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Smart Finance - France

France
  • In France, the Smart Finance market Market is estimated to generate a revenue of US$1.65bn in 2024.
  • It is expected to exhibit an annual growth rate (CAGR 2024-2029) of 4.60%, leading to a market volume of US$2.06bn by 2029.
  • When compared globally, United States is projected to generate the highest revenue, amounting to US$28.75bn in 2024.
  • In France, the smart finance market is booming with the rise of innovative fintech companies revolutionizing the way people manage their finances.

Definition:

Smart Finance refers to the application of Internet of Things technologies in the financial industry. It involves the use of connected devices, sensors, and data analytics to transform traditional financial processes and create new business models. IoT applications in financial sector include ATMs, insurance telematics, smart payment systems and asset tracking.

Additional information:

The Internet of Things market compromises of revenue and revenue growth as the key performance indicators. The market consists of pure IoT revenues generated through the sale of hardware (such as sensors, chips, and other hardware), platforms (IoT platforms, security software and other software), connectivity (cellular, LoRa, SigFox and other connectivity) and services (integration &maintenance of equipment & systems). As an example, the pure IoT revenue for a smart security camera is only the component that makes the camera "smart" and connected, not the full product price. Reported market revenues include spending by consumers (B2C), enterprises (B2B) as well as governments (B2G). Revenues are allocated to the country where the money is spent.

Some of the key player in Smart Finance include Intel, SAP and Amazon Web Services (AWS).

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In-Scope

  • Smart insurance devices
  • ATMs
  • Point-of-sale (POS) devices
  • Smart banking devices
  • Asset tracking devices

Out-Of-Scope

  • Smartwatches
Smart Finance: market data & analysis  - Cover

Market Insights report

Smart Finance: market data & analysis

Study Details

    Revenue

    Notes: Data was converted from local currencies using average exchange rates of the respective year.

    Most recent update: Jun 2024

    Source: Statista Market Insights

    Notes: The chart “Comparable Estimates” shows the forecasted development of the selected market from different sources. Please see the additional information for methodology and publication date.

    Most recent update: Jun 2024

    Volume

    Most recent update: Mar 2024

    Source: Statista Market Insights

    Key Players

    Most recent update: Mar 2024

    Source: Statista Company Insights

    Analyst Opinion

    The finance industry has been using an early version of the Internet of Things in the form of automated teller machines (ATMs) for decades, but the applications have since been increasing. Point of sale (POS) have been connected to the internet protocol (IP) for a while, and mobile POS devices are widespread and available virtually everywhere.

    Utilizing IoT technologies for risk management has been on the rise as financial institutions and insurance companies can make more informed decisions based on the data collected via the IoT devices. With the rise of transactions being performed via connected devices, the provided data gives a better insight into how the customers buy and spend their money. The demand is being fueled by the need for faster and real-time data that the devices are constantly collecting, which results in more personalized customer experience.

    With the development of edge computing, analyzing and monitoring large amounts of business operations data makes cost and performance decision-making a faster process. Companies can gain big advantage with this by setting up predictive and prescriptive analytics which have possibility to result in both time and cost savings.

    Global Comparison

    Notes: Data was converted from local currencies using average exchange rates of the respective year.

    Most recent update: Jun 2024

    Source: Statista Market Insights

    Methodology

    Data coverage

    The data encompasses B2B, B2C and B2G revenues. The revenue only refers to the spending share of the Internet of Things components.

    Modeling approach/ Market size:

    The market size is determined through a combination of top-down and bottom-up approaches. We use annual financial reports of the market-leading companies and industry associations, as well as third-party studies and reports to analyze the markets. To estimate the segment size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as consumer spending, internet penetration, 4G coverage, and current and historical developments. This data helps us estimate the market size for each country individually.

    Forecasts:

    In our forecasts, we apply diverse forecasting techniques but primarily exponential smoothing. The selection of forecasting techniques is based on the behavior of the relevant market. The main drivers are the GDP and the level of digitization.

    Additional notes:

    The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.

    Technology

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    Smart Finance: market data & analysis  - BackgroundSmart Finance: market data & analysis  - Cover

    Key Market Indicators

    Notes: Based on data from IMF, World Bank, UN and Eurostat

    Most recent update: Sep 2024

    Source: Statista Market Insights

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    Internet of Things (IoT) - statistics & facts

    In the realm of technology, few concepts have captured imaginations quite like the Internet of Things (IoT). Coined in 1999 by British technologist Kevin Ashton, IoT envisioned a future where a vast network of interconnected objects would collect and analyze data, enabling them to perform tasks autonomously. While the idea seemed more like science fiction at the time, today, IoT is no longer a hypothetical concept but a rapidly unfolding reality. Thanks to the development of communication technologies such as 5G and data analytics using artificial intelligence (AI) and machine learning, IoT has applications varying from smartwatches to city infrastructure (smart cities).
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