Risk Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast Segmented By Component (Solution and Service), By Deployment (On-premise and Cloud), By End-User (BFSI, Healthcare, Retail, Manufacturing and Others), By Region, and By Competition, 2020-2030F

Market Overview

The Global Risk Analytics Market, valued at USD 45.32 Billion in 2024, is projected to experience a CAGR of 12.83% to reach USD 93.51 Billion by 2030. Risk analytics involves the measurement, quantification, organization, and prediction of outcomes based on a business's risk exposure, utilizing various tools and technologies to forecast potential incidents and enable proactive risk management. The market's growth is primarily driven by the escalating demand for cohesive platforms to evaluate and mitigate diverse risks, including an increasing prevalence of cybersecurity threats and the complexities introduced by stringent global regulatory compliance requirements. For instance, according to the Institute of Internal Auditors (IIA) 2023 North American Pulse of Internal Audit survey, 78% of over 550 internal audit leaders identified cybersecurity as a primary risk driver for their organizations. Further expansion is supported by the expanding adoption of artificial intelligence and machine learning for enhanced predictive capabilities.

A significant challenge impeding market expansion stems from issues related to model risk and bias, particularly concerning AI and machine learning-driven predictive models, which can produce inaccurate or skewed outcomes. Organizations also face substantial hurdles in integrating new technologies and navigating complex regulatory environments, requiring careful management to ensure effective implementation and adherence to compliance standards.

Key Market Drivers

The escalating frequency of cyber threats and sophisticated fraud schemes is a primary driver for the Global Risk Analytics Market. Enterprises across all sectors face an expanding attack surface and evolving tactics from malicious actors, necessitating advanced analytical capabilities to identify vulnerabilities, predict intrusions, and respond promptly to incidents. This pervasive digital risk landscape underscores the critical need for comprehensive risk analytics solutions that process vast data to discern anomalous patterns indicative of cyberattacks or fraudulent activities. According to IBM, in its "Cost of a Data Breach Report 2023" published in July 2023, the average cost of a data breach reached an all-time high of $4.45 million, emphasizing the substantial financial implications of inadequate cybersecurity defenses. The imperative to safeguard sensitive data and maintain operational integrity fuels the demand for predictive risk analytics frameworks.

Stringent regulatory compliance and governance requirements concurrently significantly influence the Global Risk Analytics Market's expansion. Organizations, particularly within the financial services sector, operate under a continuously evolving patchwork of regulations, including anti-money laundering AML, know your customer KYC, and data privacy mandates. Adhering to these complex rules necessitates sophisticated analytical tools to ensure transparency, manage operational risks, and avoid severe penalties. For example, according to the U. S. Securities and Exchange Commission, in a press release dated November 14, 2023, it obtained judgments and orders for $4.949 billion in disgorgement and penalties during fiscal year 2023, demonstrating the financial consequences of non-compliance. The broader adoption of advanced analytical capabilities is evident across the financial industry, with firms investing heavily in technology. According to Reuters, in an article from October 24, 2023, JPMorgan planned to spend $15 billion on technology in 2023, including AI efforts, reflecting substantial investment in technologies empowering comprehensive risk analytics platforms.

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Key Market Challenges

A significant challenge impeding the growth of the Global Risk Analytics Market arises from issues related to model risk and bias, particularly concerning artificial intelligence and machine learning-driven predictive models. These advanced models, while offering enhanced capabilities, can inadvertently produce inaccurate or skewed outcomes due to inherent biases in training data or model design limitations. This directly undermines confidence in the reliability and fairness of risk analytics solutions, causing organizations to hesitate in their adoption and extensive deployment.

The complexities surrounding the validation and explainability of these sophisticated AI and machine learning models further exacerbate this impediment. According to the Risk Management Association's 2024 Model Risk Management Survey, 69% of responding banks identified cost as the primary challenge to expanding their model validation capabilities. This substantial financial hurdle in ensuring model accuracy and mitigating bias restricts investment in and wider implementation of risk analytics platforms, directly limiting market expansion as organizations prioritize addressing these fundamental validation concerns.

Key Market Trends

The expansion of risk analytics into diverse non-financial sectors is a significant market trend, driven by the escalating need to manage complex operational and external risks. Industries such as manufacturing, healthcare, and utilities are increasingly recognizing the strategic value of these advanced analytical capabilities for navigating intricate supply chain disruptions, evolving geopolitical landscapes, and operational inefficiencies. This broadened application signifies a market shift towards integrated enterprise risk management. RIMS. org's Q3 2024 publication observed increased investments in supply chain risk management across industries due to geopolitical tensions, indicating non-financial entities are enhancing their comprehensive risk approaches. This trend positions risk analytics as fundamental for strategic decision-making in these emerging markets.

The widespread adoption of cloud-native risk platforms marks a fundamental technological shift, offering enhanced scalability, flexibility, and cost-efficiency for risk management. These platforms empower organizations to process extensive data and execute complex models, enabling real-time data ingestion and dynamic risk monitoring vital for agile threat responses. A December 2024 Cloud Security Alliance survey found 60% of financial institutions prioritizing enhanced disaster recovery preparedness and 58% focusing on improved infrastructure scalability via cloud technologies. This adoption is reinforced by industry standardization efforts. The Fintech Open Source Foundation, supported by institutions like Citi, open-sourced its Common Cloud Controls in October 2023 to unify public cloud deployment security standards, fostering confidence in these critical platforms.

Segmental Insights

The Global Risk Analytics Market is observing the Cloud segment as its fastest-growing component, driven by its intrinsic capabilities to deliver highly scalable, flexible, and cost-efficient infrastructure for processing extensive datasets and intricate risk models. Cloud platforms enable organizations to effectively manage larger data volumes, enhance analytical capabilities, and achieve significant reductions in operational expenditure and capital investment. This adoption is further propelled by the need for robust data governance and sophisticated calculation capabilities to meet evolving regulatory compliance standards, such as those underscored by the Basel Committee on Banking Supervision, facilitating adherence to comprehensive risk management frameworks. The Global Risk Analytics Market is observing the Cloud segment as its fastest-growing component, driven by its intrinsic capabilities to deliver highly scalable, flexible, and cost-efficient infrastructure for processing extensive datasets and intricate risk models. Cloud platforms enable organizations to effectively manage larger data volumes, enhance analytical capabilities, and achieve significant reductions in operational expenditure and capital investment. This adoption is further propelled by the need for robust data governance and sophisticated calculation capabilities to meet evolving regulatory compliance standards, such as those underscored by the Basel Committee on Banking Supervision, facilitating adherence to comprehensive risk management frameworks.

Regional Insights

North America leads the Global Risk Analytics Market due to its advanced technological infrastructure and the substantial presence of key market participants. The region benefits from significant investments in analytical solutions by numerous technology firms and financial organizations, driven by a strong emphasis on data-driven decision-making across various industries. Furthermore, stringent regulatory and compliance frameworks, such as Basel III and Dodd-Frank in the United States, necessitate robust risk management approaches, compelling organizations to adopt sophisticated risk analytics solutions to ensure adherence and mitigate potential financial and operational exposures. This combination of technological maturity, a strong industry ecosystem, and demanding regulatory environments firmly establishes North America's dominance.

Recent Developments

• In September 2025, Bloomberg launched AI Portfolio Commentary, an AI-powered feature integrated into PORT Enterprise, its premium portfolio and risk analytics offering. This new functionality was designed to generate detailed explanations of return drivers, thereby streamlining workflows and simplifying reporting for both fixed income and equity portfolios. The system utilizes AI capabilities to deliver contextualized portfolio summaries by merging a portfolio's attribution data with media coverage from various sources. This solution enabled investment teams to quickly identify key performance drivers and relevant news, allowing them to focus on more strategic analysis and enhance efficiency in their risk and portfolio management processes.

• In July 2025, RepRisk announced an expanded collaboration with BlackRock to enhance transparency in business conduct within the investment community. RepRisk's AI-powered data, which combines advanced artificial intelligence with human expertise, was integrated into BlackRock's Aladdin® technology platform. This integration provided asset managers and owners with critical risk insights by making a global dataset covering numerous risk factors accessible through the Aladdin platform. The collaboration aimed to support more rigorous risk management and oversight, delivering early risk signals directly into decision-makers’ workflows and improving capital allocation, business efficiency, and compliance.

• In October 2024, Regnology launched its Granular Data (RGD) model, designed to transform regulatory reporting for financial institutions. This integrated data model aims to standardize and harmonize reporting across multiple jurisdictions, addressing the increasing complexity of financial regulations. RGD builds upon existing data models, providing a framework capable of managing extensive datasets from banks to ensure accurate and timely compliance. The new offering facilitates enhanced analytics and an AI-enhanced regulatory reporting framework. It also introduces advanced functionalities such as extensive data visualization, granular exploration through widgets, and complete traceability for maintaining a robust audit trail within the regulatory cycle.

• In July 2024, Moody's introduced a new Generative AI (GenAI)-powered Early Warning System aimed at enhancing commercial real estate (CRE) portfolio management. This new product provides real-time alerts and risk assessments, responding to the growing demand for rapid and precise risk management within the CRE sector. The system integrates proprietary client data with Moody's comprehensive CRE datasets to conduct swift stress tests and identify potential risk exposures. It also generates alerts for significant changes in CRE data, such as new property listings or shifts in tenant credit profiles, thereby simplifying workflows and improving decision-making for various financial stakeholders.

Key Market Players

• IBM Corporation
• Oracle Corporation
• SAP SE
• SAS Institute Inc.
• Moody's Analytics Inc.
• OneSpan Inc.
• Capgemini SE
• Accenture PLC
• Provenir Group
• AxiomSL Ltd.

Report Scope:

In this report, the Global Risk Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

• Risk Analytics Market, By Component:

o   Solution

o   Service

• Risk Analytics Market, By Deployment:

o   On-premise

o   Cloud

• Risk Analytics Market, By End-User:

o   BFSI

o   Healthcare

o   Retail

o   Manufacturing

o   Others

• Risk Analytics Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Europe

§  France

§  United Kingdom

§  Italy

§  Germany

§  Spain

o   Asia Pacific

§  China

§  India

§  Japan

§  Australia

§  South Korea

o   South America

§  Brazil

§  Argentina

§  Colombia

o   Middle East & Africa

§  South Africa

§  Saudi Arabia

§  UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies presents in the Global Risk Analytics Market.

Available Customizations:

Global Risk Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

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