Alexandra Berger, Senior Vice President, Marketing & Communications EMEA region, RS Components
There are countless predictions over what will be the next biggest threat to our economy, from risk of international conflict to failure of national governance, cyber attacks and even natural catastrophes.
Using World Economic Forum data, RS Components have mapped out the biggest risks to every country’s economy. Although the global economic outlook is stable right now, risks are always looming on the horizon. Question is, are we implementing the correct precautions to ensure we avoid these economical disasters as much as possible?
You can view the map here. The biggest threat to economies across the world are:
Number of countries at highest risk
Cyber Attacks are the biggest risk to the UK and US economy
Blasted across the news in the last few years, fears of cyber attacks has been on the rise, now becoming the biggest risk to both the UK and the US economy. Cyber attacks install a threat to a country’s ability to carry out secure financial transactions, and can install fear amongst the public extremely quickly, The impact these attacks can have on so many individuals makes this a threat really felt by the public, showing the power of web-based terrorism.
One such attack includes that of UK telecommunications provider TalkTalk who suffered a high profile data breach after falling victim to cyber hackers in 2015. The company lost £60 million and over 100,000 customers as a direct result of the incident.
Last year it was revealed that the cost of cyber crime is now up to 0.8% of global GDP or $600 billion a year. Europe suffers the highest economic impact of cyber crime, which is now estimated at 0.84% of the regional GDP, compared with 0.78% in North America, according to last year’s report on the economic impact of cyber-crime.
As a result of these threats, both the public and private sector are currently investing millions of pounds into installing cyber-security and ensuring companies and individuals feel safe on the web.
Employment is the biggest risk to the economy in the world
Impacting a staggering 31 countries, issues around unemployment and underemployment come out as the biggest risk to most countries in the world.
Unemployment in Europe
Despite a slight improvement this year, France holds one of the highest unemployment rates in Europe, at 8.8%. Unemployment figures have been a challenge for the country for a number of years – in 2017 between 200,000 and 330,000 vacancies were left unfilled.
With an increasing number of companies who are suffering financially from a lack of skilled workers, it is pivotal that the country find solutions to serve both employers and employees and minimise the risks that unemployment poses to their economy. One of the steps France is making towards reducing this threat is the government announcement in March 2018 that by January 2020, each worker (including those who work part-time) will be able to spend 5,000 euros over their careers on training courses of their choice. Will France manage their unemployment rates that pose such a threat to their economy over the next year or two?
Unemployment in Africa
Over two thirds of the countries whose economy is most threatened by employment issues are from Africa, including Zimbabwe, Angola, and Nigeria.
Youths account for 60% of all of those unemployed in Africa and women in particular feel the impact of unemployment as figures rise at higher rates for them than men. It is worth noting that Africa as a continent is considered relatively young, where the median age is about 19 years and is only expected to increase to 25 years in 2046. As a result, young people make up about half of the population of most countries on the continent in the next few decades. With many of these youths desperately wanting opportunities that will ensure a better life, it is important that countries across the continent (and globe) work towards ensuring development schemes are implemented, and more youths are given opportunities in employment.
Other issues that threaten country’s economies include failure of national governance, which impacts the likes of Greece, Ireland and Croatia, and energy prices, being the biggest risk to Australia’s economy.
Natural catastrophes are predicted to be the biggest risk to the economy for countries such as Iceland, Chile and China. China is one of the countries most affected by natural disasters, with 5 of the top ten deadliest natural disasters (based on death toll) having occurred in China. It’s no surprise then, that natural catastrophes are a huge risk to the Chinese economy.
Over the years China has been affected by several types of natural disasters including floods, droughts, ecological disasters, forestry and grassland fires, and many more. Not only do these disasters stand in the way of economic development of the region, but these natural disasters pose serious threats to life, as well as affecting the sustainable development of the country’s economy and society, and threatening the national security and social stability of the country.
Will these countries manage to avoid the biggest threats to their economy?
2020: THE YEAR BLOCKCHAIN COMES OF AGE
– By Rob Coole, VP of Cloud Technologies at IPC
Despite headlines over the years stating that blockchain will change the world, it has not been validated or deployed at such speed and scale like other new technologies such as AI or cloud. Blockchain’s intensive power consumption, reliance on multiple servers and the sheer expense of it, are some of the main reasons cited. In the past, the hype had not met the reality.
But in 2019 blockchain came into its own. With more understanding of what blockchain can do for financial markets and its use points becoming more clear, real-life deployments and advances have started to develop. 2019, for instance, was the year when we saw new blockchain alliances such as Enterprise Ethereum Alliance, increase of blockchain start-ups and the introduction of new infrastructure projects.
Additionally, Gartner’s own Hype Cycle for Blockchain Technologies shows that blockchain is sliding into the “Trough of Disillusionment” – predicting that over time, “permissioned blockchains will integrate with public blockchains, and will take advantage of shared services while supporting the membership, governance and operating model requirements of permissioned blockchain.” Additionally, Gartner predicts that blockchain will be fully scalable by 2023. IPC’s sense of the future of blockchain, particularly in the enterprise space, is just as positive. We are seeing customers truly learning about the practical purposes to deploy, leading to more investment in time and money in blockchain.
Blockchain is suited for complex, collaborative, multi-party, and critical application use-cases and one reason why the hype around blockchain took much longer than some predicted. Adoption in highly regulated, complex markets such as the financial services industry shouldn’t be a surprise. However, we are now seeing a rise in organisations taking a competitive advantage by adopting next-generation blockchain, rearchitected and redesigned to meet the stringent requirements needed for the financial industry.
Next-generation blockchain organisations are leading the way showing the industry how the technology can be used intelligently for the world we live in today. R3, an enterprise software company for example, is working with an ecosystem of over 200 financial institutions, regulators, trade associations, professional services and technology companies to develop Corda, a Blockchain platform designed specifically for businesses to deliver two interoperable and fully compatible distributions of the platform that address issues such as transactional certainty, data privacy, and the scalability limitations.
Both application service providers and subscribers should exploit service providers with products and solutions so that they are not left behind. It is important that partners are complementary to both service providers and subscribers in terms of operational level integration to complement application services. It is critical for adoption success.
We are now seeing blockchain have real value with the integration and support from the hyper-scale platform community such as Microsoft Azure and AWS together with open industry platforms, such as IPC’s Connexus Hub, that creates end-to-end solutions that solve business problems.
We are, like many technology sectors, seeing a move to an API approach. APIs support partners integration and gives institutions the ability to easily access data, provide insights and inspire innovation for the market need.
Service providers, like IPC, can play a critical role here by supporting operationalisation in the systems-oriented context. Such providers are a natural connector embedding connectivity to key market participants. IPC, for example, enables access to all asset classes with over 2,000 sell-side firms, 4,000 buy-side firms and over 75 exchanges in its vast, diverse ecosystem.
Of course, 2020 has and continues to bring new challenges, with the COVID-19 pandemic affecting every aspect of our lives. The World Economic Forum, however, believes technologies such as blockchain “will benefit all countries currently impacted by COVID-19”, as it provides an efficient approach to reduce trade cost on a global scale.
Digital initiatives such as blockchain is non-partisan and open to all which allows users to act quickly at low cost with low barriers for innovation – all valuable factors in getting the global economy back on its feet. So, although blockchain adoption was slow in its early stage, 2020 seems to be the year blockchain comes of age.
AI IN THE FINANCE SECTOR: WHAT’S NEXT?
By Rui Vasconcelos, Product Manager for AI/ML at Canonical – the publisher of Ubuntu
The last few years have seen the promise of general AI acclaimed across multiple industries and this vision has been particularly strong in the finance sector. We’ve currently hit the trough of the hype curve and it will take some time for engineering solutions to deliver on the touted promise. The potential is so great, that hope for general AI will require a longer term and collaborative investment, rather than a quick ROI for a single financial company. As a result, we need to see a continued collective effort from organisations in the direction of making general AI a reality – whether that is in the near future or further in time.
Artificial intelligence within financial organisations has developed from an almost unfathomable vision into tangible deployments, with applications ranging from back-end decision making to front-end customer-facing services. Financial services companies are now placing a much greater focus on AI/ML and are rearchitecting their IT and business operations to take advantage of what this new technology can offer. However, these implementations are what is known as ‘narrow’ AI, which is focused on a single or limited task and operates within a pre-programmed state. Almost all of the AI that surrounds us today is narrow AI. Everyday examples within the financial industry range from Robo-advisors to tailored credit and insurance tools. In distinction, general AI is a progression of this and is often described as an AI solution that can solve a wide range of financial services issues – from natural language understanding to anticipating risk and detecting fraud – with the additional advantage of self-learning to solve any problem without human intervention.
Narrow AI is goal-oriented and solves a particular problem, which is not necessarily bad. We have seen AlphaGo perform a singular task (playing the complex game of Go) and beat the top human expert at it. Organisations focused on being highly competitive in specific use-cases, should concentrate on narrow AI, however it is a short-term win. Those looking at wider-range problems and planning to gain long-term competitive edge need to consider investing in work that will make general AI more accessible, benefitting both the company and society in the long run. Getting there will harness tools and insights that will be very valuable to other financial services applications, even if we do not reach general AI in our lifetime. Where a ‘narrow’ AI would take into consideration historical stock prices to make time-series predictions, general AI would look into all types of accessible data that might influence the mood of investors on that day.
It’s unsurprising that AI development is a resource heavy and challenging process, and general AI development will be even more so. However, we possess an unparalleled capacity today to move it forward, both in terms of computation and human collaboration. The open source community may be able to help tackle some of the hurdles to general AI development by encouraging collaboration as well as pooling knowledge and resources. For instance, open source software allows IT teams in finance companies to benefit from frameworks, data sets, workflows, and software models in the public domain at reduced costs. In addition, the open source community sees projects as a shared responsibility, so provides an extra layer of security by continually monitoring source code for potential flaws and vulnerabilities.
A further advantage of the open source community is that it assists financial businesses to overcome the AI skills gap – one of the most frequently discussed obstacles to AI adoption. In fact, recent research shows that a third of IT teams cite a lack of skilled people and difficulty hiring for required roles as the third most-common challenge. The first hurdle is a lack of institutional support from within the business. In another study, technology’s lack of transparency was also cited as a major hurdle. With collaboration promoted at its very core, an open source approach to AI allows smaller IT teams to benefit from the wider expertise of the much broader community.
Open source will be fundamental to democratising the development of general AI. Financial services organisations who are invested in refining and improving AI for the benefit of their own operations and society will look to open source for future development. However, realising general AI will require long-term investment. Without it, the likelihood of reaching general AI in our lifetime is low. So, it’s up to financial services businesses to start concentrating resources into general AI now to make this future a reality in a short timeframe.
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