Global Financial Forecasting Market - 2024-2031

Global Financial Forecasting Market - 2024-2031


Global Financial Forecasting Market reached US$ 8.7 Billion in 2023 and is expected to reach US$ 21.1 Billion by 2031, growing with a CAGR of 11.7% during the forecast period 2024-2031.

Major players in various sectors, including banking, healthcare and financial services, are growing their businesses globally. Businesses require advanced financial forecasting tools and software as they expand to manage budgets, evaluate financial performance and come to wise strategic decisions. The use of advanced financial forecasting services and software is being driven by a greater focus on digital transformation projects. Businesses are leveraging cloud-based platforms and automation technologies to enhance financial planning processes and gain real-time insights into financial data.

Growing product launches by the major key players help boost global market growth over the forecast period. For instance, on October 17, 2023, NetSuite launched Enterprise Performance Management which helps finance leaders increase efficiency, productivity and profitability. It helps to improve the accuracy and speed of financial processes and gain business insights. It is also beneficial for planning and budgeting and account reconciliation.

Many major key players in North America invest in financial forecasting software and predictive analytics solutions to enhance financial planning and strategic decision support. North America is a dominating region due to the growing product launches of financial forecasting in the region. For instance, on November 03, 2022, IBM launched software to break down data silos and streamline planning and analytics. The company's new product is a suite of business intelligence planning, forecasting and dashboard capabilities that offer users a robust view of data sources across their entire business.

Dynamics

Global Digital Transformation

Companies now have easier access to and integration of financial data from several sources because of digital transformation. Data from external data sources, CRM software, ERP platforms, accounting systems and business intelligence tools are all included in this. Improved data integration and accessibility result in financial predictions that are more comprehensive. Artificial intelligence, machine learning and predictive analytics are a few examples of advanced statistical capabilities that digital transformation has provided to the Financial Forecasting sector. Businesses may now analyze past information, identify patterns, forecast future trends and provide more precise financial estimates due to this technology.

Advanced analytics also support scenario analysis and risk assessment in financial planning. As cloud computing provides scalable and cheap solutions, its adoption has completely transformed the financial forecasting industry. Businesses access their data and forecasting tools from any location at any time using any device with an internet connection by adopting cloud-based financial forecasting software. The lowers the cost of IT infrastructure and improves data security.

Rising Importance of Predictive Analysis

With the use of statistical algorithms, machine learning techniques and predictive models, predictive analysis can more accurately anticipate future trends and results. Financial forecasting software can generate more precise financial forecasts and budget estimates by utilizing predictive analysis, thereby improving planning and decision-making. Through the research of past patterns, market trends, customer behavior and external factors, predictive analysis assists companies in recognizing and reducing financial risks. Predictive analytics-enabled financial forecasting tools evaluate risk variables, foresee possible disruptions and create strategies to mitigate risk, improving risk management procedures and financial stability.

Predictive analysis identifies areas for revenue growth, cost reduction and operational efficiency, which aids in resource allocation optimization. Predictive analytics-enabled financial forecasting software may examine how resources are used, spot inefficiencies and suggest resource allocation plans that increase ROI, boost profitability and support corporate goals. Personalized financial forecasts, behavioral analysis and client segmentation are made possible by predictive analysis. Predictive analytics is a useful tool for businesses to segment their consumer base according to their financial requirements, preferences and behaviors. The makes it possible to create forecasting models that are specifically tailored to the needs of certain client categories, individualized financial solutions and targeted marketing efforts that increase consumer happiness and loyalty.

Data Security Concerns

Controlling sensitive financial data and projecting income using budgets and investment plans are all part of financial forecasting. Confidential financial information was exposed as a result of data breaches endangering the competitiveness of companies and their ability to comply with data privacy laws. For forecasting to be dependable, financial data integrity and accuracy must be guaranteed. The integrity of financial data is compromised by data security risks like data manipulation and tampering, which can result in erroneous projections and financial mismanagement.

Financial forecasting requires compliance with legal standards and data protection laws, including GDPR and CCPA. Data security issues make it more difficult for companies to adhere to laws regulating data privacy and audit trail requirements, which result in penalties and legal ramifications. Cybersecurity risks including malware attacks and insider threats might affect financial forecasting systems and software. Lack of encryption and insufficient access restrictions can leave financial data exposed to theft, unauthorized changes and cyberattacks.

Segment Analysis

The global financial forecasting market is segmented based on solution, deployment, enterprise size, end-user and region.

Growing Consumers' Demand For Financial Forecasting Software

Based on the solution, the financial forecasting market is segmented into software and services.

Financial forecasting software accounted largest market share in the market due to its advanced functionality. Advanced features and functionality, such as budgeting scenario analysis, predictive modeling, what-if analysis, sensitivity analysis and forecasting accuracy, are provided to meet a variety of forecasting demands. With the help of these tools, companies can make data-driven choices, analyze various situations and provide thorough financial predictions. Software for financial forecasting nowadays is available on a variety of platforms, devices and operating systems and it is easy to use and intuitive. Without requiring a high level of technical knowledge, finance professionals and executives analyze financial projections more easily due to user-friendly interfaces, interactive dashboards and customizable reporting tools.

Growing innovative software product launches helps to boost segment growth over the forecast period. For instance, on March 23, 2021, Phocas launched new Budgeting and Forecasting software in the market. The newly launched software enables teams to build budgets in a live data analytics environment. The cloud-based software allows teams to budget and forecast in one place from anywhere.

Geographical Penetration

North America is Dominating the Financial Forecasting Market

North America has advanced technological infrastructure including robust internet connectivity and high-speed data networks. Businesses in various sectors more easily embrace advanced financial forecasting software and digital platforms thanks to these technical improvements. Leading financial services corporations, investment firms and financial institutions are heavily concentrated in North America. Because of the highly developed financial services sector in the region, more sophisticated financial forecasting tools and analytics platforms are being used to assist investment and decision-making processes.

Growing adoption of the financial forecasting models by banks in North America helps to boost regional market growth. For instance, on January 13, 2022, Bank of America launched the CashPro Forecasting tool in the market. It is a financial tool that uses artificial intelligence(AI)and machine learning. The solution is developed in collaboration with a fintech that specializes in applying machine learning to financial forecasting to help solve financial problems for companies.

Competitive Landscape

The major global players in the market include Centage, Sageworks, Anaplan, Inc., Palantir Solutions, Planguru, Palantir Solutions, Axiom Software, Sage Group Plc oracle and IBM.

COVID-19 Impact Analysis

The epidemic highlighted the importance of risk assessment and scenario planning in financial forecasts. To evaluate the effects of various scenarios on financial outcomes, businesses developed more complex forecasting models that contain several scenarios, stress testing and sensitivity analysis. The models were important due to the unprecedented uncertainties they've faced. Changes in consumer behavior across sectors were brought about by COVID-19. Financial forecasting models were required to take into consideration changes in consumer preferences and the need for necessities compared to discretionary spending categories.

The epidemic affected manufacturing and distribution for companies all over the world by disrupting global supply lines. When projecting costs, revenues and supply chain resilience, financial forecasting models are required to account for supply chain interruptions, inventory management difficulties, shortages of raw materials, logistical restrictions and spending patterns. In several countries, COVID-19 set off an economic downturn that resulted in decreased GDP and closures of businesses. Economic indicators, recovery trajectories, stimulus package impacts, interest rate changes, inflation rates and fiscal policy measures impacting macroeconomic circumstances and company performance were all forecasted using financial forecasting models.

Russia-Ukraine War Impact Analysis

Global Financial forecasting market is volatile due to the geopolitical tensions brought on by the conflict between Russia and Ukraine. Financial forecasting models struggle to accurately predict market movements and those influenced by geopolitical events because of that unpredictability. Financial forecasting models struggle to predict asset prices, investment performance and market movements because of growing unpredictability, aversion to risk and mood changes brought on by geopolitical events.

International supply lines might be disrupted by the conflict between Russia and Ukraine that affect the energy and industrial sectors. Businesses operating in impacted countries or industries find it difficult to forecast raw material costs and supply chain stability as a result of supply chain disruptions, which can also have an impact on procurement and inventory levels. Political volatility and regulatory changes must all be considered in financial forecasting models' risk evaluations and mitigation plans. Businesses need to modify their scenario planning, risk management processes and backup plans to handle the geopolitical risks and uncertainties imposed on by the war between Russia and Ukraine.

By Solution
• Software
• Services

By Deployment
• Cloud-Based
• On-Premises

By Enterprise Size
• Small & Medium Enterprises
• Large Enterprises

By End-User
• Banking, Financial Services and Insurance (BFSI)
• E-commerce
• Healthcare
• Manufacturing
• IT and Telecommunications
• Others

By Region
• North America
U.S.
Canada
Mexico
• Europe
Germany
UK
France
Italy
Spain
Rest of Europe
• South America
Brazil
Argentina
Rest of South America
• Asia-Pacific
China
India
Japan
Australia
Rest of Asia-Pacific
• Middle East and Africa

Key Developments
• On January 11, 2024, Nayms launched the first institutional tokenized (Re)insurance marketplace on base, announcing next investment opportunity. The base is a cheap, safe layer-2 Ethereum solution. With this introduction, investors will find it easier to take advantage of yield-generating (re)insurance options that are offered as a tokenized asset class on Nayms' marketplace.
• On September 29, 2022, XA Group, a Dubai based company launched Addenda, Blockchain-based motor insurance platform in the market. The newly launched product will allow insurers to reconcile motor recovery receivables between each other.
• On October 05, 2023, Breach Insurance, a Boston-based insurance company launched Crypto Shield Pro, Institutional-Grade Crypto Insurance and Free Active Wallet Monitoring Service in the market.

Why Purchase the Report?
• To visualize the global financial forecasting market segmentation based on solution, deployment, enterprise size, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of financial forecasting market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global financial forecasting market report would provide approximately 70 tables, 61 figures and 181 Pages.

Target Audience 2024
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies


1. Methodology and Scope
1.1. Research Methodology
1.2. Research Objective and Scope of the Report
2. Definition and Overview
3. Executive Summary
3.1. Snippet by Solution
3.2. Snippet by Deployment
3.3. Snippet by Enterprise Size
3.4. Snippet by End-User
3.5. Snippet by Region
4. Dynamics
4.1. Impacting Factors
4.1.1. Drivers
4.1.1.1. Global Digital Transformation
4.1.1.2. Rising Importance of Predictive Analysis
4.1.2. Restraints
4.1.2.1. Data Security Concerns
4.1.3. Opportunity
4.1.4. Impact Analysis
5. Industry Analysis
5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion
6. COVID-19 Analysis
6.1. Analysis of COVID-19
6.1.1. Scenario Before COVID-19
6.1.2. Scenario During COVID-19
6.1.3. Scenario Post COVID-19
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion
7. By Solution
7.1. Introduction
7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
7.1.2. Market Attractiveness Index, By Solution
7.2. Software*
7.2.1. Introduction
7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Services
8. By Deployment
8.1. Introduction
8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
8.1.2. Market Attractiveness Index, By Deployment
8.2. Cloud-Based*
8.2.1. Introduction
8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. On-Premises
9. By Enterprise Size
9.1. Introduction
9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
9.1.2. Market Attractiveness Index, By Enterprise Size
9.2. Small & Medium Enterprises *
9.2.1. Introduction
9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Large Enterprises
10. By End-User
10.1. Introduction
10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
10.1.2. Market Attractiveness Index, By End-User
10.2. Banking, Financial Services and Insurance (BFSI)*
10.2.1. Introduction
10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
10.3. E-commerce
10.4. Healthcare
10.5. Manufacturing
10.6. IT and Telecommunications
10.7. Others
11. By Region
11.1. Introduction
11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
11.1.2. Market Attractiveness Index, By Region
11.2. North America
11.2.1. Introduction
11.2.2. Key Region-Specific Dynamics
11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
11.2.7.1. U.S.
11.2.7.2. Canada
11.2.7.3. Mexico
11.3. Europe
11.3.1. Introduction
11.3.2. Key Region-Specific Dynamics
11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
11.3.7.1. Germany
11.3.7.2. UK
11.3.7.3. France
11.3.7.4. Italy
11.3.7.5. Spain
11.3.7.6. Rest of Europe
11.4. South America
11.4.1. Introduction
11.4.2. Key Region-Specific Dynamics
11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
11.4.7.1. Brazil
11.4.7.2. Argentina
11.4.7.3. Rest of South America
11.5. Asia-Pacific
11.5.1. Introduction
11.5.2. Key Region-Specific Dynamics
11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
11.5.7.1. China
11.5.7.2. India
11.5.7.3. Japan
11.5.7.4. Australia
11.5.7.5. Rest of Asia-Pacific
11.6. Middle East and Africa
11.6.1. Introduction
11.6.2. Key Region-Specific Dynamics
11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Solution
11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
12. Competitive Landscape
12.1. Competitive Scenario
12.2. Market Positioning/Share Analysis
12.3. Mergers and Acquisitions Analysis
13. Company Profiles
13.1. Centage*
13.1.1. Company Overview
13.1.2. Product Portfolio and Description
13.1.3. Financial Overview
13.1.4. Key Developments
13.2. Sageworks
13.3. Anaplan, Inc.
13.4. Palantir Solutions
13.5. Planguru
13.6. Palantir Solutions
13.7. Axiom Software
13.8. Sage Group Plc
13.9. Oracle
13.10. IBM
LIST NOT EXHAUSTIVE
14. Appendix
14.1. About Us and Services
14.2. Contact Us

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