Smart Finance - Central Asia | Statista Market Forecast

In Central Asia, the Smart Finance market Market is expected to witness a significant growth in revenue, with projections indicating that it will reach US$270.90m by 2024.
Moreover, the market is anticipated to display a steady annual growth rate of 8.13% from 2024 to 2029, resulting in a market volume of US$400.40m by the end of 2029.
When compared on a global scale, it is noteworthy that United States is expected to generate the highest revenue in this market segment, with an estimated value of US$28.75bn in 2024.
In Central Asia, the adoption of smart finance solutions is rapidly increasing, with Kazakhstan leading the way in implementing digital payment systems.

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

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.

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.

This report presents a comprehensive analysis and additional information on the Technology market, in a PDF format.

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).