Trends Identified
Labour underutilization is more prevalent among women
Apart from the unemployed, a further 140 million people were in the “potential labour force” in 2018, which means that they have to be classified as underutilized labour. This group of people who are looking for a job but are not available to take up employment, or who are available but are not looking for a job, includes far more women (85 million) than men (55 million). The corresponding rate of labour underutilization is consequently much higher for women, at 11.0 per cent, than for men, at 7.1 per cent. In addition, women are much more likely to work part time and a significant proportion say they would prefer more hours of employment.
2019
World Employment and Social Outlook
International Labour Organization (ILO)
Adversarial Machine Learning Becomes Key for Security & Fraud Prevention
Machine learning has had its advantage in effectively delivering rapid prediction of trends and establishing robust risk management and inference. Much investment, time and focus by organisations has been dedicated to programming and training machine learning algorithms to fulfil these functions. However, if these algorithms become compromised, they will be prone to attacks from threats and viruses. The chaotic damage that permeating cyberattacks have inflicted in algorithms can dangerously result in the misclassification/alteration of information within them; in effect an organisation’s entire system’s security can be at stake. Cybercriminals constantly seek to successfully exploit weaknesses of learning algorithms of highly valued organisations. Fraudsters are responding to the enhanced detection capabilities for transaction fraud and account fraud offered by fraud detection and prevention service providers. In some instances, they are also using machine learning algorithms to uncover weaknesses in fraud detection systems, in a type of machine learning chess match. It is here that the choice of FDP vendor becomes important, in terms of how its machine learning solution is implemented. Is a static model used, or does the vendor employ an adversarial model that adapts to changing conditions? Fraudsters will have very little knowledge of the precise algorithms being used to detect fraud. As a result, time, effort and funding must be sourced to identify weaknesses, which may then be applied or replicated across other merchants assumed to be using similar algorithms. Sectors (healthcare, industrial, advertising) where protection of huge amounts and types of sensitive data (e.g. consumer/public data) is a high priority – will be the drivers here. Spend on Fraud Detection & Prevention software in the financial sector, ie for eCommerce transactions including ticketing, money transfer and payments, will reach $10 billion by 2022. These sectors recognise the value of determining and containing susceptibilities (e.g. to detect unauthorised access points, weak security infrastructures, etc.) in machine learning approaches within adversarial circumstances. They will prioritise increasing their understanding of these vulnerabilities in machine learning algorithms. They’ll also engage with machine learning specialists to design and implement effective action steps to address these vulnerabilities. Juniper Research believes, moving forward into 2019 and beyond, that adversarial machine learning will be required by numerous industries to: · Identify weaknesses of machine learning algorithms during the learning and identification process · Enforce the protection and integrity and validity of data in these systems · Action steps in response to specific threats · Assess the potential damage of these threats · Programme algorithms to enhance their resistance to viruses · Eliminate the presence of opaque ‘black boxes’ · Grant adequate time to algorithm developers to invest into ‘breaking’ the efforts of cybercriminals to infect data Related Research: Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2018-2023.
2019
Top Tech trends 2019
Juniper Research
Banking-as-a-Service Economy Emerges
Juniper expects the emergence of banking-as-a-service to be a key driving force in the world of finance in 2019. With PSD2 applicable as of January 2018, we expect 2019 to be the year that products based on the regulation’s open API requirements to have a significant effect on the market. Most particularly, this will enable new types of banking services to be offered by new players, who can handle the cross-platform requirements for banks unfamiliar with the technological requirements. The main opportunity here is for new technology-focused players to offer services across a wide range of new platforms. With compliance established in 2018, 2019 will see banks and technology players look beyond mere compliance and build on the opportunities the directive presents. The newer fintech start-ups stand to be the biggest beneficiaries of this development, as they can provide white-label services to a wide variety of financial institutions wanting to offer more services to customers. In time, this will extend to PaaS and SaaS providers more generally, as financial transactions becomes another form of secure data to transact through the cloud. As a result, we have seen Oracle among one of the early movers in this space; extending their cloud expertise into a new sector. This will also benefit banks, as it gives them more platforms through which to engage their customers. More types of product will give them a larger presence, and thus more ways to make their products more sticky to customers. However, the Open data requirements of PSD2 also means that consumers should benefit from increased competition as dedicated BaaS players emerge to serve customers, in the way that Monzo and other fintech companies have become prominent. Juniper expects that, while this movement has begun in Europe, later in 2019, other banking players will bring out BaaS services to customers. This will not be mandated, but a drive to increase competitive differentiation, and with the PSD2 as a de facto framework, a global BaaS market will form, although banks themselves will remain largely national. In tandem with this, we also expect IoT-based services to make an appearance in 2019. With several companies explicitly targeting this space already, it will become a key competitive benefit for several BaaS players. Related Research: Retail Banking: Digital Transformation & Disruptor Opportunities 2018-2022
2019
Top Tech trends 2019
Juniper Research
AI to Enhance EDGE Computing Power in IoT Systems
Over the past 12 to 18 months, the concept of EDGE computing to power the Internet of Things (IoT) applications, devices and systems surface has become a significant trend in the digital industry. The following factors have led to the a combination of EDGE Computing Power and IoT: · IT and technology providers, given their limitations, have had to decide how much processing power and computing resources to allocate from the cloud layer to the EDGE layer, particularly for applications that are highly Central Processing Unit (CPU) concentrated. · These providers aim to work alongside many sectors, industries, organisations to attain insightful analysis of specific, filtered data and nformation, via the use of machine learning and EDGE computing within IoT. · The collation of these significant amounts and types of intelligent data via smart sensors, actuators, servers, etc, for further analysis by EDGE and Cloud Analytics engines – instills confidence in decision makers to make the right moves. The aviation industry, for example, realises the power of the EDGE element and IoT together. By measuring and monitoring an aircraft’s performance, significant reductions in fuel and operational expenses and customer churn can be achieved. In 2017, SAS and Cisco announced the birth of their IoT Analytics platform, developed to enable analytics on devices at the edge of the network. Many industries see value in capturing and analysing data on the go, or in motion, rather than analyse data that was stored. Meanwhile, Huawei and Google have made efforts, in the last couple of years, to establish specific products to strengthen and enhance their IoT computing EDGE capabilities. In summary, the combination of AI/machine learning and EDGE within IoT systems allows IT and technology providers to: · Increase the running efficiency of their IoT operations via the gathering of intelligence from local data, particularly in locations where cloud connectivity is inconsistent. · As highlighted earlier, deliver real-time, fast predictions for critical IoT applications through machine learning processes that gather and process this data from devices and sensors. · Increase security of all types of sensor collected data via EDGE, with all privacy, security and compliance risks of these data fully eliminated. Juniper forecasts that the total number of connected IoT sensors and devices will exceed 50 billion by 2022, up from an estimated 21 billion in 2018. This growth, equivalent to 140% over the next 4 years, will be driven by EDGE computing services; increasing both deployment scalability and security. Incorporating powerful AI at the EDGE will enable faster processing, and analysis of IoT applications, and deliver improved data filtering, automation and workload distribution. We expect cloud corporates to potentially lead this space strongly, given their experience and background in AI. Related Research: The Internet of Things: Consumer, Industrial & Public Services 2018-2023
2019
Top Tech trends 2019
Juniper Research
RCS Messaging to Contest Chatbots & OTT Business Platforms
RCS has undergone a significant transformation from previous iterations of the messaging technology. Support of RCS will continue to grow over 2019 – amongst both operators and handset vendors. At present, there are over 60 operators supporting the service globally – with more operators expected to announce their support in 2019. 2019 will shape up to be a crucial time for operators wishing to curb the migration of mobile messaging traffic to OTT messaging apps and chatbots. Accessibility and management of the service for brands will be provided by CPaaS vendors, leaving little to no investment needed into infrastructure from operators - just a flat fee to the CPaaS provider. Using RCS for business messaging, or application to person messaging, will provide new revenue streams if the technology is implemented correctly. As a result, this places increased pressure on these OTT messaging apps, their business platforms and in-app chatbots as brands gravitate to the superior capabilities and reach of RCS. As the reach of RCS increases so does the value proposition for its usage in contacting customers, thus increasing adoption of the service further. This will create a virtuous circle, in which the value of RCS only continues to increase. Thus, the timing of implementation is crucial, or operators risk losing A2P messaging traffic to other messaging services in addition to P2P traffic. We anticipate advertising and retail to be the first industries to adopt RCS messaging on a large scale; further encouraging a number of other industries to look into the service. Additionally, we can expect a large amount of focus of MWC 2019 to be on RCS, notably on the revenue potential that the technology will bring operators – and what role the technology will play in the wider CPaaS ecosystem. Related Research: Mobile Messaging: Operator Strategies & Vendor Opportunities 2018-2022
2019
Top Tech trends 2019
Juniper Research
Robotic Process Automation Ramps Up
RPA has, for many years, been used to automate very simple, repetitive business tasks. However, owing to advances in machine learning algorithm modelling, RPA software systems can be trained to automate a wider set of tasks than ever before. This effectively enables a workforce of software agents to manage dynamic data inputs. Previous processes to automate a task involved creating APIs for third parties that can enable the creation of physical actions to execute. In contrast, RPA systems leverage the application’s Graphics User Interface to observe and then mimic the process through robotics. This level of automation can deliver a new degree of efficiency as tasks that were typically time consuming and repetitive, which could thus be automated. Introducing it will also reduce costs and minimise operational errors in business practices. However, its biggest strength lies in its ability to leverage existing systems, rather than requiring a complete overhaul of existing infrastructure. Juniper expects that the public sector will find the greatest benefits from RPA – providing time and cost saving efficiencies that will enable public bodies to offer citizen-centric services. With industries such as manufacturing and financial services investing in RPA solutions, key development focus will be towards more effective machine learning algorithms to increase automation levels. This is in addition to machine learning as a mechanism for defending against new security vulnerabilities introduced by RPA as a result of agents’ ability to access and process across multiple systems. SAP announced their intention to push AI and cloud-based RPA services in late 2018; joining incumbent players including Automation Anywhere, OpenSpan and Blue Prism. Juniper anticipates that in 2019, we will see a number of service providers continuing to invest in AI-based RPA services; releasing solutions that will further drive down cost of adoption. . Related Research: Banking Automation & Roboadvisors: Cost Analyses, Impacts & Opportunities 2018-2022
2019
Top Tech trends 2019
Juniper Research
Voice Assistants Become a Service-Led Market
The key opportunity here is for voice assistant providers and their partners to use the platforms to deliver a range of digital services. This follows the somewhat lacklustre uptake of voice commerce, and will provide a firmer basis for monetisation of a rapidly growing platform; Juniper expects 93 million smart speakers to be in use by the end of 2019, providing a large base for the use of these products. We expect these to be used in 9% of households worldwide by the end of 2019, reaching over 40% in some developed markets. While these devices have been rapidly adopted, they have not become the payment and commerce gateways some had hoped for. Instead, we expect vendors to turn to services as a means of monetising the platforms and further differentiate between voice assistant ecosystems, locking people into hardware. The biggest name in the market so far has been Amazon, and following the recent explosion in Echo devices, we expect the company to further differentiate between Echo and Alexa devices. This means that their own version of the voice assistant will become more appealing; forcing other manufacturers to compete by offering hardware-linked services in other areas, such as premium music subscriptions and other types of service. We expect software providers to benefit the most from this, as speaker hardware vendors will seek out premium deals to drive hardware sales; allowing the software providers to upsell existing users more easily. We also expect Amazon’s hardware sales to increase further, as difference between Echo and Alexa becomes more apparent, driving up sales throughout the year. As a result, Juniper expects more granular speaker-based services to be offered, both by software providers and speaker makers. Gating off content in this way will increase ecosystem lock-in and encourage further spending from smart speaker users. Related Research: Smart Audio Devices: Strategies & Forecasts 2017-2022
2019
Top Tech trends 2019
Juniper Research
Automotive OEMs to Disrupt Established Business Models
Telematics services is fast becoming ubiquitous within all new models of vehicles; owing to both automotive OEM efforts in inclusion and – in some regions – legislation mandating the technology’s inclusion. As the development of autonomous systems progresses, 2019 will be the year in which automotive OEMs begin to explore monetisation models beyond the initial sale of the vehicle. Given that 5G network launches are anticipated experience commercial launches in 2019 – the capabilities of vehicles are likely to increase further, enabling new services such as Vehicle-to-Everything. Juniper anticipates that growth of data from automotive services is anticipated to grow 700% over the next 5 years – driven by the increase in the number of vehicles that have access to connected car services and said emerging new services. However, the challenge of monetising this data remains for automotive OEMs – a challenge that must be considered in 2019 given said impending launches. In turn, we can expect these new business models to include leveraging subscription models for new services. Whilst we can exclude safety features, such as vehicle to vehicle from any subscription – as these will be offered for free – there are a number of consumer-oriented services that can be offered to consumers through the dashboard infotainment screen. Offering subscriptions will help prepare OEMs for the monetisation of autonomous vehicles including lessening the dependence on the vehicle ownership model. Juniper anticipates that the continuing rise of smart mobility services will continue to have an impact on how automotive OEMs plan future services, with the focus shifting to playing a role in smart mobility solutions. Additionally, the rising usage of MaaS (Mobility as a Service) will provide automotive OEMs with an opportunity to leverage their experience in the automotive sector to provide new solutions that require subscriptions for use of public vehicles. Related Research: Consumer Connected Cars: Telematics, InVehicle Apps & Connected Car Commerce 2018-2023
2019
Top Tech trends 2019
Juniper Research
Blockchain Moves into the Food Chain
Blockchain provides a tamper-proof way of tracking the source of foods. The indelible nature of the blockchain record, linked to technologies like RFID for automated tracking of food pallets and items, means that foods can be tracked and linked easily from place to place. The Blockchain record is intended to provide a single electronic point of reference for the whole food supply, from farm to processing to stores. The irrevocable process, tied to automation, can provide huge cost savings for the food tracking process, as well as making the food audit trail both digital and robust. We believe that 2019 will be the year this technology begins its worldwide roll-out; tracking around $150 million worth of food by the end of the year. We have also seen several pilot projects carried out and brought to satisfactory completion by a wide range of platform providers throughout 2018. 2019 will see the first deployment of these technologies at full commercial scale and used for producers. We expect solutions from IBM and Alibaba to be used next year, as well as a ramping up of deployments from IP Australia and the UK’s Food Standards Agency. Related Research: The Future of Blockchain: Key Vertical Opportunities & Deployment Strategies 2018-2030
2019
Top Tech trends 2019
Juniper Research
Loot Boxes to be Banned Across Europe & North America
Found in video games, loot boxes are in-game packs often gifted to players as a result of completing in-game tasks and achievements. Increasingly, these are made available to purchase with real-world currency. As this practice involves a degree of luck, cases are being made that this constitutes a form of gambling and public bodies have requested that it be regulated. Notable action has been taken in the Netherlands and Belgium against the game publisher, EA Sports, regarding their FIFA titles, in which loot boxes are a prevalent feature. The most pressing issue that law makers face is the ability for these services to be accessed by minors. Juniper Research believes that 2019 will be the year in which loot boxes are banned. This will leave games publishers with the task of developing and distributing game updates that remove this functionality with immediate effect. Related Research: The Future of Sports Content: Technologies, Broadcast Strategies & eSports 2018-2023
2019
Top Tech trends 2019
Juniper Research