Sustainable Payments The Next Frontier

In providing the fuel and rails for the modern economy, the potential for payments to impact on sustainability cannot be underestimated. As rapid, global digitization continues to transform all aspects of our lives, payments are pivotal: almost every digital activity relies on a payment system.

As a result, there is a responsibility incumbent on payment providers in funding and increasing awareness to sustainability.

Amongst both businesses and consumers, there is also a greater awareness of the role of sustainable finance, which is playing an increasingly critical part in influencing investment decisions. ESG (Environmental, Social and Governance) initiatives undertaken by payments can play a huge role in influencing these decisions.

Why is a sustainable payments industry important?

Firstly, necessity. The pandemic has significantly changed the structure of the economy, causing a decline of physical cash and digitizing businesses – all contributing to the reduction of reliance on carbon emitting processes.

The second reason is consumers. Regardless of industry, consumers are increasingly choosing businesses that share their environmental goals.

Consumers are also influencing investor pressure. Businesses are now looking to invest in environmentally friendly ways: two out of three French and German retail investors say they will invest in sustainable ways even if there is cost involved2. This is also visible in the green bond market, in 2022 green bond issuance has increased 49% year-on-year, with the market set to hit $1 trillion globally in 20213.

The third reason is regulatory. Increase in regulations, especially within Europe, is driving transparency in this space, with change being brought about thanks to the Paris agreement, COP 26 and other targeted regulations.

Challenges in the sustainable payments industry

  • Greenwashing
    Different standards, definitions and regulations can cause confusion and allow ‘greenwashing’. Incoming regulations will force industry standards and transparency, but rising focus on greenwashing is driving financial institutions to take a more cautious to ESG-linked products and solutions.
  • Geopolitical tensions
    World events can have a ‘butterfly effect’, increasing cost of living. This can result in challenges such as an impact on consumer demand, and the likelihood of consumers choosing green options when faced with financial insecurity.
  • Unintended consequences
    If not managed carefully, sustainable financing could cause unforeseen negative effects on society, such as job losses as a result of cutting finance to fossil fuel industries. Other unintended consequences for green initiatives should also be considered, for example by-products of electric cars including toxic and non-recyclable batteries.

How is J.P. Morgan making payments environmentally sustainable?

The payments scope is wide – stretching across every conceivable industry. As a common denominator between these industries, we have undertaken a program of workshops and client meetings to  recognize and support ESG needs, which vary considerably between industries. Environmental efforts are  concentrated for technology, media and telecoms as well as consumer and retail, diversified industries and natural resources. However, healthcare, utilities and public sector, alongside Financial Institutions, are targeting their focus on social and governance concerns.

Our approach to ESG management includes having robust governance systems, risk management and controls at a firmwide level. Equally important for us in J.P. Morgan is the social aspect –  investing in our employees and cultivating a diverse and inclusive work environment, and working to strengthen the communities in which we live and work.  At J.P. Morgan, we are advancing sustainable solutions for our clients and within our operations in several ways:

  • Minimizing the environmental impacts of our physical operations
  • Maintain carbon neutral operations since 2020
  • Transition J.P. Morgan’s fleet to electric vehicles by 2025
  • 100% paper purchased from renewable sources and reduce office paper by 90%
  • Working with organizations to advance sustainable development

Financing positive ‘green’ solutions. We are aiming to finance and facilitate more than $2.5 trillion over 10 years to advance climate action and sustainable development, including $1 trillion for green initiatives.

Last year, J.P. Morgan released the 2030 emission reduction targets for the Oil & Gas, Electric Power, and Auto Manufacturing financing portfolios4. In addition, we have expanded our financing restrictions on activities such as oil and gas development in the Arctic.

Specific to payments, we are developing financial solutions that drive action on climate change and generate other positive environmental impacts. In sustainable Supply Chain Finance in particular, our compelling alliance with Taulia and Ecovadis provides a sustainable SCF program that assesses sustainability of suppliers and offers tired pricing based on rating.

Based on our conversations with multi-national corporates in Europe, it is clear that sustainability sits at the heart of their corporate strategy for the future.

Every company has become a climate company in its own right, as we all work towards a common goal of limiting the impact of climate change. At J.P. Morgan, we would like to reiterate our commitment to supporting our clients, communities and colleagues by working towards a new frontier of sustainable payments where we not only invest in our platforms but in our planet.

Source: Earth Day 2022 – Sustainable Payments | J.P. Morgan

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2030 Agenda for Sustainable Development: Malaysia forwards three proposals to boost international cooperation Malay Mail

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How To Embrace The Post-Pandemic, Digital-Driven Future Of Work

https://i0.wp.com/onlinemarketingscoops.com/wp-content/uploads/2021/06/Main-Picture-1024x683-1.jpg?resize=840%2C560&ssl=1

Digital will separate the winners from the laggards in the hypercompetitive, post-pandemic business landscape, says Ben Pring, Managing Director of Cognizant’s Center for the Future of Work. We undertook a global, multi-industry study to understand how businesses are preparing for this future and here’s what we found.

COVID-19 changed digital from a nice-to-have adjunct to a must-have tool at the core of the enterprise. The pandemic forced businesses to reassess how they strategize and execute their digital ambitions in a world that has migrated online, possibly for good in many areas. Those that did not prioritize digital prior to the pandemic found that procrastination was no longer an option — the digital landscape is hypercompetitive.

The Cognizant Center for the Future of Work (CFoW), working with Oxford Economics, recently surveyed 4,000 C-level executives globally to understand how they are putting digital to use and what they hope to achieve in the coming years.

The CFoW found that digital technologies are key to success in the coming years and uncovered six key steps that all organizations can take to more fruitfully apply to gear-up for the fast unfolding digital future:

  • Scrutinize everything because it’s going to change. From how and where employees work, to how customers are engaged, and which products and services are now viable as customer needs and behaviors evolve rapidly.
  • Make technology a partner in work. Innovations in AI, blockchain, natural language processing, IoT and 5G communications are ushering in decades of change ahead and will drive new levels of functionality and performance.
  • Build new workflows to reach new performance thresholds. The most predictable, rote and repetitive activities need to be handed off to software, while humans specialize in using judgment, creativity and language.
  • Make digital competency the prime competency for everyone. No matter what type of work needs to be done, it must have a digital component. Levels of digital literacy need to be built out even among non-technologists, including specialized skills.
  • Begin a skills renaissance. Digital skills such as big data specialists, process automation experts, security analysts, etc. aren’t easy to acquire. To overcome skills shortages, organizations will need to work harder to retain and engage workers.
  • Employees want jobs, but they also want meaning from jobs. How can businesses use intelligent algorithms to take increasing proportions of tasks off workers’ plates, allowing them to spend their time creating value? This search for meaning stretches beyond the individual tasks of the job to what the organization itself stands for.

Here are a few key findings from our research:

Redesigning the workplace is just the beginning: The virus will force enterprises to ask more strategic questions.

A mesh of machine emerges: While IoT is beginning to take hold, few respondents have piloted 5G projects. But over time , the mesh of machines created by IoT and 5G will serve as the foundation for news levels of functionality and possibility.

The 3As-AI , automation and analytics are the engines of digitization: To make the future of work happen, the 3As are emerging as a sophisticated and complex set of tools more deeply embedded in processes.

To learn more, read our whitepaper “The Work Ahead: Digital First (to Last)” or see the full Work Ahead study series.

Ben Pring leads Cognizant’s Center for the Future of Work and is a coauthor of the books Monster: A Tough Love Letter On Taming The Machines That Rule Our Jobs, Lives, and Future, What To Do When Machines Do Everything and Code Halos: How the Digital Lives of People, Things, and Organizations Are Changing the Rules of Business. In 2018, he was a Bilderberg Meeting participant. He previously spent 15 years with Gartner as a senior industry analyst, researching and advising on areas such as cloud computing and global sourcing. He can be reached at Benjamin.Pring@cognizant.com

Source: How To Embrace The Post-Pandemic, Digital-Driven Future Of Work

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Critics:

Digitalization  is the adoption of digital technology to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technology. Digital solutions may enable – in addition to efficiency via automation – new types of innovation and creativity, rather than simply enhancing and supporting traditional methods.

One aspect of digital transformation is the concept of ‘going paperless‘ or reaching a ‘digital business maturity’ affecting both individual businesses and whole segments of society, such as government,mass communications,art, health care, and science.

Digital transformation is not proceeding at the same pace everywhere. According to the McKinsey Global Institute‘s 2016 Industry Digitization Index, Europe is currently operating at 12% of its digital potential, while the United States is operating at 18%. Within Europe, Germany operates at 10% of its digital potential, while the United Kingdom is almost on par with the United States at 17%.

One example of digital transformation is the use of cloud computing. This reduces reliance on user-owned hardware and increases reliance on subscription-based cloud services. Some of these digital solutions enhance capabilities of traditional software products (e.g. Microsoft Office compared to Office 365) while others are entirely cloud based (e.g. Google Docs).

As the companies providing the services are guaranteed of regular (usually monthly) recurring revenue from subscriptions, they are able to finance ongoing development with reduced risk (historically most software companies derived the majority of their revenue from users upgrading, and had to invest upfront in developing sufficient new features and benefits to encourage users to upgrade), and delivering more frequent updates often using forms of agile software development internally. This subscription model also reduces software piracy, which is a major benefit to the vendor.

Unlike digitization, digitalization is the ‘organizational process’ or ‘business process’ of the technologically-induced change within industries, organizations, markets and branches. Digitalization of manufacturing industries has enabled new production processes and much of the phenomena today known as the Internet of Things, Industrial Internet, Industry 4.0, machine to machine communication, artificial intelligence and machine vision.

Digitalization of business and organizations has induced new business models (such as freemium), new eGovernment services, electronic payment, office automation and paperless office processes, using technologies such as smart phones, web applications, cloud services, electronic identification, blockchain, smart contracts and cryptocurrencies, and also business intelligence using Big Data. Digitalization of education has induced e-learning and Mooc courses.

See also

 

Big Ethical Questions about the Future of AI

Artificial intelligence is already changing the way we live our daily lives and interact with machines. From optimizing supply chains to chatting with Amazon Alexa, artificial intelligence already has a profound impact on our society and economy. Over the coming years, that impact will only grow as the capabilities and applications of AI continue to expand.

AI promises to make our lives easier and more connected than ever. However, there are serious ethical considerations to any technology that affects society so profoundly. This is especially true in the case of designing and creating intelligence that humans will interact with and trust. Experts have warned about the serious ethical dangers involved in developing AI too quickly or without proper forethought. These are the top issues keeping AI researchers up at night.

Bias: Is AI fair

Bias is a well-established facet of AI (or of human intelligence, for that matter). AI takes on the biases of the dataset it learns from. This means that if researchers train an AI on data that are skewed for race, gender, education, wealth, or any other point of bias, the AI will learn that bias. For instance, an artificial intelligence application used to predict future criminals in the United States showed higher risk scores and recommended harsher actions for black people than white based on the racial bias in America’s criminal incarceration data.

Of course, the challenge with AI training is there’s no such thing as a perfect dataset. There will always be under- and overrepresentation in any sample. These are not problems that can be addressed quickly. Mitigating bias in training data and providing equal treatment from AI is a major key to developing ethical artificial intelligence.

Liability: Who is responsible for AI?

Last month when an Uber autonomous vehicle killed a pedestrian, it raised many ethical questions. Chief among them is “Who is responsible, and who’s to blame when something goes wrong?” One could blame the developer who wrote the code, the sensor hardware manufacturer, Uber itself, the Uber supervisor sitting in the car, or the pedestrian for crossing outside a crosswalk.

Developing AI will have errors, long-term changes, and unforeseen consequences of the technology. Since AI is so complex, determining liability isn’t trivial. This is especially true when AI has serious implications on human lives, like piloting vehicles, determining prison sentences, or automating university admissions. These decisions will affect real people for the rest of their lives. On one hand, AI may be able to handle these situations more safely and efficiently than humans. On the other hand, it’s unrealistic to expect AI will never make a mistake. Should we write that off as the cost of switching to AI systems, or should we prosecute AI developers when their models inevitably make mistakes?

Security: How do we protect access to AI from bad actors?

As AI becomes more powerful across our society, it will also become more dangerous as a weapon. It’s possible to imagine a scary scenario where a bad actor takes over the AI model that controls a city’s water supply, power grid, or traffic signals. More scary is the militarization of AI, where robots learn to fight and drones can fly themselves into combat.

Cybersecurity will become more important than ever. Controlling access to the power of AI is a huge challenge and a difficult tightrope to walk. We shouldn’t centralise the benefits of AI, but we also don’t want the dangers of AI to spread. This becomes especially challenging in the coming years as AI becomes more intelligent and faster than our brains by an order of magnitude.

Human Interaction: Will we stop talking to one another?

An interesting ethical dilemma of AI is the decline in human interaction. Now more than any time in history it’s possible to entertain yourself at home, alone. Online shopping means you don’t ever have to go out if you don’t want to.

While most of us still have a social life, the amount of in-person interactions we have has diminished. Now, we’re content to maintain relationships via text messages and Facebook posts. In the future, AI could be a better friend to you than your closest friends. It could learn what you like and tell you what you want to hear. Many have worried that this digitization (and perhaps eventual replacement) of human relationships is sacrificing an essential, social part of our humanity.

Employment: Is AI getting rid of jobs?

This is a concern that repeatedly appears in the press. It’s true that AI will be able to do some of today’s jobs better than humans. Inevitably, those people will lose their jobs, and it will take a major societal initiative to retrain those employees for new work. However, it’s likely that AI will replace jobs that were boring, menial, or unfulfilling. Individuals will be able to spend their time on more creative pursuits, and higher-level tasks. While jobs will go away, AI will also create new markets, industries, and jobs for future generations.

Wealth Inequality: Who benefits from AI?

The companies who are spending the most on AI development today are companies that have a lot of money to spend. A major ethical concern is AI will only serve to centralizecoro wealth further. If an employer can lay off workers and replace them with unpaid AI, then it can generate the same amount of profit without the need to pay for employees.

Machines will create wealth more than ever in the economy of the future. Governments and corporations should start thinking now about how we redistribute that wealth so that everyone can participate in the AI-powered economy.

Power & Control: Who decides how to deploy AI?

Along with the centralization of wealth comes the centralization of power and control. The companies that control AI will have tremendous influence over how our society thinks and acts each day. Regulating the development and operation of AI applications will be critical for governments and consumers. Just as we’ve recently seen Facebook get in trouble for the influence its technology and advertising has had on society, we might also see AI regulations that codify equal opportunity for everyone and consumer data privacy.

Robot Rights: Can AI suffer?

A more conceptual ethical concern is whether AI can or should have rights. As a piece of computer code, it’s tempting to think that artificially intelligent systems can’t have feelings. You can get angry with Siri or Alexa without hurting their feelings. However, it’s clear that consciousness and intelligence operate on a system of reward and aversion. As artificially intelligent machines become smarter than us, we’ll want them to be our partners, not our enemies. Codifying humane treatment of machines could play a big role in that.

Ethics in AI in the coming years

Artificial intelligence is one of the most promising technological innovations in human history. It could help us solve a myriad of technical, economic, and societal problems. However, it will also come with serious drawbacks and ethical challenges. It’s important that experts and consumers alike be mindful of these questions, as they’ll determine the success and fairness of AI over the coming years.

By: By Steve Kilpatrick
Co-Founder & Director
Artificial Intelligence & Machine Learning

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Building Business Stability In An Unstable World

Introducing Digital Factory 4.0, the future of effortless, connected, and proactive operations. 

I’ve seen some things. 

Back in 2000, I watched as the soaring dot com economy plummeted back to Earth. Then there was the gut-wrenching housing crisis of 2008. Still, I hardly envisioned a global pandemic that would drive 3,600 American businesses into bankruptcy in the first six months of 2020 alone.   

The scope of these bankruptcies are unprecedented, yet they underscore an old business maxim: the time to prepare for a crisis is before it happens. In an unpredictable world, futureproofing your business isn’t optional. COVID-19 is one example of instability, but it’s easy to think of others geopolitics, climate change, and societal tension to name a few. And while every industry confronts these challenges, not every industry is similarly at risk.  

Introducing Digital Factory 4.0  

Manufacturers are particularly exposed to the economic impacts of COVID-19 because of their global supply chains, interactive working environments, and high sensitivity to downstream demand. These factors place them at risk from future crises as well. As a result, their post-pandemic planning must include process alterations for COVID-19 and a comprehensive strategy for whatever comes next.  

Fortunately, in this digital day and age we have the tools to create resilience for this pandemic and beyond.  

The first step is the complete digitization and connection of factory operations through automation and digital workflows. This will create what I like to call Digital Factory 4.0.  

This factory represents a fourth revolution within manufacturing. In the first, steam power mechanized production; in the second, electricity created mass production; in the third, information technology automated and globalized that production.  

Now, in the fourth, emerging technologies, including artificial intelligence and the internet of things (IoT), are combining to digitize, automate, and transform the factory entirely. 

Digital nervous system 

Digital Factory 4.0 is based on a digital nervous system that ties the full manufacturing value chain together and makes all operations effortless, connected, and proactive. This nervous system consists of workflows that eliminate silos and create a connected enterprise of universal visibility.   

On the factory floor, insignificant problems quickly ripple into larger delays down the line when machine operators lack the knowledge to remediate the issue. Something as small as a misprinted label can throw the entire production process into disarray.  

In Digital Factory 4.0, notes detailing past machine fixes, a comprehensive knowledge base, and a workflow-powered connection to an outside technician are all accessible through a mobile device linked to the factory’s digital nervous system. Employees have the information they need at their fingertips, operations flow effortlessly, and overall equipment efficiency (OEE) is improved throughout the factory.  

In the event of a larger breakdown, information about downstream effect is quickly cascaded to the relevant parties via automated workflows. Information captured in these workflows, along with that from IoT sensors, helps manufacturers better understand the trade-offs that limit or increase capacity.   

Oh geez...just screens with code looking very technological. Bleep bloop!
A digital nervous system connects the Digital Factory 4.0. Getty Images/iStockphoto

Intelligent quality control 

World-class operations extend beyond maintenance and information dissemination to quality control and product development—two areas of significant expense.  

For example, when a manufacturer I worked with altered its pet food recipe, it unknowingly shipped bags with heavier individual pellets and thus more food than necessary. That compounded into a noticeable cost.  

Digital Factory 4.0 addresses this problem in two ways. First, IoT sensors identify discrepancies immediately and trigger a disruption workflow that drives actions to resolve the complication before production is impacted. This is intelligent quality control. Again, it’s both effortless and connected.  

Second, by digitizing product development—running simulations on a digital twin of the physical product—we can decrease parts per million (PPM) defective rates and proactively address quality issues that arise when we, for instance, change a recipe.  

Along with improved OEE, decreased PPM translates to higher margins and greater profit, ensuring a sustainable and resilient factory.  

Connecting teams and people 

Most important, Digital Factory 4.0 connects teams, keeping the workforce healthy and engaged while managing for regulatory compliance. This is especially important as leaders consider how to safely navigate the workplace during the COVID-19 pandemic. 

ServiceNow’s Contact Tracing app, for example, uses system data (badge scans, workstation location, etc.) to identify and isolate employees who come in contact with an individual infected by COVID-19. It’s one way to ensure a safe return to work, and it’s also indicative of a core tenet of connected teams: the use of employee data—on everything from common challenges to health and wellness—to build a sustainable workforce.  

For example, many manufacturing injuries can be linked to addressable root cause issues. By aggregating and analyzing information on these injuries, we can pinpoint causes and shift processes. The data also informs other areas in the organization, such as risk, compliance, and workforce planning.  

Digital Factory 4.0 is about getting access to this data on the assumption that all the information we need to perfectly optimize operations is readily available—if only we could see it.  

With COVID-19 placing pressure on manufacturers like never before, it’s the organizations who digitize operations and unlock their data that will survive, reinvest, and continuously improve.

Tasker Generes

Tasker Generes

Tasker Generes is global head of connected enterprise at ServiceNow, crafting strategy for the connected enterprise leveraging IoT, BlockChain, and AI while also providing executive level advisory to help companies modernize, transform and innovate. He is the author of 87 patent claims around ConnectedOperations, ConnectedHuman, ConnectedSecurity and ConnectedService. Prior to joining ServiceNow, Tasker was chief technology officer at Amtrak and ran his own consulting firm Silos to Service Solutions Inc., bringing business and IT together to leapfrog their competition through focused service. Through his work at IBM as chief technologist for service management solutions, Tasker developed a deep depth of knowledge and experience in leading global service management delivery across process, technology, organization and information. At IBM, he also served as co-chair of LEAP (Leadership Education for Asia-Pacifics). Tasker earned his Master of Project Management degree from George Washington University School of Management and a Bachelor’s degree in Economics from the University of California, San Diego

Source: Forbes

Digitization Is Poised To Transform Steel Plants

We live in a digital age, and our production processes need to evolve to reflect that fact. Converting traditional production environments into highly automated “smart” plants will entail fundamental changes in the way metals manufacturers interact with their suppliers and customers. When technology works in perfect harmony with the different aspects of metals production, the effect can be compared to that of a skilled orchestra’s performance……………

Source: Digitization Is Poised To Transform Steel Plants

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