothetical example: A financially focused AI might decide that people whose names end in vowels are a high credit risk. That could negatively affect people of certain ethnicities, such as people of Italian or Japanese descent.

Responsibility. Those involved in developing AI systems should be held accountable for their work.

Privacy. An ethical AI system promotes privacy both as a value to uphold and a right to be protected.

Mintz points to one recent workplace survey that examined the views of employers and employees in a number of countries with respect to AI ethics policies, potential misuse, liability, and regulation.

“More than half of the employers questioned said their companies do not currently have a written policy on the ethical use of AI or bots,” Mintz says. “Another 21 percent expressed a concern that companies could use AI in an unethical manner.”

Progress is being made on some fronts, though.

In Australia, five major companies are involved in a trial run of eight principles developed as part of the government AI Ethics Framework. The idea behind the principles is to ensure that AI systems benefit individuals, society and the environment; respect human rights; don’t discriminate; and uphold privacy rights and data protection.

Mintz says the next step in the U.S. should be for the business community likewise to work with government agencies to identify ethical AI principles.

“Unfortunately,” he says, “it seems the process is moving slowly and needs a nudge by technology companies, most of whom are directly affected by the ethical use of AI.”

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Dr. Steven Mintz (www.stevenmintzethics.com), author of Beyond Happiness and Meaning: Transforming Your Life Through Ethical Behavior, has frequently commented on ethical issues in society and business ethics. His Workplace Ethics Advice blog has been recognized as one of the top 30 in corporate social responsibility. He also has served as an expert witness on ethics matters. Dr. Mintz spent almost 40 years of his life in academia. He has held positions as a chair in Accounting at San Francisco State University and Texas State University. He was the Dean of the College of Business and Public Administration at Cal State University, San Bernardino. He recently retired as a Professor Emeritus from Cal Poly State University in San Luis Obispo.

forex

How to Analyze Data for More Profitable Forex Trading

Successful forex trading is the art of being able to predict when currencies are going to shift in value in relation to each other, and what direction that shift is going to be in. The good news is that those fundamentals are relatively simple; is the dollar going to weaken against the yen? Will the pound pick up against the euro? Another piece of good news is that there are huge swathes of data available to the average retail trader to enable them to make these decisions. Of course, you may opt to rely on your instincts and make decisions as the situation in the various currency exchanges unfolds before you.

While there is a place for this kind of fast thinking and quick decision making in forex trading, it will only ever form the basis of a stable and successful long term strategy – one which delivers consistent levels of profit – if the quick decisions are built upon the foundations of a clear and thought through long term plan. And this kind of planning is only possible if you know exactly what kind of data to be on the lookout for, and about the tools which are available aid in your analysis. 

The complexities of big data in the age of seamless digital communication are such that it would be impossible to summarise every possible metric or analytical approach accessible to the retail trader in the space available. What is possible, however, is an overview of the main planks of data analysis a trader needs to bear in mind, and a look at a few of the types of tool which can make that analysis easier and more accurate.             

Forex Fundamentals 

When a trader buys and sells shares the analysis required is focused, in the main, on the good health of otherwise of the company in question, and whether the various indicators predict that the shares are likely to rise or fall in value. Wider market conditions have an impact as well, of course, but these conditions would be the same for any stock being traded, which places the emphasis firmly on the choice of stock.

Where forex trading is concerned, however, the fundamental issue is always going to be the relative strength and weakness of a pair of currencies. Looking ahead in an effort to take advantage of shifts in value means analysing macro-economic figures such as interest rates, unemployment rates and GDP (gross domestic product). Many of these figures are firmly fixed in the economic news cycle, meaning it’s simple for a trader to see in advance when a country or bloc such as the EU is likely to announce figures which might impact on currency fluctuations (predicting what this impact will be is a more complex matter altogether, of course).

Requiring more vigilance to spot, on the other hand, are the sudden shifts which might be triggered by an event such as a comment in a ministerial press conference which is assumed to increase the chances of a no-deal Brexit and so sends the value of the pound dropping. Fundamental analysis based on one-off events of this kind requires a close attention to detail, up to the minute (or even second) access to newsfeeds and the willingness to take up positions instantly.        

Technical

Technical analysis is based not on real world events beyond the confines of the currency exchanges, but on in-depth analysis of the way in which the price of currencies has moved in the past. By focusing on charts of price movements and analysing them with a variety of tools – both manual and automatic – a trader can identify patterns which have repeated in the past and can be expected to repeat again in the future. Past performance is no guarantee of future success, of course (some clichés become clichés because they happen to be true), but the relative stability of the major currencies, over the long term, means that patterns of movement can become relatively predictable. 

Market Movements

A further method of analyzing the forex markets is by watching out for larger than usual shifts in the number of traders investing in a particular currency. As soon as a large number of traders invest in a particular currency, the future pool of people who might opt to sell that currency expands, with the result that the potential value of that currency is impacted upon. Analyzing market movements could be referred to as depending upon the wisdom of crowds. As has been shown in the past, that wisdom can often be mistaken. A stampede to buy or sell a specific currency could be triggered by knowledge of where the value of that currency is heading, but it could also be caused by a simple self-fulfilling prophecy – sometimes, if enough traders take a position, enough other traders assume there must be a good reason for doing so and follow suit, creating a pattern which feeds off itself with little or no external justification.     

It’s not a question of which of these three modes of analysis is the most effective, since the best results will always be gained by combining elements of all three. The deluge of data which is available, however, particularly where technical analysis is concerned, means that the wiser trader will make use of some of the tools which are available:

Session highlighter

One of the key attractions of forex trading is the fact that the currency markets are open somewhere in the world 24 hours a day throughout the week. The fact that different markets are open at different times of the day means that the sessions within those markets are likely to have different impacts on the pairs of currencies which a trader is working with. A session highlighter tool can be used to divide a traders charts into these various sessions, and then to highlight any movement that occurs over set periods, such as a minute, a specific number of minutes or an hour.     

Volatility Tool for Forex 

A volatility tool will show a trader how much, and in what way, a pair of currencies has moved on an hourly basis during a period such as the last thirty days. This enables the trader to build up a fuller picture of the way the currency pair behaves, and note any patterns such as recurring movements on specific days or at a specific time of the day. The more advanced versions of the tool will calculate the typical movement range and, given a time period by the trader, will display a percentage probability that the pair will stay within the set range.   

Signal service

Signal service providers offer instant information in the form of tips, delivered either by experts or AI systems, which recommend trades are made at a certain time and price on the basis of analysis. There are different types of signal services available, some based on fundamental analysis (i.e. news which might impact on the markets) and some on technical analysis. Signals shouldn’t be confused with the kind of AI that trades automatically on your behalf – they are merely providing information in a timely manner which it is up to you, as a trader, to interpret.  

Undertaking and applying analysis is a key practice of any successful trader. The degree of analysis a trader carries out will depend upon their inclination and appetite for hard number crunching, but the rule to remember is that while there really isn’t such a thing as too much analysis (as long as it’s used to eventually take a position), the concept of too little analysis is all too real.   

machine learning

How Machine Learning Is Transforming Supply Chain Management

Supply chain management is a complicated business. A lack of synchronization or one missing entity can interrupt the entire chain and result in millions in losses.

In a market environment where businesses are continually striving to cut costs, increase profits, and enhance customer experience, disruptive technologies like machine learning offer a window of opportunity. By exploiting the enormous amount of real-time data and leveraging the cloud power, it improves decision making, process automation, and optimization. It can create an entire machine intelligence-powered supply chain model. It also helps companies improve insights, mitigate risks, and enhance performance, all of which are crucial as the global supply chain war wages on.

Gartner recently announced that innovative technologies like blockchain and Artificial Intelligence (AI)/machine learning would significantly disrupt existing supply chain operating models. In addition to advanced analytics and Internet of Things (IoT), machine learning is considered one of the high-benefit technologies. This is because it allows dynamic shifts across industries and enables efficient processes that result in significant revenue gains or cost savings. 

So, it is no surprise then that, in another industry update, Gartner predicted that at least 50% of global companies would be using AI-related transformational technologies in supply chain operations by 2023.

There are three key ways in which these transformational technologies empower businesses:

Monitoring: By connecting equipment, products, and vehicles with IoT sensors, companies can monitor goods and operations in real time.

Analyzing: Advanced analytics convert data into actionable insights and help businesses understand the reason behind specific incidents and how they impact the business.

Acting: Valuable insights as a result of data crunching help businesses address planning challenges and automate processes to improve efficiency.

So, adopting machine learning in supply chains is critical for companies to stay competitive in the long run. However, what aspects of the supply chain will be impacted by machine learning? Let us find out.

A Myriad of Benefits to Supply Chains

If you get the algorithms right, the benefits of using machine learning are innumerable. The algorithms can predict supply trends based on human behavior, resulting in personalized customer service with lower inventories and better utilization of resources. We take a look at several such benefits of machine learning below.

Brings Real-Time Visibility Which Improves Customer Experience

According to a Statista survey, visibility is a significant organizational challenge for 21% of supply chain professionals. Visibility has been a buzzword in supply chain circles for more than a decade now and every technology so far has promised to improve visibility in some way. But, is machine learning contributing anything here? 

The combination of IoT, deep analytics, and real-time monitoring is improving supply chain visibility, helping businesses achieve delivery commitments and transforming the customer experience. By examining historical data from various sources, machine learning workflows discover complex interconnections between various processes along the value chain.

Amazon is a prime example as it is using machine learning to enhance its customer experience by gaining an understanding of how product recommendations influence customers’ store visits.

Cuts Costs and Reduces Response Times

As per Amazon’s regulatory filing in 2017, their shipping costs increased from $11.5 billion in 2015 to $21.7 billion in 2017. And, it’s not just Amazon. Many other players are struggling because of rising shipping costs. In fact, in one survey, more than 24% of supply chain professionals expressed that delivery costs are the biggest challenge for B2C companies.

By applying machine learning to handle demand-to-supply imbalances and trigger automated responses, businesses can improve the customer experience, while minimizing costs. Operational and administrative costs can also be reduced by integrating freight and warehousing processes and improving connectivity with logistics service providers.

Machine learning algorithms’ ability to analyze and self-learn from historic delivery records and real-time data helps managers and dispatchers optimize the route for each vehicle. This allows them to save costs, reduce driving time, and increase productivity. 

Machine learning can also be used to detect issues in the supply chain before they disrupt the business. Having an effective supply chain forecasting system means a business has the intelligence to respond to emerging threats. And, the faster a business can respond to problems, the more effective the response will be.

Streamlines Production Planning and Identifies Demand Patterns

When it comes to machine learning’s role in optimizing complex supply chains, production planning is just the tip of the iceberg.

Sophisticated algorithms are trained on existing production data in such a way that they start identifying future buying, customers’ ordering behavior, and possible areas of waste. This helps businesses tailor production and transport processes to actual demand as well as improve their relationships with specific customers.

For example, by anticipating and acting on the specific needs of your customers before they even arise, businesses can establish themselves as reputed brands capable of recognizing customer needs. 

There is so much volatility in global supply chains that it will be challenging to forecast demand accurately, without technologies like machine learning. However, reaping the full benefits of machine learning might take years. So, businesses should plan for the future and start taking advantage of the machine learning solutions available today.

Investing in machine learning and the related technologies today means increased profitability and more resources for your business tomorrow. Businesses that can use machine learning in their supply chains will have better plans, resulting in less “firefighting” and fewer inefficiencies.

 

FinTech

FinTech: 5 Automation Trends That Are Impacting the Industry Right Now

The FinTech industry is rapidly moving toward automation as a source of efficiency. The move to specific tools and software programs increases speed and accuracy of processes. It also keeps employers on their toes as they need to quickly evolve and learn. Many of these programs previously required specialized training and adaptability.
Automation helps with repetitive procedures and simplifies complicated tasks. It increases accuracy and safety measures, while minimizing human error. Expectations indicate that the FinTech industry will extend its tech integration significantly over the next four years.


Here are 5 automation trends that are impacting the Fintech industry right now:

1. Human Resources Management: This used to be one of the least automated components, but now software like Workday and 15Five are building platforms to assist workflow with related systems that support employee management. Finance companies increasingly recognize that their people are the most valuable resource and need to be managed more thoughtfully as well as efficiently.

2. Mobile: Finance companies now consider mobile oriented tech as part of the core work-flow. The industry relies heavily on its ability to get work done efficiently. FinTech continues to utilize software which speeds up communication and productivity. Mobile used to be considered a security risk by the financial industry. Now it is considered a way to enhance productivity as well as provide more flexible workflow for employees.

3. Customer Support: More automation is taking over customer service. This support has advanced tremendously with certain software programs that include internal systems to support customers. Software systems such as Fresh Desk and Zen Desk are cutting down on the head count needed for customer service departments in some companies. But more importantly these new systems are improving the customer experience and the lives of the people working in those departments.

4. Billing/Invoicing: Payments systems like Stripe, invoicing and billing systems like Freshbooks, and more advanced ERP systems Netsuite are examples of programs that continue to reinvent the way FinTech is automating business functions. Although many companies are still at least partially stuck in the past of creating manual invoices and payments, these automated systems are increasingly taking over. Both the customer and the vendor win with greater automation in this area. Vendors cut costs and get paid faster. Customers benefit from this greater efficiency of vendors with lower prices or higher value delivered for their purchases.

5. Accounting: Xendoo, Zoho, Quicken online and other systems automate are automating the accounting, bookkeeping, and tax filing functions of businesses. Traditional accounting software, and human bookkeepers and accountants, still have an important role to play in this area, but the accounting business is rapidly changing as well due to technology. The number of people involved with these activities is likely to shrink dramatically as automation takes over more of these functions. Ultimately businesses and their customers will benefit from this via lower operating costs that allow for better value to be delivered rather than spent on administrative functions like accounting.

It is crucial for companies of all sizes to be knowledgeable about this trend and keep their business updated as automation continues to reinvent Fintech industry jobs. You have to be able to adapt quickly to these changes. Our previous ideas and habits of doing business are changing, and we have to keep up with those changes or be left behind by competitors who will adapt more quickly

Automation is impacting Fintech employees in a variety of complex ways so it’s critical for employees to have a greater understanding of and training on different software systems to ensure they keep up with the automation and benefit from it rather than viewing it as a potential threat to their jobs. There is no way to stop technology. All of us need to work hard to stay on the right side of its inevitable progress.

AI

How AI can Amp Up Thematic Investment Strategies

One of the persistent criticisms facing equity investors is their short-term view. They are characterized by adding or dropping stocks as the quarterly earnings roll in. Thematic investment, on the other hand, provides one counterpoint to earnings-focused stock picking.

Thematic investing  – a strategy designed to capitalize on broad economic or social changes – has seen increasing use in recent years. In 2016, thematic funds accounted for 30% of new ETFs introduced, on topics ranging from obesity, millennial consumption habits, and health and fitness.

Yet, asking questions about anything long term can be complex and often obscure. The trends and themes themselves that will reshape economies may be easy to identify, but translating them into quality investment vehicles is another matter. Using themes like clean energy, disruptive technologies, aging populations, or emerging markets to structure portfolios comes with its own unique challenges: successfully sifting genuine long-term trends from flash-in-the-pan fads – and critically, doing so early – is no easy task. Good analysis requires a massive amount of diverse data that, once structured in a way, it would facilitate thematic analysis.

A Knowledge Graph-based framework is uniquely positioned to provide both the data and analytic framework, with the inference capabilities necessary to provide actionable insights into large data sets.

A properly built Knowledge Graph describes the interrelations between real-world entities through a multidisciplinary, multidimensional correlated structure, comparing common themes and concepts across hundreds of millions of data assets over several years of correlated data embedded into the Knowledge Graph.
Such a framework can automatically calculate thousands of strategies for any investable concept an investor can think of – ranging from sustainability themes like clean energy to disruptive technologies like 5G or cloud computing.

A functional Knowledge Graph can rapidly build new, flexible strategies for thousands of concepts, deriving insights from millions of combined sources, and in ways that a typical analyst approach cannot match. Data sets can have global coverage – with strategies tailored to and applicable to multiple regions and countries – while also being highly specialized. They’re equally capable of taking in structured and unstructured data sets; everything from news reports, SEC filings, and financial or macroeconomic reports to court opinions and clinical trial data or patents. This multidimensional approach powers a dynamic point-in-time Knowledge Graph framework to produce exposure indices with precision.

Knowledge Graphs can further offer special insights in building a thematic investing portfolio through the way they look at concepts, both – quantitative (AAPL stock prices or its fundamental indicators for example) and qualitative. This offers not only the numbers behind what makes a wise investment, but also the context behind those numbers, which is especially critical when tracking themes.

Taking that capability a step further, it can also weigh data points based on the strength of their correlation to a given data set, or screen against undesirable exposure that might at first glance appear to be on theme. This scoring can be done at the entity level, offering sourced data on every point used in the process. When the process is complete, the final index that is produced has been weighed on multiple levels, accounting for variables such as market caps and liquidity for each company, and the aggregated exposures.

This type of analysis illustrates one of the key strengths of thematic investing: its concentration. Thematic investments are typically concentrated on a smaller selection of stocks but a Knowledge Graph framework offers the opportunity to build thematic strategies based on a larger constituents basket. This pushes market analysis away from being a purely reactive prospect; through identifying anticipated changes in the world, investors can take a forward-looking approach to capitalize on opportunities as they are forming, leading to potentially greater long-term growth opportunities.

Contrast that approach with mutual funds, which are typically concentrated on 40-80 stocks in a portfolio. The emphasis is generally on diversification, which manages risk, but is not necessarily the optimal way to achieve growth.

Some funds have already begun to turn to technology to do some of this critical analysis work. The AI-powered International Equity ATF (NYSEArca: AIIQ) has been doing just this since 2018. The fund runs on the Equbot Model, a proprietary algorithm that compares and analyzes data points and international companies on a daily basis to find and optimize portfolio exposures.

With a properly designed framework, a Knowledge Graph’s AI-based exposure engine can draw inferences to understand the dynamic market trends constantly driving returns while promoting concepts investors feel strongly about. Properly deployed, AI-based thematic investment strategies can instantly create new strategies or power existing ones – and in a fraction of the cost and time that traditional analysis could yield.

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Ruggero Gramatica is founder and CEO of Yewno, innovator of the Knowledge graph that generates actionable knowledge from today’s vast informationYewno has created an extensive multi-domain knowledge graph using proprietary AI algorithms, combined with a multi-disciplinary technology platform that extracts insights and delivers products and services tailored to specific industries. Yewno generates actionable knowledge from the ever-increasing amount of information available today.

As a pioneer in the Knowledge Economy and the innovator of the proprietary Yewno Knowledge Graph, an artificial intelligence-based framework powered by billions of disparate data sources, Yewno provides continuously evolving inferences that uncover unexpected insights for financial services, education, life sciences, government and beyond.  By delivering more meaningful intelligence, Yewno is revolutionizing how information is processed and understood, enabling users to more quickly analyze complex problems and improve decision-making. For more information, visit https://www.yewno.com/.