Business Insider and eMarketer analysts estimate that the volume of global e-trade will amount to $3.914 trillion in 2020. See the main results of their report below.

Online sales in Western Europe, with an overall decline in retail turnover by 9.9%, will grow by 16.9% reaching $498.32 billion by the end of the year. The earlier predicted figure is 8.8%, which is $10.83 billion less than the current forecast.

“We previously expected retail sales in eCommerce to account for 11.0% of total retail by the end of the year, but we revised this figure to 13.2%,” the report says.

A number of European countries will grow significantly above the general market. Thus, online stores in Spain will increase their sales by 22.9%, the highest rate in Western Europe and one of the fastest in the world. The market of the Netherlands will grow by 21.9%, and Italy – by 20.5%.

Due to China’s overwhelming dominance in the global e-commerce market, the Asia-Pacific region holds a 62.6% share of the total market. North America and Western Europe will have shares of 19.1% and 12.7% respectively by the end of the year.

In the United States, the top ten online retailers will account for 60.1% of total e-commerce turnover in 2020, up from 58.2% last year. Top 5 sellers: Amazon, eBay, Walmart, Apple, the Home Depot. In the past few months, consumers have increasingly turned online to networks such as Target and Costco. During the pandemic, each of these companies experienced a surge in online sales.

“We expect that the top 10 retail companies engaged in e-commerce will increase the volume of online sales at a faster pace. They will increase by 21.8%,” the authors of the report believe.

Mobile commerce has shown a solid growth recently: in the UK, it accounts for about half of all online orders. The most active of the European countries is growing m-commerce in Germany. In the US, the pandemic has shown that young people also prefer smartphones to computers.

This year the number of “mobile buyers” in the US (those who used their mobile device to make at least one purchase through a mobile site or application) will reach 167.8 million. By 2024 this figure will grow to 187.5 million people, or two-thirds of the population of the USA.

In the 18-24 age group, this is 75% of users, and in the 25-34 group – all 90%. But even here, China will overtake other countries: the average time that Chinese people spend daily on their smartphones will grow this year to 2 hours 43 minutes, which is 17.9% more than a year earlier.

*our special thanks to www.e-pepper.ru

The pandemic clearly showed that in fact, the only alternative to closing a business was online sales. Even if a company’s website was in its infancy, it was urgently setting up standard tools for e-commerce: lead generation, traffic generation, and sales. The key problem that remained was attracting the attention of potential customers to their resource. It was even more difficult as people started to buy less because of falling real incomes and under stress from viral threats and long self-isolation.

Customers who once refused to buy a product of a certain brand return with great difficulty. The company, which lost the ability to remind customers of itself in the usual channel during isolation, had to use online loyalty tools to return sales.

Thus, in these difficult circumstances, when customer interest is at a very low level, marketers need not only to bring a potential buyer to the retailer’s site, but also to show them exactly those products that they are most likely to like, otherwise the purchase will not take place.

Data researchers and data scientists help you find out your customers ‘ preferences. Using predictive analytics tools, they identify people with common behavior patterns among all their clients, form clusters, and then use it to prepare the most personalized offer for each cluster.

Clusterization is not about segmenting customers on formal grounds like by age, gender, place of residence. Clusterization helps you identify truly homogeneous groups with similar attitudes to purchases and the same problems, preferences, interests, or lifestyle. This mathematical procedure is based on a statistical approach and allows you to programmatically identify the most significant parameters of consumer behavior of buyers. Then, again, using software methods, you can create trade offers for many identified small groups and promote them through different channels.

For instance, a customer is looking for the products they need on your website and popular items from the related category are automatically pulled up.

Connecting recommendation services to online store sites gives good results.

When the data analyst has formed clusters of buyers, it is necessary to predict which product is likely to be offered to which clusters of buyers. Knowing the preferences of customers in a particular cluster, the specialist builds a table for the probability of purchasing a specific product.

For a company with a customer base of about 12 million people and about 200 thousand products in the active range, such a table can consist of more than 240 billion cells: horizontally-people, vertically-products. This amount of data will break Excel down, but machine learning can handle this task.

The table can be filtered by the highest probability of purchase (we are interested in at least 50%), then we will see everyone who is sure to buy these products. At the same time, you will be able to find out which of the buyers does not buy anything and creates an outflow. Using the table, we try to offer this segment of customers several types of goods and see how customers react.

It is possible to predict the purchase of goods not only here and now, but also for a long time.

Predictive analytics is still a new marketing tool, and retail, of course, is very heterogeneous, so the wariness of many companies is clear: will machine learning be effective in a particular segment of the industry? In this case, you should first conduct a pilot project and based on its results, make a decision to launch the service into productive operation. You should start using machine learning technologies by embedding models in existing processes and systems (for example, CRM) to get the fastest possible return.

However, at the beginning of online development, it is too early to engage in data analytics, since the company does not have stable traffic yet and, in fact, there is nothing to analyze. Any work of this kind begins when a good amount of data already collected.

Major retailers’ IT departments understand that it is easier to give the task to an experienced third-party contractor than to look for specialists inside, especially if the company has never had such a project. You need to look for companies that consist of industry experts and a data science team. Projects can be called effective when their results are transmitted with the source code, open source technologies are used, and the customer company forms its own competence center based on the results of the project.

If the company is ready to finance the development of its own e-commerce team, this will be the best investment. After the project it will keep its own specialists and raise funds through predictive analytics. Client traffic generation will continue. With constant work in this direction, the model, which is continuously in the process of self-learning, will learn data better and make predictions more accurately.

If you can’t afford to hire data scientists, you can optimally use predictive analytics based on cloud services or SaaS (Software as a Service) solutions.

Covid-19 has changed economic and social life making our dependence on digital technologies even stronger. Of course the trend has had a great impact on the banking sphere which started experimenting with digital technologies even before the virus appeared. Even before Covid-19 retail banking started changing: branch usage was declining while customers preferred using digital channels to manage their money. Adopting digital technologies is quick in the US and the EU countries like Italy and Spain. In other markets the trend is also visible but goes slower. According to McKinsey report dated July 30, 2020 top performers in the banking sphere made a shift to digital technologies before the pandemic and greatly outperformed their competitors in terms of distribution channels.

In terms of digital services the research has shown great customer satisfaction (60-85%) with banking from home in the EU and the US. Even elderly clients got used to transactions via mobile apps. Biometric authentication, quick balance checks, and easy transfers are increasingly table stakes for banking apps. However, leaders take a customer-centric mindset to developing new features that will make users even more attached to digital technologies. Personalized home pages in the apps are already widely used and hailed by clients.

While in many markets the crisis caused a significant drop in monthly unit sales across all channels, it also accelerated the sales mix redistribution as channels recovered at varying speeds. This has made digital sales penetration jump especially with leading banks. Leading banks doubled their digital cross-sell rates (digital sales per digital user) between 2015 and 2019 to 4.2 times that of slow adopters. To achieve this result they regularly tested and launched new capabilities, used customer-relationship-management (CRM) tools to create preapproved offers, streamlined journeys with prefilled applications, and used digital signatures for instant fulfillment. A lot of customer-behavior analysis has also contributed to sales increase.

Research has shown that before Covid-19 outbreak inbound calls to contact centers started giving way to other communication channels. But the first days of self-isolation were characterized by a steep rise of such calls since uncertainty requires contact. At the same time in markets with developed digital communication channels this rise wasn’t that steep. As a result, the pandemic has brightly illustrated demand for digital communication in banking. Practice demonstrates that interactive voice response (IVR) is helpful but modern banks are turning to next-generation tools, data, and analytics to optimize the end-to-end call funnel. Chatbots are used to retain customers in digital, reducing inbound calls. IVRs are evolving to be conversational and enhanced with contextual awareness that leverages historical interaction data to provide personalized query resolution and protect agent capacity. In the research by McKinsey it is mentioned that many banks have also experimented with remote advisory models, such as branch-to-branch, branch-to-hub, or hub-to-home. These capabilities are said to offer convenient access to complex advice and match customers to the right specialists, making conversations more efficient.

The virus and the social distancing caused by it triggered the closure of many branch offices even among leading banks. After the gradual revival from self-isolation the trend remained viable. Some banks boldly cut down the number of branches while others acted in favor of gradual changes. Yet, McKinsey research demonstrates that the bold bankers happen to be more efficient and successful. The reduction was quick but it was also about operational restructuring. To shift the operating model, leaders began to reskill profiles toward universal banker roles to better respond to the lower volume but wider variety of demand coming into branches. Branch formats were changed to create formats tailored to customer needs in specific areas. These ranged from large flagship branches to mini branches with a high degree of self-service, remote advice capabilities, and flexible opening time in low-traffic areas.

Thus, the pandemic has accelerated the process of the banking sector digitalization. The digitalization itself is beneficial for banks as it leads to cost-cutting and to clients who become more satisfied with managing finances from home and using customized digital banking products.

To learn more you can consult the full report: https://www.mckinsey.com/industries/financial-services/our-insights/breaking-away-from-the-pack-in-the-next-normal-of-retail-banking-distribution#

Artificial intelligence will play a central role in the economy of the future and serve as a growth driver. Application of artificial intelligence ranges from predictive analytics and chatbots to fraud prevention and regulatory compliance. Banks ‘ investments in machine learning technologies grow by an average of 46.2% annually, but many projects remain incomplete. So the question is how to make such projects effective.

Two effective approaches to implementing AI in banking

For the past three years the banking industry has been gripped by a real “gold rush” in terms of artificial intelligence. Banks have created a lot of data lakes, launched a lot of AI initiatives, and spared no expense in attracting the best young specialists in data processing and analysis.

And what do we see as a result of these 3 years? There was a lot of sand and very, very little gold. According to Gartner, 80% of AI projects have failed or have not progressed beyond prototype development.

What is the reason for this? It seems that all the necessary prerequisites were available for the success of the projects:

• a large number of open source machine learning algorithms have been developed;
• there are significantly more data sets accumulated than one can imagine;
• computing resources are widely available.

Evaluating the results, one can assume that banks are very actively engaged in business, without having thought through a strategy for working with data. In many large projects that have been launched, responsibility has been assigned to its departments, rather than to business units.

For the AI projects to bring results, it makes sense to follow two strategic approaches.

The first is that machine learning capabilities are adapted, implemented and integrated into all banking applications for the front office and back office, including for digital interactions with customers, compliance with regulations, financial management and HR management. As a result, customers can use AI capabilities directly at the time of the transaction.

The second approach is to focus on specific cases with a clear understanding of business goals. Being specific is helpful for performance assessment and result orientation.

Indeed, rushing for AI projects banks faced many difficulties and here come recommendations for making such projects effective:

• start small and expand your approach,
• find out the needs and demonstrate the benefits,
• first of all, think about business results,
• assign a responsible manager from the main business, not from the IT office.

How banks can develop an effective AI strategy

Many banks initially treated data lakes as a sacred cow when working with AI. However, some of these data lakes have unfortunately turned into swamps. As a result, data processing and analysis specialists and developers began to move to financial technology companies where there were no problems with data and getting access to it, unlike in banks.

Gartner analysts estimate that 70% of the AI effort is spent on data management: getting, cleaning, preparing, and processing.

To ensure that customers do not have to spend time moving data, updating it, and ensuring its integrity, it makes sense to implement machine learning algorithms, such as R and Python, directly in the data source in real time.

At the same time, it is possible to implement innovative tools for autonomous data management to reduce the load and significantly simplify all standard AI operations. This radically changes the paradigm of working with AI data, as users can fully focus on their strategic analysis.

Thus, banks will be able to extract the gold that is hidden in various internal data sources faster and with much less effort.

Artificial intelligence under control

AI conclusions reliability is of increasing concern to regulatory authorities in many countries, that is why they are increasing their supervision of banks ‘ initiatives in this area. Banks have to explain the logic of machine learning models to them. In particular, this applies to the use of AI in robots-investment consultants, for recommendations on transactions or monitoring compliance with regulatory requirements.

Regulatory authorities also have requirements for data localization. To meet these requirements, it is possible to create a virtual machine learning platform in the private cloud inside the data center, protected by firewalls. If data sets do not contain personal data, sometimes they can be processed in a hybrid environment or a public cloud.

Thus, continuous cooperation between banks, regulatory authorities, and technology partners is very important for transparency, reliability, and compliance with ethical values when banks work with AI.

Banks’  applications and applications of other similar organizations may stop working on smartphones manufactured by Huawei and Honor. The new restrictions on the Chinese company are reported by the Washington Post.

On August 13, Huawei’s temporary general license (TGL) expired. The license allowed the US companies to cooperate with Huawei, which is currently under sanctions. According to experts, due to the license loss, Google will stop producing security updates for Huawei smartphones and its subsidiary brand Honor. This applies to both new and old devices released before the Chinese corporation was included in the US sanctions list in May 2019.

It is reported that Huawei devices will no longer receive the SafetyNet certificate from Google. In this case, apps that require this certificate will stop working on smartphones. Experts explain that the manufacturer’s devices may be left without banking and payment applications, as well as some programs with built-in microtransactions.

Representatives of the US Commerce Department explain that the temporary delay is necessary in order for the US communication providers and other companies to find new suppliers instead of Huawei. It remains unknown whether the TGL will be extended. In a comment to the Washington Post  Huawei claims that it is assessing the potential consequences of the license expiration and is monitoring the situation.

On August 15, the Trump Administration granted the Pentagon a temporary waiver from a nationwide ban on contractors using Huawei products. The temporary suspension is valid from August 13 to September 30. During this time, defense contractors must find suppliers to substitute for the Chinese equipment.

Facebook has created a new division to manage all the company’s payment projects. It will be headed by Libra co-founder David Marcus, according to Bloomberg news.

The new division was named Facebook Financial or F2. Its team will be responsible for payment and trading services, including Facebook Pay, which the company plans to integrate into all its apps.

Facebook expects that the integration of payment services in Instagram, Messenger and WhatsApp will increase ad revenue and the amount of time users spend in apps.

“Facebook is developing many initiatives related to commercial activities. We thought it was time to develop a rational strategy at the company level, ” said David Marcus, head of the new project.

He will continue to lead Novi, a division that creates a digital wallet for storing the Libra cryptocurrency. In addition, he will develop the WhatsApp payment system in India and Brazil.

To assist him, Upwork Inc. former CEO Stephane Kasriel was invited to the position of Facebook Financial Vice President.

Marcus moved to Facebook from his position as  PayPal President in 2014 and managed Facebook Messenger for four years before launching Libra.

South Korean company Samsung Electronics has introduced its new product to the US market: a debit plastic card called Samsung Money by SoFi, linked to its mobile payment service Samsung Pay and released in collaboration with Mastercard and the fintech company SoFi.

According to experts, the release of  similar physical bank cards by Apple has had a big impact on Samsung’s decision to implement this project. What is happening reflects that despite the active penetration of contactless payment systems in the US (Apple Pay and Samsung Pay) consumer interest in the use of plastic remains significant. To satisfy consumer demand, Apple launched its plastic Apple Card and it is not surprising that Samsung decided to follow suit. To contrast with its competitor, Samsung offered black plastic for the design of its Samsung Money card. This is a perfect visual contrast to the white Apple Card.

The main advantages of the new product by Samsung in addition to the advanced technological component are the absence of any commissions for account maintenance and increased interest rates on deposits.

The launch of the card Samsung Money by SoFi is planned for this summer. To get it, you just need to apply to Samsung Pay and get approval to get a virtual Bank card, which you can immediately use on your smartphone. You can also add a Samsung Money plastic card with home delivery by post as a duplicate of your virtual card.

Naturally, Samsung Pay mobile app has all the necessary tools to manage your Samsung Money card: users can check their balance, view account statements, and track transactions. They can flag suspicious activity, suspend or resume spending on the card, freeze or unfreeze their card, change their pin code and assign a trusted contact.

Like all users of the Samsung Pay service in the United States, Samsung Money owners can sign up for the Samsung Rewards loyalty program, which enables them to earn points for each purchase made using the Samsung Pay service. Points can later be exchanged for money and credited to the card. The company also notes that the Samsung Money account is insured by the Federal Deposit Insurance Corporation (FDIC) up to $ 1.5 million.

Ingenico Group, the global leader in seamless payments, has welcomed a new partnership with the Saint-Sixtus Abbey, brewers of the Trappist Westvleteren, to provide a global payments solution that supports the increased international demand for its famous beer.

Saint-Sixtus Abbey of Westvleteren, which belongs to the Cistercians of Strict Observance, or Trappists, is a Roman Catholic abbey located in Westvleteren, in the Belgian Province of West Flanders. The Abbey is famous for its spiritual life, characterized by prayer, reading, and manual work, the three basic elements of Trappist life. It has also a reputation for its brewery, one of the several breweries of Trappist beer in Belgium. The monks of the Abbey started brewing beer alongside their monastic activities in 1839. All beer types produced in the Abbey carry the label of “Authentic Trappist Product”, which means they are brewed within the walls of a Trappist monastery under the control of the monks community. The production is limited and aims to cover costs of the Abbey’s operations, sponsorships of charitable initiatives and social projects.

Both the Abbey and the beer were little known until 2005, when a user-driven ranking website for craft beer enthusiasts named the Trappist Westvleteren the best beer in the world. Word of mouth made the beer a “must taste” product among beer connoisseurs. It has since been awarded the title four more times and was named as one of the best beers for taste, making international beer lovers enthusiastic to buy it.

Because of  this growing demand and the limited stock, the Abbey faced a number of issues with customers stockpiling products and reselling them for much higher prices. In 2019 the Abbey began cooperating with Ingenico to develop an online payment solution, which could control orders and enable foreign customers to buy their beloved beer without overpaying. Ingenico worked with the Abbey to establish a novel click and collect system with the ability to accept international payments over a very limited sales period. The payment solution is simple and secure with a user-friendly interface. It is characterized by a sophisticated fraud detection module which sets sales limits and blocks transactions as necessary. This has thwarted a number of fraud attempts against the monastery and greatly decreased black market reselling of the beer.

Benoit Boudier, Managing Director, SMB Online Europe at Ingenico, was quoted as saying, “We are extremely proud to be partnering with Westvleteren Abbey. It had a bespoke need as a growing business with its own peak sales times – the payments service the Abbey provides to its customers is integral to the growth and security of the business. So, we stepped in to provide a robust payments solution that supported the business’s growth while ensuring availability during times of greater demand. We’re delighted to have enabled it to continue to serve its customers via a click and collect system while providing the fraud protection it needs.”

Ingenico cooperates with businesses of various sizes to offer payments solutions and international payment capabilities that provide growth opportunities and correspond to the goals and needs that businesses face.

To learn more about Ingenico payment solutions you can consult https://www.ingenico.com/

To learn more about the Abbey and the beer you can visit the website

Garner is a leading research and advisory company founded in 1979. The company aims at providing senior managers with up-to-date tips on the most efficient and vibrant business trends and developments which equip senior decision-makers with the right information and tools for creating organizations of tomorrow. Gartner has developed its own methodology to illustrate how a new technology can be potentially viable and beneficial for businesses, how it might evolve over time and be applied in the most beneficial way. Indeed, when a new technology is launched, it is important to differentiate between hype and really promising innovations. Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities.

The research presented in this abstract provides an overview of technologies that might be efficient for frontline workers. The research appeared in July 2020 and takes into account the situation round Covid-19 and its impact on business and technologies that are to enable employees to work remotely. If we may say so, the research was inspired by the pandemic and looks at possible technologies that allow qualified personnel to work away from the office keeping in touch with the team, partners and clients.

The research concentrates on frontline workers who are subdivided into two groups: service and task workers. Service workers primarily spend their time performing client-facing activities. They typically represent the “face” of an organization to customers. Task workers are workers who primarily spend their time performing operational activities. They typically represent the “heart” of an organization. Naturally, both groups need to stay in touch with the organization and with clients despite Covid-19 limitations and new technologies provide this option. The Hype Cycle contains technologies designed primarily for task workers, but it also includes some technologies designed for both service and task workers. The research concentrates on 30 technologies disclosing their business benefits and viability. One of the most important research tables measures new technologies in terms of their benefit and the time period required for mainstream adoption.

Each of the 30 technologies from the table above is analyzed separately according to the following plan: expert name, technology definition, position and adoption speed justification, user advice, business impact, benefit rating, market penetration, maturity, sample vendors and recommended reading. It is clear from the table that at present the most beneficial and quick to be adopted are Cloud Office, Lone Worker Protection and Social Distancing Technologies. These technologies are analyzed by Gavin Tay, Leif-Olof Wallin and Nick Jones respectively. The potential benefit is to a great extend dictated by the current spread of Covid-19 all over the world and the necessity of social distancing to stop the virus spread. At the same time the research concentrates on technologies that have transformational benefit which enables new ways of doing business across industries that will result in major shifts in industry dynamics. Here the quickest to be adopted is Speech Recognition described by Anthony Mullen.

The Hype Cycle itself is illustrated by the following graph

Each of the phases on the graph is described in the research Appendixes. It is said that Plateau of Productivity is the most important phase as “the real-world benefits of the technology are demonstrated and accepted. Tools and methodologies are increasingly stable as they enter their second and third generations. Growing numbers of organizations feel comfortable with the reduced level of risk; the rapid growth phase of adoption begins”. And the graph illustrates that Cloud Office and Speech Recognition have the strongest business potential for frontline workers. The full research requires 98 min. for reading but taking into account the transformed business environment the reading can help you choose the right technologies for organizing efficient remote personnel performance.

Users of the American company Garmin, one of the world’s largest navigation equipment and “smart” watches manufacturers, faced a multi-hour failure of its services on July 22. The Garmin Connect service, designed to sync data on the physical activity of smartwatches’ owners, became completely unavailable, the company’s official website and the support service were disrupted: Garmin could not receive calls or emails from customers.

For several days until July 27 the services remained unavailable, an unusual situation for such a large international corporation as Garmin (Garmin’s revenue in 2019 amounts to more than $3.7 billion). According to some public sources, the cause of the failure was a hacker cyberattack on Garmin’s resources. The new WastedLocker ransomware that appeared back in May, like other similar malware, operates according to a particular scenario: it encrypts the victim’s data, deletes the original files, and then demands a huge sum as ransom. To “unlock” the required data hackers demand to transfer the ransom in cryptocurrency, usually in bitcoins. It is impossible for the victim to restore data without backup copies.

According to Malwarebytes analysts’ conclusions, WastedLocker creators are the hacker group Evil Corp. The group became world-known when the banking trojan Dridex infected thousands of computers around the world and was used for blackmail, fraud and identity theft. The impunity of Evil Corp costs the affected companies dearly. According to the US authorities, the total amount of damage caused by the group exceeds $100 million. The British authorities estimate damage to the UK alone at several hundred million pounds. They call Evil Corp the most significant threat in the field of cybercrime.

At the moment, Garmin services are gradually being restored. The Garmin Connect platform is available in a limited mode, and devices have started downloading data for syncing, but the process may take a long time, up to seven days. At the same time paying a “ransom” is not an option: Evil Corp is subject to sanctions from the US authorities, so if Garmin attempts to negotiate and pay the amount requested by fraudsters, it is likely to faces criminal prosecution since American companies are prohibited from participating in any transactions with members of the group. Besides, it doesn’t make sense to collaborate with the hackers as they are unable to provide any guarantees in case the ransom is paid .