Smart Airport Market Research Showing Huge Demand in Future (2020-2027) by Focusing on Top …

Factors driving the smart airport market is the rapid growth in the airport … the increase in number of smartphone consumers, self-service technologies, as well … On the contrary, increase in the conceptualization of smart cities, smart …

Smart airport is a concept to bring advance solutions with a purpose to enhance the capacity and systems such as communication, security, baggage control, checking and other functions with minimal timeframe. Factors driving the smart airport market is the rapid growth in the airport industry with the increase in number of smartphone consumers, self-service technologies, as well as requirement for better real-time incident applications driven by advance IoT solutions. This has put the airport operators and management under pressure to adopt for smart airport solutions in varied applications.

Whereas, growing concern of users and public towards data security is one of factor which might affect the growth of smart airport market. On the contrary, increase in the conceptualization of smart cities, smart parking, and smart agriculture, implementation of smart airport solution is on the pace to grow due to digitization and tech-savvy young population which is forecasted to provide various growth opportunities in the future.

The Smart Airport Market research report includes Market segmentation and overlays shadow upon the leading market players highlighting the favorable competitive landscape and trends prevailing over the years. This study provides information about the sales and revenue during the historic and forecasted period of 2019 to 2027. Understanding the segments helps in identifying the importance of different factors that aid the Smart Airport market growth.

Smart airport is a concept to bring advance solutions with a purpose to enhance the capacity and systems such as communication, security, baggage control, checking and other functions with minimal timeframe. Factors driving the smart airport market is the rapid growth in the airport industry with the increase in number of smartphone consumers, self-service technologies, as well as requirement for better real-time incident applications driven by advance IoT solutions. This has put the airport operators and management under pressure to adopt for smart airport solutions in varied applications.

Whereas, growing concern of users and public towards data security is one of factor which might affect the growth of smart airport market. On the contrary, increase in the conceptualization of smart cities, smart parking, and smart agriculture, implementation of smart airport solution is on the pace to grow due to digitization and tech-savvy young population which is forecasted to provide various growth opportunities in the future.

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Top Players Analysis

  • SITA
  • Huawei Technologies Co., Ltd.
  • Amadeus IT Group SA
  • Thales Group
  • Sabre Corporation
  • T-Systems
  • Indra Sistemas S.A.
  • Rockwell Collins, Inc.
  • Honeywell International Inc.
  • Raytheon Company

Global Smart Airport Market: Regional Analysis

The report offers in-depth assessment of the growth and other aspects of the Smart Airport market in important regions. Key regions covered in the report are North America, Europe, Asia-Pacific and Latin America.

The report has been curated after observing and studying various factors that determine regional growth such as economic, environmental, social, technological, and political status of the particular region. Analysts have studied the data of revenue, production, and manufacturers of each region. This section analyses region-wise revenue and volume for the forecast period of 2019 to 2027. These analyses will help the reader to understand the potential worth of investment in a particular region.

Global Smart Airport Market: Competitive Landscape

This section of the report identifies various key manufacturers of the market. It helps the reader understand the strategies and collaborations that players are focusing on combat competition in the market. The comprehensive report provides a significant microscopic look at the market. The reader can identify the footprints of the manufacturers by knowing about the global revenue of manufacturers, during the forecast period of 2019 to 2027.

Major Key Points of Smart Airport Market

  • Smart Airport Market Overview
  • Smart Airport Market Competition
  • Smart Airport Market, Revenue and Price Trend
  • Smart Airport Market Analysis by Application
  • Company Profiles and Key Figures in Smart Airport Market
  • Market Dynamics
  • Methodology and Data Source

Leading market players and manufacturers are studied to help give a brief idea about them in the report. The challenges faced by them and the reasons they are on that position is explained to help make a well informed decision. Competitive landscape of Brown Sugar market is given presenting detailed insights into the company profiles, developments, merges, acquisitions, economic status and best SWOT analysis.

NOTE: Our team is studying Covid-19 and its impact on various industry verticals and wherever required we will be considering Covid-19 analysis of markets and industries. Cordially get in touch for more details.

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Research Scientist – Theoretical Cryptography (For Quantum Cryptography)

Cambridge Quantum Computing has a vacancy for a Research Scientist to work in its quantum cryptography team. New. Closing date: 16 Dec 2020 …

Cambridge Quantum Computing (CQC), is dedicated to developing and deploying advanced scientific research to lead us into the quantum age. CQC’s mission is to develop the world’s best quantum-based products and to make meaningful impacts on humanity.

Location: Teddington and/or central London (Currently home working within UK – flexible working available).

Cambridge Quantum Computing (CQC) is dedicated to advanced scientific research and currently employs in excess of 100 people and more than 70 scientists. With research teams focused on quantum software, quantum chemistry, quantum natural language processing, quantum machine learning and quantum cryptography, our objective is to develop the best products to lead us into the quantum age.

CQC has developed a range of technologies and recently launched the first self-testing quantum random number generator based on quantum correlations. This is currently implemented on quantum computers and also, in the future, on a single-purpose device. Deployment of this technology in the cryptography space is paving the way for new levels of information security.

About the role

As a researcher in theoretical cryptography you will work in our quantum cryptography team, which combines expertise in different fields such as quantum information and cryptography, mathematics and experimental physics in order to develop quantum-based solutions to problems in cryptography (see [1] for a sample of our work). Our team also works closely with the optics and engineering teams for the real-world implementation and deployment of our products.

In this role you will bring your expertise in computer science and/or classical cryptography to find solutions to the different problems faced both by classical cryptography in a post-quantum world but also the ones faced by quantum cryptography. One such example is randomness extractors [2], which are both essential in quantum cryptography and also need to be made quantum-proof [3]. To thrive in this role you will be self-driven and given the freedom to learn, but you will also give direction and explore your own solutions to all these challenges.

In summary, you will:

  • Research and design new cryptography applications with a quantum advantage, together with their security proofs.
  • Find innovative solutions to the problems faced by classical cryptography in a quantum world and to the challenges faced in quantum cryptography.
  • Develop and implement mathematical schemes and algorithms, e.g. randomness extractors, digital signatures and other cryptographic primitives.

References

[1] https://arxiv.org/abs/2009.06551.

[2] https://cs.haifa.ac.il/~ronen/online_papers/ICALPinvited.pdf.

[3] https://arxiv.org/abs/1510.06743.

Key requirements

  • Theoretical background in computer science and/or cryptography.
  • PhD in computer science, mathematics, physics or related field (or equivalent experience).
  • Familiarity with quantum cryptography, quantum-based and/or post-quantum.
  • Good programming skills (e.g. Python, C/C++ and/or other).
  • Capacity and desire to work in an interdisciplinary team.

Desirable skills

  • Job experience in research, either as a postdoc or with a company, is beneficial but not essential.
  • Track record of publications in relevant fields.
  • Ability to mentor and coach colleagues.

What is in it for you?

We offer an amazing opportunity to join a world leading quantum computing company. You will be working alongside a highly talented team, with world leading names in the quantum computing industry. We offer a highly competitive package, which includes 28 days holiday plus bank holidays, a workplace pension and we have a positive approach to flexible working.

About us

Established in 2014, CQC is a world leading independent quantum computing software company. CQC designs solutions that benefit from quantum computing even in its earliest forms and allows the most effective access to these solutions for the widest variety of corporate and government users.

CQC combines expertise in the product areas of quantum software, specifically a quantum compiler t|ket™, enterprise applications in the area of quantum chemistry, quantum machine learning, and quantum encryption.

The successful applicant will join one of the most exciting companies in the world with the potential to dominate innovation across all aspects of economy and society.

Please note that employment at CQC is subject to successfully passing our pre-employment screening checks.

Apply

QML Scientist

Cambridge Quantum Computing has a vacancy for a QML Scientist to join its Machine Learning and Quantum Algorithms team. New. Closing date: 16 …

Cambridge Quantum Computing (CQC), is dedicated to developing and deploying advanced scientific research to lead us into the quantum age. CQC’s mission is to develop the world’s best quantum-based products and to make meaningful impacts on humanity.

Quantum machine learning (QML) is one of the most interesting applications of quantum computers. For example, parameterized quantum circuits (PQC) can be trained to perform tasks such as classification, regression, and generative modelling (see our recent Topical Review [1] for an introduction).

QML algorithms can be successfully implemented using hybrid quantum-classical systems and are amongst the most promising techniques to show a near-term impact on real-world problems. Firstly, it has been empirically shown that they can cope with noise, a limited number of quantum bits, and shallow circuits. Secondly, it has been theoretically shown that some classes of circuits have remarkable expressive power and share many aspects with classical neural network models. Also, QML borrows many concepts with Deep Learning and other areas of statistical learning and these links have not been thoroughly explored; in this respect, it offers great opportunities to Machine Learning experts interested in quantum computing applications.

The field is thriving with new ideas and open questions such as proving quantum advantage, assessing computational complexity, designing variational circuits, and efficient state preparation, to name a few.

CQC is looking to expand its cutting-edge Machine Learning and Quantum Algorithms team with a full-time research lead. The role entails contributing to world-class scientific research on quantum algorithms for supervized [2] and unsupervized [3] learning. We are also looking to expand our research portfolio in directions that can demonstrate the impact of PQC on computational techniques with business applications. The research will be both theoretical and aimed at prototyping and benchmarking new algorithms on the state-of-the-art of quantum computers.

This position is embedded in a team of world-class academics focusing on hybrid quantum algorithms for near term application, such as combinatorial optimization and Monte Carlo sampling, in partnership with some of the global leaders in the financial, manufacturing, chemical and shipping industries.

Key requirements

  • PhD in quantum physics, computer science.
  • Knowledge of quantum information, quantum algorithms and machine learning.
  • Published research in at least one relevant topic.

Desirable skills

  • Peer-reviewed publications on high impact factor journals.
  • Familiarity with NISQ device and their implementation aspects.

References

[1] Benedetti et al, Parameterized quantum circuits as machine learning models, https://arxiv.org/abs/1906.07682 (2019)

[2] Grant, et al, Hierarchical quantum classifiers, https://www.nature.com/articles/s41534-018-

0116-9 (2018)

[3] Benedetti et al, A generative modeling approach for benchmarking and training shallow quantum circuits, https://www.nature.com/articles/s41534-019-0157-8 (2019)

What is in it for you?

We offer an amazing opportunity to join a world leading quantum computing company. You will be working alongside a highly talented team, with world leading names in the quantum computing industry. We offer a highly competitive package, which includes 28 days holiday plus bank holidays, a workplace pension and we have a positive approach to flexible working.

About us

Established in 2014, CQC is a world leading independent quantum computing software company. CQC designs solutions that benefit from quantum computing even in its earliest forms and allows the most effective access to these solutions for the widest variety of corporate and government users.

CQC combines expertise in the product areas of quantum software, specifically a quantum compiler t|ket™, enterprise applications in the area of quantum chemistry, quantum machine learning, and quantum encryption.

The successful applicant will join one of the most exciting companies in the world with the potential to dominate innovation across all aspects of economy and society.

Please note that employment at CQC is subject to successfully passing our pre-employment screening checks.

Apply

Global Quantum Computing Technologies Market Size and Share 2020 Report by Sales Revenue …

Airbus Group; Alibaba Group Holding Limited; Cambridge Quantum Computing; Nokia Bell Labs; Google Quantum AI Lab; IBM; Intel Corporation …

Industry Research Biz

“Final Report will add the analysis of the impact of COVID-19 on this industry.”

Global “Quantum Computing Technologies Market” Research Report 2020-2026 is a historical overview and in-depth study on the current & future market of the Quantum Computing Technologies industry. The report represents a basic overview of the Quantum Computing Technologies market share, competitor segment with a basic introduction of key vendors, top regions, product types, and end industries. This report gives a historical overview of the Quantum Computing Technologies market trends, growth, revenue, capacity, cost structure, and key driver’s analysis.

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The report mainly studies the Quantum Computing Technologies market size, recent trends and development status, as well as investment opportunities, market dynamics (such as driving factors, restraining factors), and industry news (like mergers, acquisitions, and investments). Technological innovation and advancement will further optimize the performance of the product, making it more widely used in downstream applications. Moreover, Porter’s Five Forces Analysis (potential entrants, suppliers, substitutes, buyers, industry competitors) provides crucial information for knowing the Quantum Computing Technologies market.

Key players in the global Quantum Computing Technologies market covered in Chapter 5:

  • Airbus Group
  • Alibaba Group Holding Limited
  • Cambridge Quantum Computing
  • Nokia Bell Labs
  • Google Quantum AI Lab
  • IBM
  • Intel Corporation
  • Toshiba
  • Microsoft Quantum Architectures
  • TO UNDERSTAND HOW COVID-19 IMPACT IS COVERED IN THIS REPORT

    Global Quantum Computing Technologies Industry 2020 Market Research Report also provides exclusive vital statistics, data, information, trends and competitive landscape details in this niche sector.

    Top Countries Data Covered in Quantum Computing Technologies Market Report are United States, Mexico, Germany, UK, France, Italy, Spain, Russia, China, Japan, India, Southeast Asia, Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Brazil, and Others

    On the basis of types, the Quantum Computing Technologies market from 2015 to 2025 is primarily split into:

  • Software
  • Hardware
  • On the basis of applications, the Quantum Computing Technologies market from 2015 to 2025 covers:

  • Government
  • Business
  • High-Tech
  • BFSI
  • Manufacturing & Logistics
  • Other
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    Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2015-2025) of the following regions are covered:

    • United States
    • Europe (Germany, UK, France, Italy, Spain, Russia, Poland)
    • China
    • Japan
    • India
    • Southeast Asia (Malaysia, Singapore, Philippines, Indonesia, Thailand, Vietnam)
    • Central and South America (Brazil, Mexico, Colombia)
    • Middle East and Africa (Saudi Arabia, United Arab Emirates, Turkey, Egypt, South Africa, Nigeria)
    • Other Regions

    Global Quantum Computing Technologies Market Chapter-wise Analysis:

  • Chapter 1 provides an overview of Quantum Computing Technologies market, containing global revenue, global production, sales, and CAGR. The forecast and analysis of Quantum Computing Technologies market by type, application, and region are also presented in this chapter.
  • Chapter 2 is about the market landscape and major players. It provides competitive situation and market concentration status along with the basic information of these players.
  • Chapter 3 provides a full-scale analysis of major players in Quantum Computing Technologies industry. The basic information, as well as the profiles, applications and specifications of products market performance along with Business Overview are offered.
  • Chapter 4 gives a worldwide view of Quantum Computing Technologies market. It includes production, market share revenue, price, and the growth rate by type.
  • Chapter 5 focuses on the application of Quantum Computing Technologies, by analyzing the consumption and its growth rate of each application.
  • Chapter 6 is about production, consumption, export, and import of Quantum Computing Technologies in each region.
  • Chapter 7 pays attention to the production, revenue, price and gross margin of Quantum Computing Technologies in markets of different regions. The analysis on production, revenue, price and gross margin of the global market is covered in this part.
  • Chapter 8 concentrates on manufacturing analysis, including key raw material analysis, cost structure analysis and process analysis, making up a comprehensive analysis of manufacturing cost.
  • Chapter 9 introduces the industrial chain of Quantum Computing Technologies. Industrial chain analysis, raw material sources and downstream buyers are analyzed in this chapter.
  • Chapter 10 provides clear insights into market dynamics.
  • Chapter 11 prospects the whole Quantum Computing Technologies market, including the global production and revenue forecast, regional forecast. It also foresees the Quantum Computing Technologies market by type and application.
  • Chapter 12 concludes the research findings and refines all the highlights of the study.
  • Chapter 13 introduces the research methodology and sources of research data for your understanding.
  • Get a sample copy of the Quantum Computing Technologies Market Report 2020

    Some of the key questions answered in this report:

    • What will the market growth rate, growth momentum or acceleration market carries during the forecast period?
    • Which are the key factors driving the Quantum Computing Technologies market?
    • What was the size of the emerging Quantum Computing Technologies market by value in 2018?
    • What will be the size of the emerging Quantum Computing Technologies market in 2026?
    • Which region is expected to hold the highest market share in the Quantum Computing Technologies market?
    • What trends, challenges and barriers will impact the development and sizing of the Global Quantum Computing Technologies market?
    • What are sales volume, revenue, and price analysis of top manufacturers of Quantum Computing Technologies market?
    • What are the Quantum Computing Technologies market opportunities and threats faced by the vendors in the global Quantum Computing Technologies Industry?

    With tables and figures helping analyze worldwide Global Quantum Computing Technologies market growth factors, this research provides key statistics on the state of the industry and is a valuable source of guidance and direction for companies and individuals interested in the market.

    Years considered for this report:

    • Historical Years: 2014-2018
    • Base Year: 2019
    • Estimated Year: 2019
    • Quantum Computing Technologies Market Forecast Period: 2019-2026

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    Key Points from TOC:

    1 Quantum Computing Technologies Market Overview

    1.1 Product Overview and Scope of Quantum Computing Technologies

    1.2 Quantum Computing Technologies Segment by Type

    1.2.1 Global Quantum Computing Technologies Production and CAGR (%) Comparison by Type (2014-2026)

    1.2.2 The Market Profile of Type 1

    1.2.3 The Market Profile of Type 2

    1.2.4 The Market Profile of Type 3

    1.3 Global Quantum Computing Technologies Segment by Application

    1.3.1 Quantum Computing Technologies Consumption (Sales) Comparison by Application (2014-2026)

    1.3.2 The Market Profile of Application 1

    1.3.3 The Market Profile of Application 2

    1.3.4 The Market Profile of Application 3

    1.4 Global Quantum Computing Technologies Market by Region (2014-2026)

    1.5 Global Market Size (Value) of Quantum Computing Technologies (2014-2026)

    2 Global Quantum Computing Technologies Market Landscape by Player

    2.1 Global Quantum Computing Technologies Production and Share by Player (2014-2019)

    2.2 Global Quantum Computing Technologies Revenue and Market Share by Player (2014-2019)

    2.3 Global Quantum Computing Technologies Average Price by Player (2014-2019)

    2.4 Quantum Computing Technologies Manufacturing Base Distribution, Sales Area and Product Type by Player

    2.5 Quantum Computing Technologies Market Competitive Situation and Trends

    2.5.1 Quantum Computing Technologies Market Concentration Rate

    2.5.2 Quantum Computing Technologies Market Share of Top 3 and Top 6 Players

    2.5.3 Mergers & Acquisitions, Expansion

    3 Players Profiles

    3.1 Company 1

    3.1.1 Company 1 Basic Information, Manufacturing Base, Sales Area and Competitors

    3.1.2 Quantum Computing Technologies Product Profiles, Application and Specification

    3.1.3 Company 1 Quantum Computing Technologies Market Performance (2014-2019)

    3.1.4 Company 1 Business Overview

    3.2 Company 2

    3.2.1 Company 2 Basic Information, Manufacturing Base, Sales Area and Competitors

    3.2.2 Quantum Computing Technologies Product Profiles, Application and Specification

    3.2.3 Company 2 Quantum Computing Technologies Market Performance (2014-2019)

    3.2.4 Company 2 Business Overview

    3.3 Company 3

    3.3.1 Company 3 Basic Information, Manufacturing Base, Sales Area and Competitors

    3.3.2 Quantum Computing Technologies Product Profiles, Application and Specification

    3.3.3 Company 3 Quantum Computing Technologies Market Performance (2014-2019)

    3.3.4 Company 3 Business Overview

    3.4 Company 4

    3.4.1 Company 4 Basic Information, Manufacturing Base, Sales Area and Competitors

    3.4.2 Quantum Computing Technologies Product Profiles, Application and Specification

    3.4.3 Company 4 Quantum Computing Technologies Market Performance (2014-2019)

    3.4.4 Company 4 Business Overview

    3.5 Company 5

    3.5.1 Company 5 Basic Information, Manufacturing Base, Sales Area and Competitors

    3.5.2 Quantum Computing Technologies Product Profiles, Application and Specification

    3.5.3 Company 5 Quantum Computing Technologies Market Performance (2014-2019)

    3.5.4 Company 5 Business Overview

    …………………………………………………………………..

    4 Global Quantum Computing Technologies Production, Revenue (Value), Price Trend by Type

    5 Global Quantum Computing Technologies Market Analysis by Application

    6 Global Quantum Computing Technologies Production, Consumption, Export, Import by Region (2014-2019)

    7 Global Quantum Computing Technologies Production, Revenue (Value) by Region (2014-2019)

    8 Quantum Computing Technologies Manufacturing Analysis

    8.1 Quantum Computing Technologies Key Raw Materials Analysis

    8.1.1 Key Raw Materials Introduction

    8.1.2 Price Trend of Key Raw Materials

    8.1.3 Key Suppliers of Raw Materials

    8.1.4 Market Concentration Rate of Raw Materials

    8.2 Manufacturing Cost Analysis

    8.2.1 Labor Cost Analysis

    8.2.2 Manufacturing Cost Structure Analysis

    8.3 Manufacturing Process Analysis of Quantum Computing Technologies

    9 Industrial Chain, Sourcing Strategy and Downstream Buyers

    9.1 Quantum Computing Technologies Industrial Chain Analysis

    9.2 Raw Materials Sources of Quantum Computing Technologies Major Players in 2018

    9.3 Downstream Buyers

    10 Market Dynamics

    10.1 Drivers

    10.2 Restraints

    10.3 Opportunities

    10.3.1 Advances in Innovation and Technology for Quantum Computing Technologies

    10.3.2 Increased Demand in Emerging Markets

    10.4 Challenges

    10.4.1 The Performance of Alternative Product Type is Getting Better and Better

    10.4.2 Price Variance Caused by Fluctuations in Raw Material Prices

    10.5 Porter’s Five Forces Analysis

    10.5.1 Threat of New Entrants

    10.5.2 Threat of Substitutes

    10.5.3 Bargaining Power of Suppliers

    10.5.4 Bargaining Power of Buyers

    10.5.5 Intensity of Competitive Rivalry

    11 Global Quantum Computing Technologies Market Forecast (2019-2026)

    12 Research Findings and Conclusion

    13 Appendix

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    The Next Stage in the Financial Revolution: AR and VR Solutions

    Virtual reality (VR) is essentially an immersive and multi-sensory computer-generated experience – allowing users to interact with a simulated …

    Technology-enabled financial solutions have undergone an evolution over the past 130 years. We can consider the late 19th century to have given way to financial globalization. Starting with technologies such as the telegraph, railroads, and steamships that enabled rapid transmission of financial information across the globe.

    Since then, rapid technological developments have enhanced the way financial institutions can deliver their services. Traditionally, the financial sector has depended largely on human input to collect, manipulate, and use data to serve the financial needs of consumers. From investment banking, accounting, and wealth management, to insurance, regulated advice, and retail banking; human involvement has always been necessary.

    Then came Big Data, machine learning, and artificial intelligence (AI). AI has become an integral part of our daily lives. From powering what we see on social media, activating facial recognition, and suggesting the music we want to listen to; it seems fitting that artificial intelligence also contributes to our financial sector.

    Machine learning as a subset of AI is constantly changing the way we make decisions. Unsurprisingly, managing our finances and machine learning is a natural combination. Thanks to machine learning, functions like fraud detection and credit scoring have become automated. Banks have also come to leverage machine learning and predictive analysis to offer customers personalized user experience. Whilst startups are hitting the market in abundance with new solutions to managing our wealth. Consider ARQ’s technology enabling you to connect investments and see how you’re performing with actionable insights generated from vast quantities of data.

    AR and VR in the Financial Sector

    The next step in the financial evolution has welcomed the applications of immersive Augmented and virtual realities. Before we explore the ways in which these technologies have spun the financial sector on its head; it pays to have a good understanding of what these realities are.

    Virtual reality (VR) is essentially an immersive and multi-sensory computer-generated experience – allowing users to interact with a simulated environment. Users can sense and perceive realities around them through a VR headset.

    Augmented reality (AR) is the technology that overlays a digital perception over the actual real world. It’s immersive and dynamic that ultimately enhances the real world with information through a smartphone, smart lenses, and tablets.

    Revolutionary capabilities of AR and VR in Finance

    A report by investment bank Goldman Sachs estimates that augmented and virtual reality is set to become an 80 billion-dollar market by 2025. Financial institutions are experimenting with the implementation of these technologies with a focus on increasing value and propositions by making the user experience more personalized and accessible.

    Simple but effective applications of AR and VR have thus far, included basic apps that use location services to help deliver updates on the nearest ATM and bank branches, for example. More dynamic 3D solutions have promoted investment advice and banking solutions.

    Augmented reality has a track record of exciting and hooking its users. It can be said that the fact 1 in 10 Americans were hooked to the virtual world mapping application – Pokemon Go – serves as a testament to the scope for applying such technology to other areas of everyday life. Like banking, managing wealth, and payments.

    AR and VR can transform traditional banking and financial services into staggering, visual experiences by developing a personalized, face-to-face virtual environment. As such, these reality technologies are transforming the way financial institutions show empathy with customers by making the experience more personal. For example, Fidelity Investments developed a VR agent named ‘Cora’ to interact with users and recommend stocks based on big data and the individual’s portfolio. Users can even interact with Cora by asking questions in a VR chat room.

    Adding Value to the Financial Sector with AR and VR

    Part of revolutionizing the financial sector over the past 130 years has been to add value to the services provided, to enhance efficiencies, and propel the sector forward. As such, the application of AR and VR is expected to deliver on each evolutionary point.

    Virtual trading

    Advanced AR-backed stock trading and investing let users track and visualize the financial markets at depth. Flat images and charts have been replaced with holographic visualization, 3D structures, and intuitive heatmaps. Trading decisions can be made based on real-time data.

    Both AR and VR have assisted in strengthening the concept of ‘workplace anytime anywhere’. Users can now work on laptops and mobiles as well as switch to virtual rooms to collaborate with and seek advice from virtual agents. It helps to strengthen the decision-making process by jointly analyzing financial data.

    Swiss bank Swissquote introduced a VR app, using a VR helmet to create a 360C trading wall for users to monitor markets and trade with all information in front of them.

    Security

    With unprecedented levels of collecting, storing, and managing mass data, many institutions are turning to tech-driven options to boost their core systems. Since biometrics is central to the augmented reality framework, financial service institutions propose more secure and sustainable protection against identity theft and data breach – which may have never been high on their priority list.

    In the advent of behavioral biometrics; iris detection and voice recognition are being integrated with AR to build secure options and maximize security.

    Data visualization

    Advisors, investors, traders, and individuals now have access to simplified breakdowns of mass data and information to make informed decisions. AR and VR have both improved access to such useful information. Fidelity Labs used Oculus Rift to create an immersive 3D environment to analyze data and stock portfolios with accuracy. Within this realm, ‘Stock City’ can be accessed to view a 3D reality for insights and data immersion.

    Retail banking

    Virtual retail banking has been at the forefront of Fintech over the past 10 years, running concurrently with the shift towards a digitized ecosystem. Chatbots and virtual assistants have added an extra element of making the customer experience more personalized. Face-to-face time from anywhere at any time is a key-value addition that AR is facilitating.

    The future of an immersive financial sector

    AR and VR technologies are already being rolled out and incorporated into everyday financial activities. There are some exciting developments in progress. In June 2020, Apple had been granted two new patents for its head-mounted vision correction devices that remove the need to wear prescription glasses while interacting with AR and VR devices. This is a massive technological advancement which raises the question of when, exactly, will Apple enable mixed reality eyewear that is capable of retina scanning and authorize payments.

    AR and VR developments we see in alternative industries like healthcare, education, construction, and beyond; can all contribute to the future development of an immersive financial sector.