The Europe Smart Finance Technologies Market is expected to witness market growth of 4.2% CAGR during the forecast period (2022-2028).
Automatic factor discovery, or the machine-based identification of the elements that promote outperformance, will become increasingly common in financial services, assisting in the refinement of financial modeling across the industry. Knowledge graphs and graph computing will play a bigger role as a crucial application of AI semantic representation. Their ability to help form relationships and find patterns across complicated financial networks by combining data from a variety of frequently divergent sources will have far-reaching repercussions in the years ahead.
Finally, better privacy protections in analytics will encourage minimum data utilization, or the use of just relevant, essential, and suitably cleansed data in financial model training. These include federated learning, a type of decentralized machine learning that addresses the problem of data centralization by bringing computational capacity to the data rather than the other way around. A new frontier in consumer protection will be driven by advanced encryption, secure multi-party computing, zero-knowledge proofs, and other privacy-aware data analysis techniques.
Germany's universal banking system enables the country's more than 36,000 bank branches to accept deposits and loans from customers as well as deal in securities. In the German economy, there are no reports of a credit shortage. Both domestic and foreign investors can obtain credit at market-determined rates, and a variety of credit instruments are available. In the past, Germany's traditional system of cross-shareholding between banks and industry, as well as a high rate of bank borrowing relative to equity financing, allowed German banks to exert significant influence on the industry.
Germany's banking sector is sophisticated. Private commercial banks, cooperative banks, and public banks form the country's so-called "three-pillar" banking system. It is an organized and well-developed sector.
Private Banks account for around 30% of the market, while publicly owned savings banks with partial ties to state and local governments account for 50% of banking transactions, and cooperative banks account for the remaining 20%.
The Germany market dominated the Europe Smart Finance Technologies Market by Country in 2021, and is expected to continue to be a dominant market till 2028; thereby, achieving a market value of $41.8 Million by 2028. The UK market is anticipated to grow at CAGR of 3.4% during (2022 - 2028). Additionally, The France market is expected to showcase a CAGR of 5% during (2022 - 2028).
Based on Type, the market is segmented into Smart Finance Platforms, Smart Finance Connectivity, Smart Finance Hardware, and Smart Finance Services. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Intel Corporation, Fujitsu Limited, Diebold Nixdorf, Inc., IMS Evolve, Miles Technologies, Inc., Zicom SaaS Pvt. Ltd., Zoho Corporation Pvt. ltd., GRGBanking Equipment Co., Ltd., Dialog Axiata PLC, and Virtusa Corporation.
Automatic factor discovery, or the machine-based identification of the elements that promote outperformance, will become increasingly common in financial services, assisting in the refinement of financial modeling across the industry. Knowledge graphs and graph computing will play a bigger role as a crucial application of AI semantic representation. Their ability to help form relationships and find patterns across complicated financial networks by combining data from a variety of frequently divergent sources will have far-reaching repercussions in the years ahead.
Finally, better privacy protections in analytics will encourage minimum data utilization, or the use of just relevant, essential, and suitably cleansed data in financial model training. These include federated learning, a type of decentralized machine learning that addresses the problem of data centralization by bringing computational capacity to the data rather than the other way around. A new frontier in consumer protection will be driven by advanced encryption, secure multi-party computing, zero-knowledge proofs, and other privacy-aware data analysis techniques.
Germany's universal banking system enables the country's more than 36,000 bank branches to accept deposits and loans from customers as well as deal in securities. In the German economy, there are no reports of a credit shortage. Both domestic and foreign investors can obtain credit at market-determined rates, and a variety of credit instruments are available. In the past, Germany's traditional system of cross-shareholding between banks and industry, as well as a high rate of bank borrowing relative to equity financing, allowed German banks to exert significant influence on the industry.
Germany's banking sector is sophisticated. Private commercial banks, cooperative banks, and public banks form the country's so-called "three-pillar" banking system. It is an organized and well-developed sector.
Private Banks account for around 30% of the market, while publicly owned savings banks with partial ties to state and local governments account for 50% of banking transactions, and cooperative banks account for the remaining 20%.
The Germany market dominated the Europe Smart Finance Technologies Market by Country in 2021, and is expected to continue to be a dominant market till 2028; thereby, achieving a market value of $41.8 Million by 2028. The UK market is anticipated to grow at CAGR of 3.4% during (2022 - 2028). Additionally, The France market is expected to showcase a CAGR of 5% during (2022 - 2028).
Based on Type, the market is segmented into Smart Finance Platforms, Smart Finance Connectivity, Smart Finance Hardware, and Smart Finance Services. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Intel Corporation, Fujitsu Limited, Diebold Nixdorf, Inc., IMS Evolve, Miles Technologies, Inc., Zicom SaaS Pvt. Ltd., Zoho Corporation Pvt. ltd., GRGBanking Equipment Co., Ltd., Dialog Axiata PLC, and Virtusa Corporation.
Scope of the Study
Market Segments Covered in the Report:
By Type
- Smart Finance Platforms
- Smart Finance Connectivity
- Smart Finance Hardware
- Smart Finance Services
By Country
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
Key Market Players
List of Companies Profiled in the Report:
- Intel Corporation
- Fujitsu Limited
- Diebold Nixdorf, Inc.
- IMS Evolve
- Miles Technologies, Inc.
- Zicom SaaS Pvt. Ltd.
- Zoho Corporation Pvt. ltd.
- GRGBanking Equipment Co., Ltd.
- Dialog Axiata PLC
- Virtusa Corporation
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Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. Europe Smart Finance Technologies Market by Type
Chapter 4. Europe Smart Finance Technologies Market by Country
Chapter 5. Company Profiles
Companies Mentioned
- Intel Corporation
- Fujitsu Limited
- Diebold Nixdorf, Inc.
- IMS Evolve
- Miles Technologies, Inc.
- Zicom SaaS Pvt. Ltd.
- Zoho Corporation Pvt. ltd.
- GRGBanking Equipment Co., Ltd.
- Dialog Axiata PLC
- Virtusa Corporation
Methodology
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