Artificial Intelligence and Ethics

Artificial Intelligence and Ethics

#AIforgood #ethics #leadership #digitaldisruption #digitaltransformation

Enterprises must confront the ethical implications of AI use as they increasingly roll out technology that has the potential to reshape how humans interact with machines

Many enterprises are exploring how AI can help move their business forward, save time and money, and provide more value to all their stakeholders. However, most companies are missing the conversation about the ethical issues of AI use and adoption.
Even at this early stage of AI adoption, it’s important for enterprises to take ethical and responsible approaches when creating AI systems because the industry is already starting to see backlash against AI implementations that play loose with ethical concerns.
For example, Google recently saw pushback with its Google Duplex release that seems to show AI-enabled systems pretending to be humans. Microsoft saw significant issues with its Tay bot that started going off the rails. And, of course, who can ignore what Elon Musk and others are saying about the use of AI.
Yet enterprises are already starting to pay attention to the ethical issues of AI use. Microsoft, for example, has created the AI and Ethics in Engineering and Research Committee to make sure the company’s core values are included in the AI systems it creates.

How AI systems can be biased

AI systems can quickly find themselves in ethical trouble when left inadequately supervised. One notable example was Google’s image recognition tool mistakenly classifying black people as gorillas, and the aforementioned Tay chatbot becoming a racist, sexist bigot.
How could this happen? Plainly put, AI systems are only as good as their training data, and that training data has bias. Just like humans, AI systems need to be fed data and told what that data is in order to learn from it.
What happens when you feed biased training data to a machine is predictable: biased results. Bias in AI systems often stems from inherent human bias. When technologists build systems around their own experience — even when Silicon Valley has a notable diversity problem — or when they use training data that has had human bias involved historically, the data tends to reflect the lack of diversity or systemic bias.
Some of these AI technologies can have ethical implications.
Because of this, systems inherit this bias and start to erode the trust of users. Companies are starting to realize that if they plan to gain adoption of their AI systems and realize ROI, those AI systems must be trustworthy. Without trust, they won’t be used, and then the AI investment will be a waste.
Companies are combating inherent data bias by implementing programs to not only broaden the diversity of their data sets, but also the diversity of their teams. More diversity on teams enables a diverse group of people to feed systems different data points from which to learn. Organizations like AI4ALL are helping enterprises meet both of these anti-bias goals.

More human-like bots raise stakes for ethical AI use

At Google’s I/O event earlier this month, the company demoed Google Duplex, an experimental Google voice assistant that was shown via a prerecorded interaction of the system placing a phone call to a hair salon on a human agent’s behalf. The system did a reasonable enough job impersonating a human, even adding umms and mm-hmms, that the human on the other side was suitably fooled into thinking she was talking to another human.
This demo raised a number of significant and legitimate ethical issues of AI use. Why did the Duplex system try to fake being human? Why didn’t it just identity itself as a bot upfront? Is it OK to fool humans into thinking they’re talking to other humans?
Putting bots like this out into the real world where they pretend to be human, or even pretend to take over the identity of an actual human, can be a big problem. Humans don’t like being fooled. There’s already significant erosion in trust in online systems with people starting to not believe what they read, see or hear.
With bots like Duplex on the loose, people will soon stop believing anyone or anything they interact with via phone. People want to know who they are talking to. They seem to be fine with talking to humans or bots as long as the other party truthfully identifies itself.

Ethical AI is needed for broad AI adoption

Many in the industry are pursuing the creation of a code of ethics for bots to address potential issues, malicious or benign, that could arise, and to help us address them now before it’s too late. This code of ethics wouldn’t just address legitimate uses of bot technology, but also intentionally malicious uses of voice bots.
Imagine a malicious bot user instructing the tool to ask a parent to pick up their sick child at school in order to get them out of their house so a criminal can come in while they aren’t home and rob them. Bot calls from competing restaurants could make fake reservations, preventing actual customers from getting tables.
Also concerning are information disclosure issues and laws that are not up to date to deal with voice bots. For example, does it violate HIPAA laws for bots to call your doctor’s office to make an appointment and ask for medical information over the phone?
Forward-thinking companies see the need to create AI systems that address ethics and bias issues, and are taking active measures now. These enterprises have learned from previous cybersecurity issues that addressing trust-related concerns as an afterthought comes at a significant risk. As such, they are investing time and effort to address ethics concerns now before trust in AI systems is eroded to the point of no return. Other businesses should do so, too.

The Future of Work is here… what are you doing about it?

The Future of Work is here… what are you doing about it?

#futureofwork #digitaltransformation #shiftmindset #leadership

Retraining and reskilling workers in the age of automation

The world of work faces an epochal transition. By 2030, according to the a recent McKinsey Global Institute report, as many as 375 million workers—or roughly 14 percent of the global workforce—may need to switch occupational categories as digitization, automation, and advances in artificial intelligence disrupt the world of work. The kinds of skills companies require will shift, with profound implications for the career paths individuals will need to pursue.
How big is that challenge?
In terms of magnitude, it’s akin to coping with the large-scale shift from agricultural work to manufacturing that occurred in the early 20th century in North America and Europe, and more recently in China. But in terms of who must find new jobs, we are moving into uncharted territory. Those earlier workforce transformations took place over many decades, allowing older workers to retire and new entrants to the workforce to transition to the growing industries. But the speed of change today is potentially faster. The task confronting every economy, particularly advanced economies, will likely be to retrain and redeploy tens of millions of mid-career, middle-age workers. As the MGI report notes, “there are few precedents in which societies have successfully retrained such large numbers of people.”
So far, growing awareness of the scale of the task ahead has yet to translate into action. Indeed, public spending on labor-force training and support has fallen steadily for years in most member countries of the Organisation for Economic Co-Operation and Development (OECD). Nor do corporate-training budgets appear to be on any kind of upswing.
But that may be about to change.
Among companies on the front lines, according to a recent McKinsey survey, executives increasingly see investing in retraining and “upskilling” existing workers as an urgent business priority—and they also believe that this is an issue where corporations, not governments, must take the lead. Our survey, which was in the field in late 2017, polled more than 1,500 respondents from business, the public sector, and not for profits across regions, industries, and sectors. The analysis that follows focuses on answers from roughly 300 executives at companies with more than $100 million in annual revenues.
Among this group, 66 percent see “addressing potential skills gaps related to automation/digitization” within their workforce as at least a “top-ten priority.” Nearly 30 percent put it in the top five. The driver behind this sense of urgency is the accelerating pace of enterprise-wide transformation. Looking back over the past five years, only about a third of executives in our survey said technological change had caused them to retrain or replace more than a quarter of their employees.
But when they look out over the next five years, that narrative changes.
Sixty-two percent of executives believe they will need to retrain or replace more than a quarter of their workforce between now and 2023 due to advancing automation and digitization. The threat looms larger in the United States and Europe (64 percent and 70 percent respectively) than in the rest of the world (only 55 percent)—and it is felt especially acutely among the biggest companies. Seventy percent of executives at companies with more than $500 million in annual revenues see technological disruption over the next five years affecting more than a quarter of their workers.
Appropriately, this keen sense of the challenge ahead comes with a strong feeling of ownership. While they clearly do not expect to solve this alone—forging creative partnerships with a wide range of relevant players, for example, will be critical—by a nearly a 5:1 margin, the executives in our latest survey believe that corporations, not governments, educators, or individual workers, should take the lead in trying to close the looming skills gap. That’s the view of 64 percent of the private-sector executives in the United States who see this as a top-ten priority issue, and 59 percent in Europe
As for solutions, 82 percent of executives at companies with more than $100 million in annual revenues believe retraining and reskilling must be at least half of the answer to addressing their skills gap. Within that consensus, though, were clear regional differences. Fully 94 percent of those surveyed in Europe insisted the answer would either be an equal mix of hiring and retraining or mainly retraining versus a strong but less resounding 62 percent in this camp in the United States. By contrast, 35 percent of Americans thought the challenge would have to be met mainly or exclusively by hiring new talent, compared to just 7 percent in this camp in Europe
Now the bad news: only 16 percent of private-sector business leaders in this group feel “very prepared” to address potential skills gaps, with roughly twice as many feeling either “somewhat unprepared” or “very unprepared.” The majority felt “somewhat prepared”—hardly a clarion call of confidence.
What are the main barriers? About one-third of executives feel an urgent need to rethink and upgrade their current HR infrastructure. Many companies are also struggling to figure out how job roles will change and what kind of talent they will require over the next five to ten years. Some executives who saw this as a top priority—42 percent in the United States, 24 percent in Europe, and 31 percent in the rest of the world—admit they currently lack a “good understanding of how automation and/or digitization will affect our future skills needs.”
Such a high degree of anxiety is understandable. In our experience, too much traditional training and retraining goes off the rails because it delivers no clear pathway to new work, relies too heavily on theory versus practice, and fails to show a return on investment. Generation, a global youth employment not for profit founded in 2015 by McKinsey, deliberately set out to address those shortcomings. Operating in five countries across over 20 professions, Generation operates programs that focus on targeting training to where strong demand for jobs exists and gathers the data needed to prove the return on investment (ROI) to learners and employers. As a result, Generation’s more than 16,000 graduates have over 82 percent job placement, 72 percent job retention at one year, and two to six times higher income than prior to the program. Generation will soon pilot a new initiative, Re-Generation, to apply this same formula—which includes robust partnerships with employers, governments and not for profits—to helping mid-career employees learn new skills for new jobs.
For many companies, cracking the code on reskilling is partly about retaining their “license to operate” by empowering employees to be more productive. Thirty-eight percent of executives in our survey, across all regions, cited the desire to “align with our organization’s mission and values” as a key reason for taking action. In a similar vein, at last winter’s World Economic Forum in Davos, 80 percent of CEOs who were investing heavily in artificial intelligence also publicly pledged to retain and retrain existing employees.
But the biggest driver is this: as digitization, automation, and AI reshape whole industries and every enterprise, the only way to realize the potential productivity dividends from that investment will be to have the people and processes in place to capture it. Managing this transition well, in short, is not just a social good; it’s a competitive imperative. That’s why a resounding majority of respondents—64 percent across Europe, the United States, and the rest of the world—said the main reason they were willing to invest in retraining was “to increase employee productivity.”
We hear that thought echoed in a growing number of C-suite conversations we are having these days. At the moment, most top executives have far more questions than answers about what it will take to meet the reskilling challenge at the kind of scale the next decade will likely demand. They ask: How can I map the future against my current talent pool and processes? What part of future employment demand can I meet by retraining existing workers, and what is the ROI of doing so, versus simply hiring new ones? How best can I tap into what are, for me, nontraditional talent pools? What partners, either in the private, public, or nongovernmental-organization (NGO) sectors, might help me succeed—and what are our respective roles?
Good questions all.
Success will require first developing a granular map of how technology will change the skill requirements within your company. Once this is understood, the next step will be deciding whether to tap into new models of online and offline learning and training or partner with traditional educational providers. (Over time, a more fundamental rethinking of 100-year-old educational models will also be needed.) Policy makers will need to consider new forms of unemployment income and worker transition support, and foster more intensive and innovative collaboration between the public and private sectors. Individuals will need to step up too, as will governments. Depending on the speed and scale of the coming workforce transition, as MGI noted in its recent report, many countries may conclude they will need to undertake “initiatives on the scale of the Marshall plan.”
But for now, we simply take comfort from the clear message of our latest survey: among large companies, senior executives see an urgent need to rethink and retool their role in helping workers develop the right skills for a rapidly changing economy—and their will to meet this challenge is strong. That’s not a bad place to start.

About the author(s)

Pablo Illanes is a partner in McKinsey’s Stamford office, Susan Lund is a partner of the McKinsey Global Institute, Mona Mourshed and Scott Rutherford are senior partners in the Washington, DC, office, and Magnus Tyreman is a senior partner in the Stockholm office.
The Fourth Industrial Revolution and why it’s relevant

The Fourth Industrial Revolution and why it’s relevant

Sep 25, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.

By Klaus Schwab

Curated by Helena M. Herrero Lamuedra

We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before. We do not yet know just how it will unfold, but one thing is clear: the response to it must be integrated and comprehensive, involving all stakeholders of the global polity, from the public and private sectors to academia and civil society.

The First Industrial Revolution used water and steam power to mechanize production. The Second used electric power to create mass production. The Third used electronics and information technology to automate production. Now a Fourth Industrial Revolution is building on the Third, the digital revolution that has been occurring since the middle of the last century. It is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres.

There are three reasons why today’s transformations represent not merely a prolongation of the Third Industrial Revolution but rather the arrival of a Fourth and distinct one: velocity, scope, and systems impact. The speed of current breakthroughs has no historical precedent. When compared with previous industrial revolutions, the Fourth is evolving at an exponential rather than a linear pace. Moreover, it is disrupting almost every industry in every country. And the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance.

The possibilities of billions of people connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge, are unlimited. And these possibilities will be multiplied by emerging technology breakthroughs in fields such as artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing.

Already, artificial intelligence is all around us, from self-driving cars and drones to virtual assistants and software that translate or invest. Impressive progress has been made in AI in recent years, driven by exponential increases in computing power and by the availability of vast amounts of data, from software used to discover new drugs to algorithms used to predict our cultural interests. Digital fabrication technologies, meanwhile, are interacting with the biological world on a daily basis. Engineers, designers, and architects are combining computational design, additive manufacturing, materials engineering, and synthetic biology to pioneer a symbiosis between microorganisms, our bodies, the products we consume, and even the buildings we inhabit.

Challenges and opportunities

Like the revolutions that preceded it, the Fourth Industrial Revolution has the potential to raise global income levels and improve the quality of life for populations around the world. To date, those who have gained the most from it have been consumers able to afford and access the digital world; technology has made possible new products and services that increase the efficiency and pleasure of our personal lives. Ordering a cab, booking a flight, buying a product, making a payment, listening to music, watching a film, or playing a game—any of these can now be done remotely.

In the future, technological innovation will also lead to a supply-side miracle, with long-term gains in efficiency and productivity. Transportation and communication costs will drop, logistics and global supply chains will become more effective, and the cost of trade will diminish, all of which will open new markets and drive economic growth.

At the same time, as the economists Erik Brynjolfsson and Andrew McAfee have pointed out, the revolution could yield greater inequality, particularly in its potential to disrupt labor markets. As automation substitutes for labor across the entire economy, the net displacement of workers by machines might exacerbate the gap between returns to capital and returns to labor. On the other hand, it is also possible that the displacement of workers by technology will, in aggregate, result in a net increase in safe and rewarding jobs.

We cannot foresee at this point which scenario is likely to emerge, and history suggests that the outcome is likely to be some combination of the two. However, I am convinced of one thing—that in the future, talent, more than capital, will represent the critical factor of production. This will give rise to a job market increasingly segregated into “low-skill/low-pay” and “high-skill/high-pay” segments, which in turn will lead to an increase in social tensions.

In addition to being a key economic concern, inequality represents the greatest societal concern associated with the Fourth Industrial Revolution. The largest beneficiaries of innovation tend to be the providers of intellectual and physical capital—the innovators, shareholders, and investors—which explains the rising gap in wealth between those dependent on capital versus labor. Technology is therefore one of the main reasons why incomes have stagnated, or even decreased, for a majority of the population in high-income countries: the demand for highly skilled workers has increased while the demand for workers with less education and lower skills has decreased. The result is a job market with a strong demand at the high and low ends, but a hollowing out of the middle.

This helps explain why so many workers are disillusioned and fearful that their own real incomes and those of their children will continue to stagnate. It also helps explain why middle classes around the world are increasingly experiencing a pervasive sense of dissatisfaction and unfairness. A winner-takes-all economy that offers only limited access to the middle class is a recipe for democratic malaise and dereliction.

Discontent can also be fueled by the pervasiveness of digital technologies and the dynamics of information sharing typified by social media. More than 30 percent of the global population now uses social media platforms to connect, learn, and share information. In an ideal world, these interactions would provide an opportunity for cross-cultural understanding and cohesion. However, they can also create and propagate unrealistic expectations as to what constitutes success for an individual or a group, as well as offer opportunities for extreme ideas and ideologies to spread.

The impact on business

An underlying theme in my conversations with global CEOs and senior business executives is that the acceleration of innovation and the velocity of disruption are hard to comprehend or anticipate and that these drivers constitute a source of constant surprise, even for the best connected and most well informed. Indeed, across all industries, there is clear evidence that the technologies that underpin the Fourth Industrial Revolution are having a major impact on businesses.

On the supply side, many industries are seeing the introduction of new technologies that create entirely new ways of serving existing needs and significantly disrupt existing industry value chains. Disruption is also flowing from agile, innovative competitors who, thanks to access to global digital platforms for research, development, marketing, sales, and distribution, can oust well-established incumbents faster than ever by improving the quality, speed, or price at which value is delivered.

Major shifts on the demand side are also occurring, as growing transparency, consumer engagement, and new patterns of consumer behavior (increasingly built upon access to mobile networks and data) force companies to adapt the way they design, market, and deliver products and services.

A key trend is the development of technology-enabled platforms that combine both demand and supply to disrupt existing industry structures, such as those we see within the “sharing” or “on demand” economy. These technology platforms, rendered easy to use by the smartphone, convene people, assets, and data—thus creating entirely new ways of consuming goods and services in the process. In addition, they lower the barriers for businesses and individuals to create wealth, altering the personal and professional environments of workers. These new platform businesses are rapidly multiplying into many new services, ranging from laundry to shopping, from chores to parking, from massages to travel.

On the whole, there are four main effects that the Fourth Industrial Revolution has on business—on customer expectations, on product enhancement, on collaborative innovation, and on organizational forms. Whether consumers or businesses, customers are increasingly at the epicenter of the economy, which is all about improving how customers are served. Physical products and services, moreover, can now be enhanced with digital capabilities that increase their value. New technologies make assets more durable and resilient, while data and analytics are transforming how they are maintained. A world of customer experiences, data-based services, and asset performance through analytics, meanwhile, requires new forms of collaboration, particularly given the speed at which innovation and disruption are taking place. And the emergence of global platforms and other new business models, finally, means that talent, culture, and organizational forms will have to be rethought.

Overall, the inexorable shift from simple digitization (the Third Industrial Revolution) to innovation based on combinations of technologies (the Fourth Industrial Revolution) is forcing companies to reexamine the way they do business. The bottom line, however, is the same: business leaders and senior executives need to understand their changing environment, challenge the assumptions of their operating teams, and relentlessly and continuously innovate.

The impact on government

As the physical, digital, and biological worlds continue to converge, new technologies and platforms will increasingly enable citizens to engage with governments, voice their opinions, coordinate their efforts, and even circumvent the supervision of public authorities. Simultaneously, governments will gain new technological powers to increase their control over populations, based on pervasive surveillance systems and the ability to control digital infrastructure. On the whole, however, governments will increasingly face pressure to change their current approach to public engagement and policymaking, as their central role of conducting policy diminishes owing to new sources of competition and the redistribution and decentralization of power that new technologies make possible.

Ultimately, the ability of government systems and public authorities to adapt will determine their survival. If they prove capable of embracing a world of disruptive change, subjecting their structures to the levels of transparency and efficiency that will enable them to maintain their competitive edge, they will endure. If they cannot evolve, they will face increasing trouble.

This will be particularly true in the realm of regulation. Current systems of public policy and decision-making evolved alongside the Second Industrial Revolution, when decision-makers had time to study a specific issue and develop the necessary response or appropriate regulatory framework. The whole process was designed to be linear and mechanistic, following a strict “top down” approach.

But such an approach is no longer feasible. Given the Fourth Industrial Revolution’s rapid pace of change and broad impacts, legislators and regulators are being challenged to an unprecedented degree and for the most part are proving unable to cope.

How, then, can they preserve the interest of the consumers and the public at large while continuing to support innovation and technological development? By embracing “agile” governance, just as the private sector has increasingly adopted agile responses to software development and business operations more generally. This means regulators must continuously adapt to a new, fast-changing environment, reinventing themselves so they can truly understand what it is they are regulating. To do so, governments and regulatory agencies will need to collaborate closely with business and civil society.

The Fourth Industrial Revolution will also profoundly impact the nature of national and international security, affecting both the probability and the nature of conflict. The history of warfare and international security is the history of technological innovation, and today is no exception. Modern conflicts involving states are increasingly “hybrid” in nature, combining traditional battlefield techniques with elements previously associated with non-state actors. The distinction between war and peace, combatant and noncombatant, and even violence and nonviolence (think cyberwarfare) is becoming uncomfortably blurry.

As this process takes place and new technologies such as autonomous or biological weapons become easier to use, individuals and small groups will increasingly join states in being capable of causing mass harm. This new vulnerability will lead to new fears. But at the same time, advances in technology will create the potential to reduce the scale or impact of violence, through the development of new modes of protection, for example, or greater precision in targeting.

The impact on people

The Fourth Industrial Revolution, finally, will change not only what we do but also who we are. It will affect our identity and all the issues associated with it: our sense of privacy, our notions of ownership, our consumption patterns, the time we devote to work and leisure, and how we develop our careers, cultivate our skills, meet people, and nurture relationships. It is already changing our health and leading to a “quantified” self, and sooner than we think it may lead to human augmentation. The list is endless because it is bound only by our imagination.

I am a great enthusiast and early adopter of technology, but sometimes I wonder whether the inexorable integration of technology in our lives could diminish some of our quintessential human capacities, such as compassion and cooperation. Our relationship with our smartphones is a case in point. Constant connection may deprive us of one of life’s most important assets: the time to pause, reflect, and engage in meaningful conversation.

One of the greatest individual challenges posed by new information technologies is privacy. We instinctively understand why it is so essential, yet the tracking and sharing of information about us is a crucial part of the new connectivity. Debates about fundamental issues such as the impact on our inner lives of the loss of control over our data will only intensify in the years ahead. Similarly, the revolutions occurring in biotechnology and AI, which are redefining what it means to be human by pushing back the current thresholds of life span, health, cognition, and capabilities, will compel us to redefine our moral and ethical boundaries.

Shaping the future

Neither technology nor the disruption that comes with it is an exogenous force over which humans have no control. All of us are responsible for guiding its evolution, in the decisions we make on a daily basis as citizens, consumers, and investors. We should thus grasp the opportunity and power we have to shape the Fourth Industrial Revolution and direct it toward a future that reflects our common objectives and values.

To do this, however, we must develop a comprehensive and globally shared view of how technology is affecting our lives and reshaping our economic, social, cultural, and human environments. There has never been a time of greater promise, or one of greater potential peril. Today’s decision-makers, however, are too often trapped in traditional, linear thinking, or too absorbed by the multiple crises demanding their attention, to think strategically about the forces of disruption and innovation shaping our future.

In the end, it all comes down to people and values. We need to shape a future that works for all of us by putting people first and empowering them. In its most pessimistic, dehumanized form, the Fourth Industrial Revolution may indeed have the potential to “robotize” humanity and thus to deprive us of our heart and soul. But as a complement to the best parts of human nature—creativity, empathy, stewardship—it can also lift humanity into a new collective and moral consciousness based on a shared sense of destiny. It is incumbent on us all to make sure the latter prevails

Turning the linear circular: the future of the global economy, leveraging Internet of Things

Turning the linear circular: the future of the global economy, leveraging Internet of Things

CE

Jun 5, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.

By Mark Esposito

Curated by Helena M. Herrero Lamuedra

Institutions, both in the private and public sector, can always reap the public relations benefits of doing good, even while still accomplishing their goals. As resources become scarcer, a major way to enhance social performance is through resource conservation, which is being underutilized.

Although the traditional model of the linear economy has worked forever, and will never be fully replaced, it is essentially wasteful. The circular economy, in comparison, which involves resources and capital goods reentering the system for reuse instead of being discarded, saves on production costs, promotes recycling, decreases waste, and enhances social performance. When CE models are combined with IoT, internet connected devices that gather and relay data to central computers, efficiency skyrockets. As a result of finite resource depletion, the future economy is destined to become more circular. The economic shift toward CE will undoubtedly be hastened by the already ubiquitous presence of IoT, its profitability, and the positive public response it yields.

Unlike the linear economy which is a “take, make, dispose” model, the circular economy is an industrial economy that increases resource productivity with the intention of reducing waste and pollution. The main value drivers of CE are (1) extending use cycles lengths of an asset (2) increasing utilization of an asset (3) looping/cascading assets through additional use cycles (4) regeneration of nutrients to the biosphere.

The Internet of Things is the inter-networking of physical devices through electronics and sensors which are used to collect and exchange data. The main value drivers of IoT are the ability to define (1) location (2) condition (3) availability of the assets they monitor. By 2020 there are expected to be at least 20 million IoT connected devices worldwide.

The nexus between CEs and IoTs values drivers greatly enhances CE. If an institutions goals are profitability and conservation, IoT enables those goals with big data and analysis. By automatically and remotely monitoring the efficiency of a resource during harvesting, production, and at the end of its use cycle; all parts of the value chain can become more efficient.

When examining the value chain as a whole, the greatest uses for IoT is at its end. One way in which this is accomplished is through reverse logistics. Once the time comes for a user to discard their asset, IoT can aid in the retrieval of the asset so that it can be recycled into its components. With efficient reverse logistics, goods gain second life, less biological nutrients are extracted from the environment, and the looping/cascading of assets is enabled.

One way to change traditional value chain is the IoT enabled leasing model. Instead of selling an expensive appliance or a vehicle, manufacturers can willingly produce them with the intention of leasing to their customers. By imbedding these assets with IoT manufacturers can monitor the asset’s condition; thereby dynamically repairing the assets at precise times. In theory the quality of the asset will improve, since its in the producers best interest to make it durable rather than disposable and replaceable.

Even today, many sectors are already benefiting from IoT in resource conservation. In the energy sector, Barcelona has reduced its power grid energy consumption by 33%, while GE has begun using “smart” power meters that reduce customers power bills 10–20%. GE has also automated their wind turbines and solar panels; thereby automatically adjusting to the wind and angle of the sun.

In the built environment, cities like Hong Kong have implemented IoT monitoring for preventative maintenance of transportation infrastructure, while Rio de Janeiro monitors traffic patterns and crime at their central operations center. Mexico city has installed fans in their buildings which suck up local smog. In the waste management sector, San Francisco and London have installed solar-powered automated waste bins, that alert local authorities to when they are full; creating ideal routes for trash collection and reducing operational costs by 70%.

Despite the many advantages to this innovation, there are numerous current limitations. Due to difficulty in legislating for new technologies, Governmental regulation lags behind innovation. For example, because Brazil, China, and Russia do not have legal standards to distinguish re-manufactured products from used ones, cross-border reverse supply-chains are blocked. Reverse supply chains are also hurt by current lack of consumer demand , which is caused by low residual value of returned products. IoT technology itself, which collects so much data people’s private lives, generates major privacy concerns.

Questions arise like: who owns this data collected? How reliable are IoT dependent systems? How vulnerable to hackers are these assets? Despite the prevalence of IoT today, with 73% of companies invest in big data analytics, most of that data is merely used to detect and control anomalies and IoT remains vastly underutilized. Take an oil rig for example, it may have 30,000 sensors, but only 1% of them are examined. Underutilization of IoT in 2013 cost businesses an estimated 544 billion alone.

Even with these current barriers, because of the potential profits and increased social performance, the future implementation of an IoT enhanced CE is bright.

Estimates are that the potential profits from institutions adopting CE models could decrease costs by 20%, along with waste. The increase in efficiency combined with the goodwill generated by conservation is a win-win proposition for innovation, even with costs implementation, future monetary profitability will make it a no-brainer.

Keeping Up With New Work Culture

Keeping Up With New Work Culture

May 15, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.

By Scott Scalon, Hunt Scalon Media

Curated by Helena M. Herrero Lamuedra

Companies are facing a radically shifting context for the workforce, the workplace, and the world of work, and these shifts have already changed the rules for nearly every organizational people practice, from learning and management to executive recruiting and the definition of work itself. Every business leader, no matter their function or industry, has experienced some form of radical work transformation, whether it be digitally in the form of social media, for example, demographically, or in countless other ways. Old paradigms are out, new ways of thinking are in — and talent, that one ‘commodity’ we’re all after is caught up in the middle of it all.

Almost 90 percent of HR and business leaders rate building the organization of the future as their highest priority, according to Deloitte’s latest Global Human Capital Trends report, “Rewriting the Rules for the Digital Age.” In the report, Deloitte issues a call-to-action for companies to completely reconsider their organizational structure, talent and HR strategies to keep pace with the disruption.

A Networked World of Work

“Technology is advancing at an unprecedented rate and these innovations have completely transformed the way we live, work and communicate,” said Josh Bersin, principal and founder, Bersin by Deloitte, Deloitte Consulting. “Ultimately, the digital world of work has changed the rules of business. Organizations should shift their entire mind-set and behaviors to ensure they can lead, organize, motivate, manage and engage the 21st century workforce, or risk being left behind.”

With more than 10,000 HR and business leaders in 140 countries weighing in, this massive study reveals that business leaders are turning to new organization models, which highlight the networked nature of today’s world of work. However, as business productivity often fails to keep pace with tecnological progress, Deloitte finds that HR leaders are struggling to keep up, with only 35 percent of them rating their capabilities as ‘good’ or ‘excellent.’

“As technology, artificial intelligence, and robotics transform business models and work, companies should start to rethink their management practices and organizational models,” said Brett Walsh, global human capital leader for Deloitte Global. “The future of work is driving the development of a set of ‘new rules’ that organizations should follow if they want to remain competitive.”

Talent Acquisition: Biggest Issue Facing Companies

As the workforce evolves, organizations are focusing on networks of teams, and recruiting and developing the right people is more consequential than ever. However, while Deloitte finds that cognitive technologies have helped leaders bring talent acquisition into the digital world, only 22 percent of survey respondents describe their companies as ‘excellent’ at building a differentiated employee experience once talent is acquired. In fact, the gap between talent acquisition’s importance and the ability to meet the need increased over last year‘s survey.


How Else the World of Work Is Changing

It is, indeed, a landscape of shifting priorities, and nowhere are we seeing this unfold more than among the group that matters most: job candidates. Five years ago, benefits topped their list of preferences. Today it’s culture and flexibility. Organizations need talented employees to drive strategy and achieve goals, but finding, recruiting and retaining people is becoming more difficult. While the severity of the issue varies among organizations, industries and geographies, it’s clear that this new landscape has created new demands. And organizations are scrambling.

It is critical, according to the report, to take an integrated approach to building the employee experience, with a large part of it centering on ‘careers and learning,’ which rose to second place on HRs’ and business leaders’ priority lists, with 83 percent of those surveyed ranking it as ‘important’ or ‘very important.’ Deloitte finds that as organizations shed legacy systems and dismantle yesterday’s hierarchies, it’s important to place a higher premium on implementing immersive learning experiences to develop leaders who can thrive in today’s digital world and appeal to diverse workforce needs.

The importance of leadership as a driver of the employee experience remains strong, as the percentage of companies with experiential programs for leaders rose nearly 20 percentage points from 47 percent in 2015 to 64 percent this year. Deloitte believes there is still a crucial need, however, for stronger and different types of leaders, particularly as today’s business world demands those who demonstrate more agile and digital capabilities.

Time to Rewrite the Rules

As organizations become more digital, leaders should consider disruptive technologies for every aspect of their human capital needs. Deloitte finds that 56 percent of companies are redesigning their HR programs to leverage digital and mobile tools, and 33 percent are already using some form of artificial intelligence (AI) applications to deliver HR solutions.

“HR and other business leaders tell us that they are being asked to create a digital workplace in order to become an ‘organization of the future,’” said Erica Volini, a principal with Deloitte Consulting LLP, and national managing director of the firm’s U.S. human capital practice. “To rewrite the rules on a broad scale, HR should play a leading role in helping the company redesign the organization by bringing digital technologies to both the workforce and to the HR organization itself.”

Deloitte found that the HR function is in the middle of a wide-ranging identity shift. To position themselves effectively as a key business advisor to the organization, it is important for HR to focus on service delivery efficiency and excellence in talent programs, as well as the entire design of work using a digital lens.

How Jobs Are Being Reinvented

While many jobs are being reinvented through technology and some tasks are being automated, Deloitte’s research shows that the essentially human aspects of work – such as empathy, communication, and problem solving – are becoming more important than ever.

This shift is not only driving an increased focus on reskilling, but also on the importance of people analytics to help organizations gain even greater insights into the capabilities of their workforce on a global scale. However, organizations continue to fall short in this area, with only eight percent reporting they have usable data, and only nine percent believing they have a good understanding of the talent factors that drive performance in this new world of work.

One of the new rules for the digital age is to expand our vision of the workforce; think about jobs in the context of tasks that can be automated (or outsourced) and the new role of human skills; and focus even more heavily on the customer experience, employee experience, and employment value proposition for people.

This challenge requires major cross-functional attention, effort, and collaboration. It also represents one of the biggest opportunities for the HR organization. To be able to rewrite the rules, HR needs to prove it has the insights and capabilities to successfully play outside the lines.

How to ensure future brain technologies will help and not harm society

How to ensure future brain technologies will help and not harm society

May 9, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.

By Written by P. Murali Doraiswamy -Professor, Duke University, Hermann Garden – Organisation for Economic Co-operation and Development, and David Winickoff – Organisation for Economic Co-operation and Development

Curated by Helena M. Herrero Lamuedra

Thomas Edison, one of the great minds of the second industrial revolution, once said that “the chief function of the body is to carry the brain around.” Understanding the human brain – how it works, and how it is afflicted by diseases and disorders – is an important frontier in science and society today.

Advances in neuroscience and technology increasingly impact intellectual wellbeing, education, business, and social norms. Recent findings confirm the plasticity of the brain over the individual’s life. Imaging technologies and brain stimulation technologies are opening up totally new approaches in treating disease and potentially augmenting cognitive capacity. Unravelling the brain’s many secrets will have profound societal implications that require a closer “contract” between science and society.

Convergence across physical science, engineering, biological science, social science and humanities has boosted innovation in brain science and technological innovation. It offers large potential for a systems biology approach to unify heterogeneous data from “omics” tools, imaging technologies such as fMRI, and behavioural science.

Citizen science – the convergence between science and society – already proved successful in EyeWire where people competed to map the 1,000-neuron connectome of the mouse retina. Also, the use of nanoparticles as coating of implanted abiotic devices offers great potential to improve the immunologic acceptance of invasive diagnostics. Brain-inspired neuromorphic engineering aims to develop novel computer systems with brain-like characteristics, including low energy consumption, adequate fault tolerance, self-learning capabilities, and some sort of intelligence. Here, the convergence of nanotechnology with neuroscience could help building neuro-inspired computer chips; brain-machine interfaces and robots with artificial intelligence systems.

Future opportunities for cognitive enhancement for improved attentiveness, memory, decision making, and control through, for example, non-invasive brain stimulation and neural implants have raised, and shall continue to raise, profound ethical, legal, and social questions. What is societally acceptable and desirable, both now and in the future?

At a recent OECD workshop, we identified five possible systemic changes that could help speed up neurotechnology developments to meet pressing health challenges and societal needs.

1. Responsible research

There is growing interest in discussing and unpacking the ethical and societal aspects of brain science as the technologies and applications are developed. Much can be learned from other experiences in disruptive innovation. The international Human Genome Project (1990-2003), for example, was one of the earlier large-scale initiatives in which social scientists worked in parallel with the natural sciences in order to consider the ethical, legal and social issues (ELSI) of their work.

The deliberation of ELSI and Responsible Research and Innovation (RRI) in nanotechnologies is another example of how societies, in some jurisdictions, have approached R&D activities, and the role of the public in shaping, or at least informing, their trajectory. RRI knits together activities that previously seemed sporadic. According to Jack Stilgoe, Senior Lecturer in the Department of Science and Technology Studies, University College London, the aim of responsible innovation is to connect the practice of research and innovation in the present to the futures that it promises.

Frameworks, such as ELSI and RRI should more actively engage patients and patient organisations early in the development cycle, and in a meaningful way. This could be achieved through continuous public platforms and policy discussion instead of traditional one-off public engagement and the deliberation of scientific advances and ELSI through culture and art.

Research funders – public agencies, private investors, foundations, as well as universities themselves – are particularly well positioned to shape trajectories of technology and society. Through their funding power, they have unique capacity to help place scientific work within social, ethical, and regulatory contexts.

It is an opportune time for funders to: 1) strengthen the array of approaches and mechanisms for building a robust and meaningful neurotechnology landscape that meaningfully engages human values and is informed by it; 2) discuss options to foster open and responsible innovation; and 3) better understand the opportunities and challenges for building joint initiatives in research and product development.

2. Anticipatory governance

Society and industry would benefit from earlier, and more inclusive, discussions about the ethical, legal and social implications of how neurotechnologies are being developed and their entry onto the market. For example, the impact of neuromodulatory devices that promise to enhance cognition, alter mood, or improve physical performance on human dignity, privacy, and equitable access could be considered earlier in the research and development process.

3. Open innovation

Given the significant investment risks and high failure rates of clinical trials in central nervous systems disorders, companies could adopt more open innovation approaches in which public and private stakeholders actively collaborate, share assets including intellectual property, and invest together.

4. Avoiding neuro-hype

Popular media is full of colorful brain images used to illustrate stories about neuroscience. Unproven health claims, including those which give rise to so-called ‘neuro-hype’ and ‘neuro-myths’. Misinformation is a strong possibility where scientific work potentially carries major social implications (for example, work on mental illness, competency, intelligence, etc).

It has the potential to result in public mistrust and to undermine the formation of markets. There is a need for evidence-based policies and guidelines to help the responsible development and use of neurotechnology in medical practice and in over-the-counter products. Policymakers and regulators could lead the development of a clear path to translate neurotechnology discoveries into human health advantages that are commercially viable and sustainable.

5. Access and equity

Policymakers should discuss the socio-economic questions raised by neurotechnology. Rising disparities in access to often high-priced medical innovation require tailored solutions for poorer countries. The development of public-private partnerships and simplification of technology help access to innovation in resource-limited countries.

In addition to helping people with neurological and psychiatric disorders, the biggest cause of disability worldwide, neurotechnologies will shape every aspect of society in the future. A roadmap for guiding responsible research and innovation in neurotechnology may be transformative.

Disruption, Regulation, Consolidation… and Collaboration in the Ecosystem!

Disruption, Regulation, Consolidation… and Collaboration in the Ecosystem!

Mar 14, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters

Bracing for seven critical changes as fintech matures

By Miklos Dietz, Vinayak HV, and Gillian Lee

Curated by Helena M. Herrero Lamuedra

For the past decade, fintech companies—technology firms that focus on financial products and services—have moved quickly, forcing incumbents to rethink their core business models and embrace digital innovations. But now, the fintech industry is itself maturing and entering a period of rapid change. Companies wondering how they will fit into this new era must first understand the forces that are pushing the changes.

While the industry will undoubtedly continue to expand as its customer base grows and investor appetite remains unsated, changes are imminent. Indeed, the very concept of what comprises fintech will shift. As the industry evolves, it will play a role well beyond financial products and services, individual companies will vie to become undisputed leaders by size and breadth, and ecosystems will develop that have a tight grip on customer loyalty.

This new fintech era is being shaped by changes in market conditions, new regulations, and shifts in consumer demands and behaviors. As a result, the industry, generally, is becoming more cautious, even as it becomes more diverse across technologies and products. McKinsey research and work with fintechs in many markets suggest seven critical aspects of this new environment that must be understood to thrive in the shifting market.

Expanding scope

The scope of products and services offered by fintechs is expanding rapidly. Where once companies focused on payment applications, lending, and money transfers, the industry’s reach has extended into more than 30 areas. The shift brings fintechs away from a focus on frontline activities to a broad engagement throughout the value chain. The new offerings cut across a wide swath of financial services: retail, wealth management, small- and midsize enterprises (SMEs), corporate and investment banking, and insurance.

Various fintechs using a variety of technologies are active in each of these areas. Some, for example robo-advisory systems that provide automated recommendations with little human input, use tested technologies to meet customer needs, while others pursue more experimental technologies, such as blockchain systems that track and store an expanding series of transactions to help reduce infrastructure costs and improve efficiency.

In addition, fintechs are moving beyond addressing a customer’s financial needs to offering a wider range of services, blurring the industry’s boundaries. For example, Social Finance, known generally as SoFi, began by offering financial products to students and young professionals and has since expanded to provide career coaching and networking services. Holvi Payment Services, a Finnish start-up acquired by Spanish financial group Banco Bilbao Vizcaya Argentaria (BBVA) in 2016, began by offering banking services to SMEs and expanded to provide complementary offerings, such as an online sales platform, bookkeeping services, expense-claims systems, and a cash-flow tracker.

Increasing diversity

The fintech industry is also becoming more diversified, with a wide variety of business models seen across geographies, segments, and technologies. One common model would be a start-up backed by venture-capital funding emerging to address a specific customer need.

For example, the US-based Stripe, one of the largest fintech players, was founded in 2011 to offer an improved online payment system and has attracted more than $300 million from venture-capital funds, including Founders Fund, Khosla Ventures, and Sequoia Capital.1 1. Leena Rao, “Stripe’s new funding makes it a $5 billion company,” Fortune, July 28, 2015, fortune.com. Stripe was one of the first fintechs to dramatically accelerate and improve the process merchants followed to accept payments online. While legacy payments companies needed five to seven days to set up a new merchant, Stripe gave merchants the chance to launch a website and start accepting payments within minutes.2 2. TechCrunch blog, “The story behind payment disruptor Stripe.com and its founder Patrick Collison,” blog entry by Derek Andersen, May 20, 2012, techcrunch.com. Another model would be a large technology company expanding into financial services. China’s Alibaba, one of the best-known examples of this model, started as a major e-commerce site and has moved into financial products, with its Alipay subsidiary boasting more than 800 million registered users in 2016. Another emerging model would be an established financial company creating its own fintech unit. For example, Ping An Insurance (Group) Company of China, China’s largest insurer by assets, launched a peer-to-peer service, Lufax, in 2012, and by 2016 the unit was valued at almost $19 billion.3 3. Gabriel Wildau, “Chinese P2P lender Lufax valued at $19bn in latest funding round,” Financial Times, January 18, 2016, ft.com.

Fintech pioneers, such as PayPal, are also adjusting their business models to encompass a wider range of services. PayPal, launched in the 1990s to provide a payment system for online purchases, then a new phenomena, has since expanded to provide instant lines of credit and mobile applications that locate nearby stores and restaurants that accept payment by PayPal.4 4. Mashable business blog, “PayPal mobile app lets you order ahead at restaurants,” blog entry by Todd Wasserman, September 5, 2013, mashable.com.

Along with diversified models, performance has also become highly variable among fintechs. Certain players have seen share prices fall more than 50 percent. At the other extreme, fintechs that retain the confidence of investors and customers have continued to see strong performance as reflected by share price and business growth. Among the examples, share price for IHS Markit, a financial information and data provider, rose by more than 20 percent over the 12 months ending October 2016. IHS Markit had shown consistently strong financial performance, with, for instance, adjusted third quarter 2016 revenue up 5 percent from a year earlier and its full-year margin forecast at about 36 percent.5 5. Q3 16 Earnings Supplemental Financials, IHS Markit, September 27, 2016, phx.corporate-ir.net.

Improving collaboration

Collaborative partnerships will become increasingly important as fintechs seek scale and traditional financial institutions seek digital expertise. While fintechs have developed applications that create improved customer experiences, many lack skills in customer acquisition and other fields needed to grow quickly. Incumbent banks, on the other hand, already have hard-won capabilities in these areas, but they will have to work harder to create a true digital enterprise.

Examples of such partnerships are already emerging. For example, in 2014 New York–based Moven and Australia’s Westpac announced an agreement to integrate Moven’s mobile financial-management tools with Westpac’s Internet-banking platform in New Zealand. Westpac hoped to use the tools to become the largest bank in the market, while Moven sought to expand into new markets.6 6. Westpac New Zealand REDnews business blog, “Westpac enters exclusive New Zealand partnership with financial services start-up Moven,” August 25, 2014, Westpac.co.nz.

Spain’s BBVA offers an example of an incumbent bank moving aggressively across several areas. BBVA joined data-analytics start-up Destacame to extend credit to the underbanked using Destacame credit scores built from utility-bill-payment histories. It is also working with FutureAdvisor, which focuses on robo-advisory services, to offer low-cost, enhanced financial-advisory services to help customers with portfolio optimization. In addition, BBVA and Dwolla, a payments company, have joined to offer BBVA customers accelerated payment services with low fees.

Impending consolidation

As the industry continues to mature, fintechs will likely enter a period of consolidation, with larger players turning to mergers and acquisitions to satisfy their expansion goals. For example, in 2015 PayPal announced the acquisition of Xoom, an international fund-transfer service, for $890 million. The acquisition was expected to allow PayPal to broaden its services into digital money transfer and management.

In another recent example, in 2015 peer-to-peer lender Prosper Marketplace spent $30 million to acquire BillGuard, later renamed Prosper Daily, an app that allows users to track their spending and credit. The move added personal-financial-management services to Prosper’s core refinancing and credit-rehabilitation offerings and provided a new channel for engaging with customers.10 10. TechCrunch blog, “Prosper Marketplace relaunches its BillGuard app under the Prosper brand,” blog entry by Jonathan Shieber, March 10, 2016, techcrunch.com.

Consolidation, which complements the collaboration trend, may force other changes in the market as well. For instance, banks may have to move quickly to identify acquisition targets before the most attractive are taken by competitors. They will also have to reconcile differences in corporate culture that can limit the upside from such mergers. The trend also offers fintech start-ups an alternative to initial public offerings for exit options.

Normalizing valuations

Valuations of fintechs are also normalizing as investors become more cautious and start favoring companies with proven track records. Examining 44 fintechs with valuations of more than $1 billion, McKinsey found that valuation growth has slowed considerably. Between 2014 and 2015, valuations for these companies grew on average by 77 percent, and then slowed to 9 percent from 2015 to 2016. Companies in the study cut across geographies and segments.

In the United States, where more than half the companies in the study were based, the shift was even more dramatic. While valuations for large US fintechs grew on average by 54 percent from 2014 to 2015, they not only did not grow but dropped by 7 percent from 2015 and 2016.

The shift toward normalized valuations was also noticeable in investment trends. One study looked at the 30 largest fintech investments by venture-capital funds in 2016 through August and found that more than half were later-stage funding deals. The data suggest investors are more interested in companies with proven business models.

Shifting regulations

Not surprising for a new industry, the regulatory regimes affecting fintechs are also evolving swiftly and will significantly influence how the industry develops. In many markets, regulators are playing a more proactive role in overseeing the industry, often encouraging its development, for instance by following a sandbox—or test and learn—approach that allows fintechs to experiment without impacting the entire financial system.

In the United Kingdom, for example, the country’s Financial Conduct Authority has launched Project Innovate, a program that guides technology start-ups through regulatory processes and pushes for speedy responses to applications and questions. Regulators are also increasingly involved in nurturing fintech clusters, organizing large educational and community-building events in many markets.

As regulators increasingly shape the evolution and growth of the fintech industry, it remains unclear how the costs of regulations will impact players, particularly early-stage start-ups. However, while regulators work toward balancing the risks to the financial-services sector, they are also eager to encourage innovation, and many have taken steps toward this goal.

Emerging ecosystems

As digital offerings become more mature and interconnected, vast ecosystems will develop that span multiple industries. In many instances, fintechs will become submerged in these ecosystems, representing, like many others, a component of a much broader digital network.

Ecosystems will likely develop to follow customer needs, rather than conform to traditional industry lines. Leaders in these ecosystems will need strong data-analytic capabilities to develop useful insights from the torrent of customer information available, and they will likely use fintechs and others to develop the system and extract maximum value. While data and analytic capabilities are crucial to leading an ecosystem, companies will also need demonstrated prowess in cybersecurity to credibly safeguard the huge amounts of potentially sensitive client data available in the system.

Already, ecosystem orchestrators are building advantageous data-analytic capabilities. For example, China’s Ping An established a big data–analytics platform in 2013 to improve cross-selling and customer migration. The platform is a critical component in reaching the company’s stated goal of “one customer, one account, multiple services, and multiple products.” Ping An is already benefiting from the use of this platform, with more than half of Ping An’s 109 million core finance customers successfully migrated and also using its online services as of 2016. Across all its platforms, the company has an Internet user base of 298 million people as of June 2016, presenting powerful opportunities for customer acquisition and channel migration.

Other examples of early ecosystems include Commonwealth Bank of Australia (CBA), which is building relationships with a broad customer base across different channels, using technology like MyWealth, a portfolio-management app; DailyIQ, a data-analytic app for SMEs; and Albert, a point-of-sale device for business owners.  Combined, these efforts can provide CBA access to rich data on customer-spending patterns, allowing it to build an ecosystem around these insights and customer relationships.

Outside the financial sector, China’s Tencent, a leader in gaming and social networking, has launched WeChat, a messaging platform that, among other features, can provide instant loans without collateral of up to $30,000. The service combines credit-bureau data from the People’s Bank of China with that gleaned from Tencent’s customer base of 800 million active users to analyze and respond to credit applications. Fintech services have become an integral component in the company’s ecosystem.

The development of ecosystems will differ broadly across markets for various reasons, such as consumer behavior and competitive landscape. In the United States, for example, they could be slower to develop because of market fragmentation, with strong companies already providing compelling solutions backed by advanced technologies. Greater consolidation and scale are likely needed to create conditions suitable for viable ecosystems. In emerging markets, however, digital ecosystems could advance more quickly as companies bypass intermediary technologies and go straight to the most advanced solutions. Platform players that are already deeply entrenched in the lives of consumers, like Tencent, could leverage their solid customer base to form the core needed for an ecosystem’s development.


Fintechs have matured rapidly in recent years, and the industry is entering a new phase of development. With no signs of the industry’s growth abating, its reach is likely to broaden quickly to embrace even newer technologies and offerings, blurring the boundaries now delineating financial services. As the momentum continues, some aspects of fintech are likely to reach into a broad swath of the global economy, much like how digital technologies have become a necessity, rather than an option, for every industry. Understanding the seven features that characterize this new era will allow companies to stake out the most valuable plots in the new landscape.

About the author(s)

Miklos Dietz is a senior partner in McKinsey’s Vancouver office; Vinayak HV is a partner in McKinsey’s Singapore office, where Gillian Lee is a consultant. The authors wish to thank Balazs Kenez, Miklos Radnai, Kausik Rajgopal, and Joydeep Sengupta