Risk Analytics Market: Trends, Opportunities & Forecast to 2031
Risk Analytics Market by Offering (GRC Software, ERM Software, Third-Party Risk Management Tools, Consulting Services, Risk Advisory Services), Risk Type (Operational Risks, Financial Risks, Technology Risks), and Vertical - Global Forecast to 2031
OVERVIEW
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
The risk analytics market is evolving from traditional risk assessment methods toward integrated, data-driven analytics platforms that help organizations identify, quantify, monitor, and mitigate financial and non-financial risks. The market is estimated at USD 35.68 billion in 2026 and is projected to reach USD 54.69 billion by 2031, registering an 8.9% CAGR during the forecast period. The market is driven by increasing adoption of predictive analytics, artificial intelligence, machine learning, quantitative risk modeling, fraud detection, stress testing, and integrated risk management platforms across banking, insurance, capital markets, and other industries. As adoption expands, value is shifting beyond standalone risk assessment tools toward connected platforms that combine financial, transactional, operational, and external data with predictive insights and automated monitoring capabilities. Competitive advantage is increasingly tied to data accuracy, model reliability, real-time processing, regulatory compliance, interoperability, and the ability to convert complex risk data into actionable insights for credit assessment, fraud prevention, regulatory reporting, portfolio monitoring, and enterprise risk management.
Market Size and Forecast:
- 2025 Market Size: USD 31.61 Billion
- 2026 Projected Market Size: USD 35.68 Billion
- 2031 Forecasted Market Size: USD 54.69 Billion
- Growth Rate (2026-2031): CAGR of 8.9%
- Data available from 2025 to 2031
Key Market Trends and Insights
- Largest region: North America
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Growth Drivers: Rising cyber threats, stricter regulations, big data adoption, and demand for real-time risk insights
- Latest Trends: AI-powered predictive modeling, cloud adoption, ESG compliance, and cyber risk management
- Key Opportunities: in fraud detection, predictive analytics, compliance automation, and cyber risk mitigation
- AI Impact: AI is transforming the Risk Analytics Market by enabling predictive risk modeling, automated fraud detection, real-time monitoring, and faster decision-making.
- Leading Companies: IBM (US), Oracle (US), FIS (US), Moody's Analytics (US), Lockton (US), Marsh McLennan (US), SAS Institute (US)
KEY TAKEAWAYS
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BY REGIONNorth America is estimated to account for the largest regional share of 37.01% in 2026.
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BY OFFERINGSoftware is estimated to account for 37.2% of the risk analytics market in 2026.
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BY RISK TYPEThe technology risk segment is expected to register the fastest growth of 11.4% CAGR between 2026 and 2031.
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BY VERTICALThe healthcare & life sciences segment is expected to be the fastest-growing segment across the forecast period.
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BY COMPETITIVE LANDSCAPE – RISK ANALYTICS SOLUTIONS VENDORSMarsh Mclennan, Fusion Risk Management, PWC are notable risk analytics platform vendors, offering capabilities across risk data management, credit risk assessment, predictive modeling, regulatory reporting, fraud detection, and enterprise risk management.
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BY COMPETITIVE LANDSCAPE – RISK ANALYTICS SPECIALIZED SERVICES VENDORSDeloitte, IBM, KPMG, Oracle, FIS, Moody's Analytics are notable specialized solution vendors focused on areas such as credit decisioning, entity and network risk analysis, fraud prevention, financial crime detection, enterprise risk management, and third-party cyber risk assessment.
The risk analytics market is being reshaped by a shift from traditional risk assessment methods toward integrated, data-driven analytics platforms that support continuous risk monitoring and informed decision-making. Growing adoption of predictive analytics, artificial intelligence, machine learning, quantitative risk modeling, stress testing, and automated risk detection is enabling organizations to identify potential exposures, assess their likelihood and impact, and improve risk mitigation strategies. At the same time, AI and machine learning are supporting more advanced risk analytics through automated anomaly detection, predictive modeling, and intelligent workflows, while integrated data platforms combine financial, transactional, operational, and external data. Another important shift is the growing application of risk analytics across credit assessment, fraud detection, regulatory compliance, cybersecurity, insurance risk modeling, and enterprise risk management, where specialized analytical capabilities can improve risk visibility, support timely intervention, and strengthen risk-informed decision-making.
TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS
The trends and disruptions framework highlights a shift in the risk analytics market from conventional risk assessment, manual reporting, and isolated analytical tools toward integrated risk analytics platforms, specialized risk solutions, real-time risk monitoring, and AI-powered decision-support systems. Revenue opportunities are increasingly moving toward solutions that combine financial, transactional, operational, and external data with predictive modeling, scenario analysis, stress testing, and automated risk detection. The commercial impact extends beyond risk measurement, as risk analytics increasingly helps organizations identify emerging exposures, assess potential losses, detect suspicious activities, strengthen regulatory compliance, and improve risk mitigation strategies. Risk analytics is therefore evolving from retrospective reporting toward predictive, continuous, and AI-enabled risk intelligence that supports evidence-based decisions and enables organizations to monitor and refine risk management strategies over time.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
MARKET DYNAMICS
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Rising cyber threats driving demand for advanced risk analytics, increasing regulatory compliance requirements
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Optimization of operations through predictive risk intelligence
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High implementation and integration costs of risk analytics platforms
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Technical complexity and difficulties integrating risk analytics with legacy systems
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Adoption of AI and machine learning for predictive risk assessment and automated decision-making
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Growing demand for industry-specific risk models across banking, insurance, healthcare, and manufacturing
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Model risk, algorithmic bias, and lack of explainability in AI-driven risk models
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Shortage of skilled professionals in risk modeling, quantitative analytics, and risk management
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Driver: Rising Cyber Threats and Increasing Regulatory Compliance Requirements
The increasing frequency and sophistication of cyber threats, including ransomware, data breaches, phishing, and identity theft, are driving demand for advanced risk analytics solutions. Organizations use these solutions to identify vulnerabilities, detect suspicious activities, assess potential financial and operational losses, and monitor emerging threats. In addition, regulatory requirements across financial services and other industries are increasing the need for systematic risk assessment, reporting, and compliance monitoring.
Restraint: High Implementation and Integration Costs of Risk Analytics Platforms
Implementing risk analytics platforms can require significant investment in software, infrastructure, data integration, customization, and employee training. Integrating these platforms with existing legacy systems can further increase costs, making adoption difficult for small and medium-sized organizations with limited budgets.
Opportunity: Adoption of AI and Machine Learning for Predictive Risk Assessment and Automated Decision-Making
The adoption of AI and machine learning creates opportunities for risk analytics providers to develop predictive models that identify potential risks, detect unusual patterns, and support faster decision-making. These technologies help organizations improve fraud detection, assess credit and operational risks, and automate risk monitoring and assessment processes.
Challenge: Model Risk, Algorithmic Bias, and Lack of Explainability in AI-Driven Risk Models
AI-driven risk models may produce inaccurate predictions or biased results when trained on incomplete, outdated, or unrepresentative data. Limited explainability can also make it difficult for organizations to understand or justify model decisions, particularly in regulated industries. Providers must therefore focus on model validation, data quality, transparency, and ongoing monitoring to ensure reliable risk assessments.
RISK ANALYTICS MARKET: COMMERCIAL USE CASES ACROSS INDUSTRIES
| COMPANY | USE CASE DESCRIPTION | BENEFITS |
|---|---|---|
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Askari Bank adopted SAS Governance and Compliance Manager to consolidate risk and compliance activities, automate workflows, improve reporting, and provide greater visibility into enterprise-wide risks. | Improved data consistency and transparency, reduced manual reporting and errors, established clearer accountability through audit trails, and enabled faster risk monitoring through dashboards. |
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Bradesco implemented FICO Platform and developed its SAFER fraud and compliance platform to monitor instant payment transactions, detect suspicious activities in real time, and automate fraud-related decisions. | Reduced fraud-related customer friction by 89%, reduced transaction rejections by 25%, increased real-time account openings by 11%, and supported processing of nearly one billion PIX transactions monthly. |
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HSBC deployed SAS Fraud Management to detect and manage fraudulent credit and debit card transactions in real time across its global network, covering transactions in the US, Europe, and Asia. | Significantly reduced the incidence of fraud across tens of millions of debit and credit card accounts, exceeding the bank’s stated fraud-reduction objectives. |
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AXA Tianping used Verisk’s data and automated risk assessment capabilities to improve insurance underwriting, identify relevant risk factors, and reduce manual intervention in policy assessment. | Achieved a reported 30% increase in sales while maintaining a stable loss ratio, reduced manual underwriting reviews, and enabled faster application processing. |
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET ECOSYSTEM
The risk analytics ecosystem comprises a diverse range of software and service providers supporting financial risk assessment, regulatory compliance, enterprise risk management, and operational risk monitoring. Risk analytics software includes risk calculation engines from Quantifi, ZestyAI, Risk Edge Solutions, and Spin Analytics; risk reporting and analytical tools from Kyvos, Etiometry, Moody’s Analytics, and Quantexa; and dashboard analytics and risk management platforms from Riskonnect, Fusion Risk Management, Onspring, and Z2Data. Governance, risk, and compliance solutions are offered by ServiceNow, Onspring, Diligent, and Archer, while enterprise risk management and third-party risk management capabilities are provided by MetricStream, RiskVille, CubeLogic, ProcessUnity, Interos, OneTrust, and CENTRL. The services ecosystem includes professional services such as consulting, risk assessment and advisory, incident response and crisis management, and training and support, provided by companies including Deloitte, KPMG, PwC, Marsh McLennan, CRISIL, Aon, and SafetyCulture. Managed services cover risk analytics, regulatory compliance, cybersecurity risk management, financial and accounting services, and legal services, with providers including RiskOptics, IBM, FIS, Sprinto, LogicManager, OneTrust, Archer, EY, Milliman, Validus, Diligent, and PwC. Overall, the ecosystem combines specialized software platforms and professional and managed services to support risk identification, measurement, reporting, mitigation, and regulatory compliance across industries.
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET SEGMENTS
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Risk Analytics Market, By Offering
Software is expected to be the fastest-growing segment of the risk analytics market, driven by increasing adoption of AI-powered predictive analytics, automated fraud detection, real-time risk monitoring, and regulatory reporting tools. Organizations are investing in risk analytics software to process large volumes of data, identify emerging risks, improve decision-making, and automate risk assessment. Integration with enterprise systems and demand for scalable, data-driven risk management platforms are further supporting software adoption.
Risk Analytics Market, By Deployment Mode
Cloud deployment is anticipated to hold a significant share of the risk analytics market in 2026, supported by its scalability, flexible computing resources, and ability to integrate data from multiple sources. Cloud-based platforms enable organizations to process large volumes of financial and operational data, deploy analytical models, and monitor risk indicators across distributed business operations. They can also support AI-driven analytics and reduce the need for extensive on-premises infrastructure. However, data security, privacy requirements, regulatory obligations, and integration with legacy systems remain important considerations influencing deployment decisions.
Risk Analytics Market, By Risk Type
Technology risk is expected to be the fastest-growing segment of the risk analytics market, driven by increasing cybersecurity threats, data breaches, cloud adoption, and the growing use of AI and digital technologies. Organizations are adopting technology risk analytics to identify vulnerabilities, monitor cyber threats, assess third-party technology risks, and strengthen IT resilience. Rising regulatory requirements and the need for continuous risk monitoring are further increasing demand for solutions that support technology risk identification, assessment, and mitigation.
Risk Analytics Market, By Vertical
The BFSI sector is expected to account for the largest share of the risk analytics market in 2026, owing to its extensive requirements for credit risk assessment, fraud prevention, market risk monitoring, liquidity management, and regulatory compliance. Banks, insurance companies, and financial service providers process substantial volumes of financial and customer data and use analytics to evaluate exposures, detect suspicious transactions, assess potential losses, and support lending and investment decisions. Regulatory reporting requirements and the need for continuous monitoring of financial risks further contribute to demand for risk analytics solutions across the BFSI sector.
REGION
North America is expected to dominate the risk analytics in 2026, accounting for the largest share of revenues
North America is expected to account for the largest share of the risk analytics market in 2026. The region's market position is supported by the presence of established financial institutions, regulatory requirements, and the adoption of advanced risk management technologies. Organizations across banking, insurance, capital markets, and other industries use risk analytics for credit risk assessment, fraud detection, market risk monitoring, regulatory compliance, and operational risk management. The US contributes significantly to regional demand through the scale of its financial services industry and requirements for risk measurement and reporting. The adoption of artificial intelligence, machine learning, cloud-based analytics, and predictive modeling is expanding the use of risk analytics for identifying emerging exposures and evaluating potential losses. The presence of providers such as Moody’s Analytics, FICO, SAS Institute, IBM, Oracle, and Verisk Analytics also supports the availability of risk data, analytical models, and risk management solutions across North America.
RISK ANALYTICS MARKET: COMPANY EVALUATION MATRIX
Moody’s Analytics is positioned among the Star companies, while Deloitte is positioned among the Emerging Leaders in the Risk Analytics category. Moody’s Analytics’ strong position is supported by its credit risk modeling, economic forecasting, stress testing, financial data, and regulatory compliance capabilities, which help financial institutions and enterprises assess exposures and make informed risk decisions. Its analytical solutions support credit portfolio management, risk measurement, scenario analysis, and regulatory reporting. Deloitte is strengthening its position through risk advisory, enterprise risk management, financial risk consulting, regulatory compliance, cybersecurity risk management, and AI-enabled analytics. Its capabilities help organizations identify emerging risks, evaluate potential losses, improve risk governance, and integrate analytical insights into business decisions. Both companies contribute to the adoption of data-driven risk management, with Moody’s Analytics emphasizing specialized financial risk intelligence and Deloitte providing broader risk consulting and implementation services.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
KEY MARKET PLAYERS
- Moody’s Analytics (U.S.)
- FIS (U.S.)
- Willis Towers Watson Plc (UK)
- SAP (Germany)
- IBM (U.S.)
- Oracle (U.S.)
- ServiceNow (U.S.)
- Deloitte (UK)
- Verisk Analytics (U.S.)
- SAS Institute (U.S.)
- Milliman (U.S.)
- OneTrust (U.S.)
- MetricStream (U.S.)
- Diligent (U.S.)
- Accenture (Ireland)
MARKET SCOPE
| REPORT METRIC | DETAILS |
|---|---|
| Market Size in 2025 (Value) | USD 31.61 Billion |
| Market Forecast in 2026 (Value) | USD 35.68 Billion |
| Market Forecast in 2031 (Value) | USD 54.69 Billion |
| Growth Rate | 8.9% CAGR (2026–20231) |
| Years Considered | 2021–2031 |
| Base Year | 2025 |
| Forecast Period | 2026–2031 |
| Units Considered | Value (USD Million/Billion) |
| Report Coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Segments Covered |
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| Regions Covered | North America, Europe, Asia Pacific, Middle East Africa and Latin America |
WHAT IS IN IT FOR YOU: RISK ANALYTICS MARKET REPORT CONTENT GUIDE
DELIVERED CUSTOMIZATIONS
We have successfully delivered the following deep-dive customizations:
| CLIENT REQUEST | CUSTOMIZATION DELIVERED | VALUE ADDS |
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| Leading Risk Analytics Provider (North America) |
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| Leading Risk Analytics Provider (Europe) |
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RECENT DEVELOPMENTS
- October 2026 : Moody’s Analytics and Allvue Systems launched a credit risk model designed to identify early signs of borrower stress in private credit. The model supports borrower risk assessment and helps private credit investors identify potential credit deterioration.
- September 2026 : Oracle Financial Services expanded its financial crime and compliance management portfolio with the availability of Oracle Nexus Case Flow and Oracle Nexus Reach, incorporating agentic AI capabilities for financial crime investigations. The solutions automate preliminary case investigations, consolidate relevant information, and help financial institutions identify suspicious activity and support more consistent investigative decisions while maintaining human oversight.
- August 2026 : Moody’s integrated its credit ratings, research, and entity intelligence into Google Cloud’s Gemini Enterprise for Financial Services through its Credit Model Context Protocol (MCP) server. The integration enables financial professionals to access Moody’s risk intelligence directly within AI-supported workflows for credit analysis, counterparty assessment, and entity screening.
- June 2026 : ServiceNow and Accenture launched a joint offering comprising managed security services built on the ServiceNow AI Platform and an AI-powered solution to automate migration from legacy systems to ServiceNow. The offering targets enterprise risk modernization by addressing migration complexity and supporting cybersecurity risk management.
- March 2026 : Orange selected IBM OpenPages for a global governance, risk, and compliance (GRC) deployment. The agreement supports centralized risk and compliance management, workflow automation, AI-enabled capabilities, and real-time reporting across Orange’s operations.
Table of Contents
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Methodology
The research study for the risk analytics market involved extensive secondary sources, directories, journals, and paid databases. Primary sources were mainly industry experts from the core and related industries, preferred risk analytics providers, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews with primary respondents, including key industry participants and subject matter experts, were conducted to obtain and verify critical qualitative and quantitative information and assess the market’s prospects.
Secondary Research
In the secondary research process, various sources were referred to identify and collect information for the study. The secondary sources included annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as AI conferences and related magazines. Additionally, the risk analytics spending of various countries was extracted from respective sources. Secondary research was used to obtain key information about the industry’s value chain and supply chain to identify key players by solution, service, market classification, and segmentation according to the offerings of major players and industry trends related to solutions, applications, verticals, and regions, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and risk analytics expertise; related key executives from risk analytics solution vendors, SIs, managed service providers, industry associations; and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from solutions and services, market breakdowns, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, data types, service types, software types, verticals, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users of risk analytics solutions, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of risk analytics, which would impact the overall risk analytics market.
The Breakdown of Primary Research:
Note: Tier 1 companies account for annual revenue of >USD 10 billion; Tier 2 companies’ revenue ranges between USD 1 and 10 billion; and Tier 3 companies’ revenue ranges between USD 500 million–USD 1 billion
Source: MarketsandMarkets Analysis
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Market Size Estimation
Multiple approaches were adopted to estimate and forecast the risk analytics market. The first approach involves estimating the market size by summing companies’ revenue generated by selling solutions and services.
Market Size Estimation Methodology - Top-down approach
In the top-down approach, an exhaustive list of all the vendors offering solutions and services in the risk analytics market was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor's offerings were evaluated based on the breadth of solutions according to software type, service type, technology, data type, and vertical. The aggregate of all the companies’ revenue was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets repository for validation.
Market Size Estimation Methodology - Bottom-up approach
In the bottom-up approach, the adoption rate of risk analytics solutions and services among different end users in key countries, with respect to their regions contributing the most to the market share, was identified. For cross-validation, the adoption of risk analytics solutions among industries, along with different use cases with respect to their regions, was identified and extrapolated. Use cases identified in different regions were given weightage for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the risk analytics market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major risk analytics providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primary interviews, the exact values of the overall risk analytics market size and segments’ size were determined and confirmed using the study.
Risk Analytics Market: Top-Down and Bottom-Up Approach
Data Triangulation
The market was split into several segments and subsegments after arriving at the overall market size using the market size estimation processes as explained above. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
The risk analytics market comprises digital solutions that enable insurers to manage core processes such as policy administration, underwriting, claims management, and customer engagement. These platforms use cloud computing, automation, and data analytics to improve operational efficiency, enhance customer experiences, and support product innovation. They serve insurers, brokers, and third-party service providers, enabling seamless ecosystem integration and regulatory compliance.
Key Stakeholders
- Risk analytics software providers
- Risk analytics service providers
- Third-party administrators
- Business analysts
- Cloud service providers
- Consulting service providers
- Enterprise end-users
- Distributors and value-added resellers (VARs)
- Government agencies
- Independent Software Vendors (ISVs)
- Managed service providers
- Market research and consulting firms
- Support & maintenance service providers
- System Integrators (SIs)/Migration service providers
- Technology providers
Report Objectives
- To define, describe, and forecast the risk analytics market by offering, deployment mode, risk type, and vertical
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
- To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the risk analytics market
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
- To profile the key players and comprehensively analyze their market ranking and core competencies
- To analyze competitive developments, such as partnerships, product launches, and mergers & acquisitions, in the risk analytics market
Available customizations:
Using the provided market data, MarketsandMarkets offers customizations tailored to the company’s specific needs. The following customization options are available for the report.
Product Analysis
- Product comparative analysis, which gives a detailed comparison of innovative products being offered by prominent vendors
Geographic Analysis
- Further breakdown of additional European countries by offering, deployment mode, risk type, and vertical
- Further breakdown of additional Asia Pacific countries by offering, deployment mode, risk type, and vertical
- Further breakdown of additional Middle Eastern & African countries by offering, deployment mode, risk type, and vertical
- Further breakdown of additional Latin American countries by offering, deployment mode, risk type, and vertical
Company Information
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Detailed analysis and profiling of additional market players (up to five)
Key Questions Addressed by the Report
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