The global financial analytics market size is expected to reach USD 8.63 billion in 2024 and USD 14.81 billion by 2029, growing at a CAGR of 11.4% during the forecast period.
In an economic environment characterized by volatility, uncertainty, and high risk, financial planning, management, and forecasting solutions provide the speed, agility, and foresight clients need to be competitive. By using them, customers can synthesize information, discover trends, and provide information to improve decision-making across the enterprise. Besides, the increasing emphasis on end-user data-driven financial decisions and the emergence of big data requires solutions that can handle large amounts of data and provide valuable information, driving the demand for these solutions.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2029 |
Base Year |
2023 |
Forecast Period |
2024 to 2029 |
CAGR |
11.4% |
Segments Covered |
By Solution, Application, Industry Vertical, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
Oracle (US), IBM (US), Teradata (US), TIBCO Software (US), SAP (Germany), SAS Institute (US), Alteryx (US), Qlik (US), FICO (US), GoodData (US), Birst (US), Google (US), Information Builders (US), Zoho Corporation (US), Domo (US), and others. |
The major companies operating in the global financial analytics market include Oracle (US), IBM (US), Teradata (US), TIBCO Software (US), SAP (Germany), SAS Institute (US), Alteryx (US), Qlik (US), FICO (US), GoodData (US), Birst (US), Google (US), Information Builders (US), Zoho Corporation (US), Domo (US), and others.
In January 2018, BT announced a partnership with IBM Corporation. With Cloud Connect Direct for IBM, BT customers will receive an IBM cloud connection to access computing, networking, and storage infrastructures, artificial intelligence, blockchain, IoT, data capabilities, and analysis.
In December 2017, Microsoft launched Azure Stack in India in December 2017 to boost cloud computing. It offers all three forms of cloud (private, public, and hybrid) to its customers. Microsoft is focused on nurturing innovation and accelerating the country's digital transformation with Azure Stack, which makes cloud computing more agile than on-premise environments.
In February 2019, Oracle Financial Services Global Business Unit collaborated with Blue Prism, a robotic process automation (RPA) software vendor, to integrate the Financial Crime Management and Compliance Suite Services into Digital Workforce from Blue Prism.
In January 2019, SAP announced the release of its new S / 4 Hana Large Ledger for Financial Products. The solution provides a central hub for managing data between operational and financial systems, streamlining accounting flows, and supporting increased transparency and control. It also helps organizations analyze data for financial steering.
By Solution
Financial Functions Analytics
Financial Market Analytics
By Application
Transaction Monitoring
Customer Management
By Deployment
Cloud-based
On-premises
By Organisation
SMEs
Large enterprise
By Vertical
Education
Healthcare
Media
Government etc.
By Region:
North America
Europe
Asia Pacific
Latin America
Middle East & Africa
North America dominates the overall market, whereas Asia Pacific is recorded as the fastest-growing region during the forecast period.
Frequently Asked Questions
Emerging trends include the integration of advanced visualization tools, the development of real-time analytics capabilities, and the adoption of AI-driven predictive modeling techniques, catering to the evolving needs of businesses worldwide.
Some regions face challenges related to data privacy concerns, lack of skilled professionals, and infrastructure limitations, which may hinder the adoption of financial analytics solutions.
Artificial intelligence and machine learning technologies are enabling organizations to automate routine tasks, detect anomalies, and extract actionable insights from large datasets, driving efficiency and accuracy in financial analysis on a global scale.
Financial institutions globally are utilizing advanced analytics techniques such as fraud detection algorithms, risk modeling, and cybersecurity analytics to identify and mitigate potential threats, safeguarding sensitive financial data and maintaining trust among stakeholders.
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