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USING ARTIFICIAL INTELLIGENCE TO ACHIEVE CIRCULAR ECONOMY

By Professor Terence Tse, ESCP Business School

 

It is really only a matter of time before the two main trends, artificial intelligence (AI) and circular economy, would come together. A milestone of this convergence was the white paper “Artificial intelligence and the circular economy”: AI as a tool to accelerate the transition, jointly published by The Ellen MacArthur Foundation and Google earlier this year. It has kick-started the discussion on how AI can be used as a tool to help accelerate and scale our transition to a circular economy. This can be achieved by unlocking new opportunities through improving product and material design, enhancing circularity-based business models, and optimising circular infrastructure. The paper draws on the food and consumer electronics industries to illustrate the circular benefits driven by AI. The forecasted value that can emerge from these is encouraging: up to $127 billion and $90 billion a year in 2030, respectively.

 

The pace will be slow

No doubt these are very good news. It also shows how innovative technologies can take circular economy to the next level. Yet, I believe the path leading there will be full of challenges, not least because, contrary to what general media would like to get us to believe, the development of AI is, in reality, really slow.

 

There are several reasons attributable to this sluggish pace

First, there is a general shortage of AI-proficient graduates. Training up AI researchers takes time. Universities are not churning out data scientists fast enough to meet the job market demand. For those who are graduating, they will most likely be snapped up by the technology giants. Indeed, it has been estimated that some 60% of AI talent are in the employment of technology and financial services companies, leading to a ‘brain drain’ in academia, which in turn, slows down the production of qualified graduates. Small circular economy-based companies (as well as AI start-ups) will struggle to have the same hiring power, as they often lack the ability to match the levels of salaries and prestige offered by large organisations.

Another reason why circular economy-aimed companies, large or small, will struggle to deploy AI is that the technology remains a very expensive investment. AI is, at the moment, far from a plug-and-play technology. Arguably, there are off-the-shelf AI applications available in the market. But what this one size fits-all technology solutions can really do is often very limited and their effectiveness low. Inevitably, for AI to work at an acceptable, value-creating level, it is necessary to integrate it into the existing wider IT system. Customising AI applications to be embedded in the system architecture is very complex and hence very costly.

To make matters worse, the market is seemingly inundated with self-proclaimed AI companies. A recent report has suggested that 40 percent of start-ups in Europe that are classified as AI companies do not actually use artificial intelligence technologies in a way that is “material” to their businesses. As someone who researches and works in the business of AI, I can readily observe this phenomenon has already eroded the trust of many companies, making them increasingly cautious when proceeding with investment and deployment of AI.

 

Gradual developments, not quantum jump

For these reasons above, the adoption of AI, and by extension, in the area of circular economy, will be slow. This, however, does not mean there will be no advancement. Instead of “big bang” new business model creations, AI will most likely produce circular advantages through baby steps in operational enhancement gradually. For instance, one of the important elements in achieving circular economy is better asset management. In a recent research project for the European Defence Agency, my colleagues and I have discovered that there is a wide spectrum of operations for ministries of defence to save money and practise circular economy, from refurbishing and repurposing small military equipment items to reduce waste and minimise the use of virgin materials to extending the service years of capital assets. Unquestionably, the same may be applied to civilian activities. For example, combining the power of AI and drones can extend the longevity of major infrastructure such as reactors and bridges.

Advancements in drone technologies have allowed them to be deployed to take pictures at heights that are dangerous for inspectors to reach. The contributions of AI come from its ability to analyse and identify cracks as well as defects on assets that are not always visible to human eyes from captured images. Consequently, problems are detected before the assets become irreparable, thereby lengthening their lifetime.

A seemingly insignificant but potentially huge possibility of waste reduction would be saving on paper use. In the insurance industry, for instance, there is still a huge reliance on actual paper, with the communications between various stakeholders, including the underwriters, brokers and insured, passing on a large number of physical documents. AI techniques, in particular natural language processing, can help speed up the digitalisation of documents as they can go beyond the point of just reading and processing text to recognising and recording signatures and rubber stamp marks. Little by little, it will be possible to lower paper consumption.

 

The future is now

Both AI and circular economy are by themselves breakthrough ideas that are set to change the world dramatically. Combined, it can be a very powerful force of good. But this can only be achieved if we can synthesise them. For AI and circular economy to work together, it is necessary to educate AI developers to be more familiar with the idea of circular economy as well as making circularity practitioners and researchers more AI-savvy. Holding just half of the equation, we risk missing out on most of the intelligence. After all, no matter how smart machines can be, ultimately, it is the human intelligence – or stupidity – that determines the kind of future that we will be having.

 

Extract of “The AI Republic: Building the Nexus Between Humans and Intelligent Automation”

 

Technology

PASSWORDS, BIOMETRICS AND BEYOND

By: Hicham Bouali, Pre-Sales Director EMEA of One Identity, a specialist in identity and access management

 

At any given moment, millions of acts of authentication are performed around the world. Most often, by entering a password. More and more, however, are performed with biometrics or with the help of a unique object, specific to the user. And it’s not only humans who authenticate themselves: machines are doing it on a massive scale, too.

 

How did it all start? And where does it lead us?

In its simplest form, authentication is about proving a user’s identity. And the easiest way to do this is, of course, to agree on a “secret” shared between the user and the machine. This is the principle on which the good old password is based on, and the technique that was implemented by the first multi-user machines installed in universities (the first microcomputers, considered as single-user, obviously did not need this).

But quickly, the password showed its limitations. What happens when it is stolen? How can we be sure it cannot be easily guessed? Why do we do when users choose weak passwords or forget them?

To overcome these limitations, a whole market of dedicated tools has developed, from the password safe (which allows to store passwords on one’s computer in a secure way) to HSMs (electronic boxes that generate highly random passwords), through SSO (connecting to different applications with a single password). Organisations started adopting these tools and developed their own policies around passwords.

As long as this remained limited to the walls of the company, it was still possible to manage a wide range of support solutions. But when the Web opened the floodgates, things became more complex: millions of users were able to access tens of thousands of online services asking for a password. Databases containing several million passwords could be stolen and identities could be usurped. And criminals were very quick at realising that, for the sake of convenience, Internet users sometimes reuse the same identifier, which accentuates the problem.

In short, the Internet has clearly shown that the reign of the password is coming to an end.

The end, really? Not exactly… Because the password still maintains two great advantage: the ease of use and its relative ease of implementation.

However, the Internet ecosystem has started to look for alternatives. With the advent of social networks, a few web giants have notably tried to propose a common authentication standard, which would allow anyone with an account on a social network to authenticate on other websited (the principle of federating identities using standards such as OAuth). It doesn’t quite solve the problem, but it does benefit ease of use.

At the same time, multi-factor authentication, which is still considered one of the most effective means of strengthening passwords, has emerged. By sending the user a very short-lived validation code (OTP : One time Password), by SMS for example, we ensure that even if the password has been stolen, the attacker will not have access to the associated phone and will therefore be unable to complete the authentication process. This worked until we realised that text messages were never designed for this, and the industry now turns almost exclusively to validation codes based on time synchronization with the server, generated on a hardware device such as RSA SecurID or a software device via a smartphone application.

Smartphone manufacturers have also (finally) managed to make biometrics authentication available and usable by anyone by introducing fingerprint and face recognition. This made it possible to equip a large part of the population with a second, truly powerful authentication factor. The password is thus still present, but solidly reinforced by biometric authentication or a single-use validation code. Progress has been made…

But in all this history, the industry has mostly adapted on a case-by-case basis, trying to overcome the weaknesses of the password. What is still missing is a true modern authentication standard that is easy to use, reliable and accessible to all. This standard could well be FIDO (Fast Identity Online), developed since 2012 by a consortium of tech giants including Amazon, Google, Facebook, Paypal, as well as Visa and Wells Fargo.

FIDO’s objective is not to make the password disappear (it is understood that it will always be useful) but to raise the other means of authentication to the same level of simplicity of deployment, in order to allow easy switching from one to the other. FIDO supports the use of passwords as well as biometrics (facial and digital), voice recognition and physical keys. Today, FIDO solutions enable strong authentication on a website or application at the touch of a button on a USB key inserted on the computer, while at the same time authenticating the service itself to protect users against phishing attacks.

Why is it so important to make all other authentication methods as easy to deploy as the password? Because during all this time, things were changing incredibly rapidly: applications were increasingly migrating to the Public Cloud, the perimeter was gradually disappearing, employees were increasingly working from unsecured networks with unsecured devices… So, it no longer makes sense to have to choose a single authentication method. Companies must be able to adapt dynamically to the authentication context (by taking into account the user’s identity in a broader risk analysis) in order to choose the right method at the right time.

The future of authentication is no longer in the methods themselves: the industry has made peace with the good old password and no longer intends to make it disappear at all costs, provided they have the choice! Rather, the future lies in the dynamic management of identities and authentication processes at the enterprise level, in a pragmatic way. Because yes, the password still has its use).

And that’s a new frontier!

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Finance

DIGITAL FINANCE: UNLOCKING NEW CAPITAL IN DISRUPTED MARKETS

Krishnan Raghunathan, Head of Finance & Accounting Services at WNS, explores how a digitally transformed finance department can give enterprises the ability they need to improve cash flow and revenue through better use of data and improved analytics-driven visibility.  

Businesses everywhere are scrambling to recover lost revenues and protect cash flow. But as countries globally grapple with a dreaded second wave of the pandemic, imposing far more stringent localised lockdowns and new restrictions, it is set to be the hardest winter in living memory for many sectors.

The likelihood of winter peaks, so often the saviour of sectors such as travel and hospitality, benefitting businesses is diminishing rapidly. While many have pivoted to a greater or lesser degree, few have been able to offset the impact of falling revenues on cash flow. Even retail, riding an e-commerce boom in many regions, is finding itself in choppy waters, with 17 percent of consumers switching brands due to the economic pressures and changing priorities caused by the pandemic.

As one McKinsey article notes, “With some companies losing up to 75 percent of their revenues in a single quarter, cash isn’t just king – it’s now critical for survival”. Where then do businesses find new sources of cash to sustain their operations through the coming months?

 

Tapping Overlooked Cash Opportunities

Krishnan Raghunathan

For many, the answer could depend on whether they have digitally transformed their finance department. Why? Because many organisations are sitting on unidentified opportunities, funds that could be vital in shoring up businesses over the next few months or plugging the gap between operating costs and government bailouts. Yet those that have been slow to start their digital transformation journey are at a disadvantage;. At the same time, it is possible to identify these hidden seams in an analogue organisation, the process is time-consuming, manually intensive and, without the right digital tools, prone to human error.

Where deploying digital tools helps is by bringing speed, automation and reliable data to the fore. Connecting them with digital finance and accounting systems can give businesses clear insights into how money is being spent, where wastage is occurring, and where opportunities for optimisation exist.

It might be something as simple as automating the accuracy checking, issuing and chasing of invoices and late payments. This could reduce errors and invoice disputes and ultimately lead to faster payments. Accuracy and organisation are also important in billing – better records enable faster billing for work completed, and in turn, should deliver quicker payments.

It could also be around having the ability to review the supply chain and procurement data and identify where a supplier is subsidising a larger customer’s product line through drawn-out payment terms, or where a variety of vendors are on different terms across the business. Using that data and overall knowledge of the business to negotiate better terms that work for both supplier and customer can create new opportunities. It could even be to identify late-paying customers, determine the reason for late payments, and use that intelligence to develop products or financing solutions that continue to support those customers (and improve loyalty) without increasing the burden on the balance sheet.

 

Generating Reliable Insights for Faster Decision-making

To do any of these manually would take months, generating data slowly that would quickly go out of date. But digital finance departments have evidence they can trust to inform business decision-making. That’s because old, manual processes built around Order-to-Cash lack the flexibility and agility that businesses require in today’s markets. The fact is that even before the global pandemic crisis, the pace of digitisation across all sectors was demanding new approaches to finance and book balance.

The opportunities are significant – from cognitive credit and improved forecasting accuracy to enhanced customer analytics. All use similar tools, based on artificial intelligence and quality, trusted data. Cognitive credit can be deployed to quickly make decisions on whether to advance or restrict credit, based on individual company positions and available data. Doing so enables businesses to either capitalise on opportunities (for instance, agreeing credit for a supplier that has run out but is a supportive and integral partner) or avoid risk (in the cases where a business might be in administration).

With more accurate forecasts, businesses can better manage their currency purchases and deposits, selling currency that is not required or buying more where predictions identify an upcoming demand.

It is the same with customer analytics – with a greater understanding of customer needs, businesses can make decisions based on the right mix of the product (and how it meets demand) and supply chain suitability (such as production costs and location in relation to customers).

In many ways, the events of the past year have accelerated the process. In doing so, the problem is the pandemic has also accelerated the speed at which failure to act can lead to obsolescence. Therefore, it is vital that businesses, and more particularly their finance and accounting departments, kick start their digital transformation. This will enable them to deploy the tools and analytics that is needed to capture data, generate insights and drive fast, accurate decision-making to uncover previously untapped sources of cash and reverse revenue degradation.

 

The Importance of Digitally Enabled Finance Teams

Forward-thinking CFOs have already begun the process of digitising their departments, but for those that have been slow to start, now is the time to push forward. It is only through digital tools and analytics that finance leaders can identify both the internal and external opportunities to recover revenue and improve cash flow. Whether that’s releasing working capital, minimising revenue loss and accelerating revenue recovery, reducing total cost of ownership or enhancing customer retention – only digitally enabled finance teams will be in a position to capitalise and, ultimately, bolster business performance during what will be a trading period like no other.

 

 

About the author: Krishnan Raghunathan

Krishnan Raghunathan is the head of Finance & Accounting (F&A) practice and operations at WNS. He also leads the international delivery locations in China, Costa Rica,  Spain, Sri Lanka, Romania, The Philippines, Poland and USA.

Prior to this, Krishnan was Chief Capability Officer for WNS, in that role he headed Horizontal practices across Finance & Accounting, Customer Interaction Services and Research & Analytics, Transformation & Process Excellence, Program Management (Transitions) and Solutions development.

He has more than 27 years of experience across Finance & Accounting, Business Process Management, Sales Solutions and Capability functions including 7 years in Accounting practice.

Before joining WNS in 2013, Krishnan led several challenging roles at Genpact, supporting strategic deals and consultative selling. In addition, Krishnan was also the business leader for a number of industry verticals at Genpact, including hospitality, transportation, logistics, media and professional services

Krishnan is a Chartered Accountant, a Certified Six Sigma Green Belt and a trained Six Sigma Black Belt

 

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