The PREVIEW Global Risk Data Platform is a multiple agencies effort to share spatial data information on global risk from natural hazards. Users can visualise, download or extract data on past hazardous events, human & economical hazard exposure and risk from natural hazards. It covers tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions. This was developed as a support to the Global Assessment Report on Disaster Risk Reduction (GAR).

The PREVIEW Global Risk Data Platform is a multiple agencies effort to share spatial data information on global risk from natural hazards. It covers tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions. The collection of data is made via a wide range of partners. This was developed as a support to the Global Assessment Report on Disaster Risk Reduction (GAR).This map shows disasters that occurred before the 2013 Global Assessment Report was published.

Data Sources:Cyclones: UNEP/GRID-Geneva, based on various raw data sources.Cyclones storm surges: UNEP/GRID-Geneva, based on Cyclones - winds data.Droughts: UNEP/GRID-Geneva based on Climate Research Unit (CRU) precipitation data. Earthquakes: United States Geological Survey (USGS) ShakeMap Atlas.Fires: European Space Agency (ESA-ESRIN) and World Fires Atlas Program (ATSR). Data from Preview, from the Data User Element of the Genevaan Space Agency.Floods: Dartmouth Flood Observatory (DFO).Tsunamis: National Geophysical Data Center (NGDC) Tsunami database, NOAA.Volcanoes: Smithsonian Institution Volcanoes of the world.

This layer presents an estimation of the global risk induced by flood hazard. Unit is estimated risk index from 1 (low) to 5 (extreme). For more information, visit the Global Risk Data Platform: http://preview.grid.unep.ch/index.php?preview=data&events=floods&evcat=5&lang=eng

Credit Risk Management Platform Market size was valued at USD 7.35 Billion in 2023 and is projected to reach USD 18.47 Billion by 2030, growing at a CAGR of 14.5% during the forecast period 2024-2030.

Global Credit Risk Management Platform Market Drivers

The growth and development of the Credit Risk Management Platform Market is attributed to certain main market drivers. These factors have a big impact on how integrated gas systems are demanded and adopted in different sectors. Several of the major market forces are as follows:

Growing Requirement for Risk Reduction: Robust credit risk management systems are becoming increasingly necessary to reduce possible hazards due to the complexity of financial transactions and uncertainty in the global economy.

Adherence to Regulations: Platforms for credit risk management are frequently adopted due to strict regulatory constraints. Financial institutions must abide by a number of laws to maintain accountability and transparency.

Digital Conversion: Adoption of cutting edge technologies for credit risk management is encouraged by the financial sector’s ongoing digital transformation. In this change, automation, AI, and data analytics are essential components.

Adoption of AI and Data Analytics: The use of credit risk management platforms is facilitated by the growth in data volume as well as the developments in analytics and AI. Accurate risk assessments and decision-making processes are facilitated by these technologies.

The global governance, risk and compliance platform market size reached USD 49.2 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 127.7 Billion by 2033, exhibiting a growth rate (CAGR) of 11.18% during 2025-2033. The growing focus on mitigating risks to protect sensitive data and intellectual property in various sectors, rising number of cyberthreats, and changing regulatory frameworks and compliance requirements are some of the major factors propelling the market.

IMARC Group provides an analysis of the key trends in each segment of the global governance, risk and compliance platform market report, along with forecasts at the global and regional levels for 2025-2033. Our report has categorized the market based on deployment model, solution, component, service, end-user, and industry vertical.

Risk Management Software Market size was valued at USD 11.87 Billion in 2024 and is projected to reach USD 35.08 Billion by 2031, growing at a CAGR of 14.50% during the forecasted period 2024 to 2031.

The Risk Management Software Market is witnessing robust growth due to the increasing recognition of the importance of risk mitigation and compliance across industries in the face of evolving regulatory requirements and complex business environments. Organizations are increasingly turning to sophisticated risk management solutions to proactively identify, assess, and mitigate risks, thereby safeguarding their operations, reputation, and financial performance. Moreover, the growing prevalence of cyber threats, data breaches, and compliance violations is driving demand for advanced risk management software with features such as real-time monitoring, predictive analytics, and incident response capabilities. Furthermore, the adoption of cloud-based risk management solutions is gaining traction as businesses seek scalable and cost-effective alternatives to traditional on-premises systems. Additionally, the integration of artificial intelligence and machine learning technologies into risk management software is enhancing its ability to analyze vast amounts of data and provide actionable insights, thereby fueling market growth.

ESG DATA PRODUCT DESCRIPTION

This ESG dataset offers comprehensive coverage of corporate energy management across thousands of global companies. Our data captures detailed patterns of energy consumption, production, and distribution, providing granular insights into various energy types—including electricity and heat—and the technologies (e.g. solar PV, hydropower...) and sources (e.g. biofuels, coal, natural gas...) utilized. With thorough information on renewability and rigorous standardization of every energy metrics, this dataset enables precise benchmarking, cross-sector comparisons, and strategic decision-making for sustainable energy practices.

Built on precision and transparency, the energy dataset adheres to the highest standards of ESG data quality. Every data point is fully traceable to its original source, ensuring unmatched reliability and accuracy. The dataset is continuously updated to capture the most current and complete information, including revisions, new disclosures, and regulatory updates.

ESG DATA PRODUCT CHARACTERISTICS

• Company Coverage:              5,000+ companies • Geographical Coverage:       Global • Sectorial Coverage:                All sectors • Data Historical Range:           2014 - 2024 • Median Data History:             5 years • Data Traceability Rate:           100% • Data Frequency:                     Annual • Average Reporting Lag:         3 months • Data Format:                            Most Recent/Point-in-Time

UNIQUE DATA VALUE PROPOSITION

Uncompromised Standardization

When company energy data do not align with standard energy reporting frameworks, our team of environmental engineers meticulously maps the reported figures to the correct energy types and flow categories. This guarantees uniformity and comparability across our dataset, bridging the gap created by diverse reporting formats.

Precision in Every Figure

Our advanced cross-source data precision matching algorithm ensures that the most accurate energy metrics are always delivered. For instance, an exact figure like 12,510,545 Joules is prioritized over a rounded figure like 12mio, reflecting our dedication to precision and detail.

Unbiased Data Integrity

Our approach is grounded in delivering energy data exactly as reported by companies, without making inferences or estimates for undisclosed data. This strict adherence to factual reporting ensures the integrity of the data you receive, providing an unaltered and accurate view of corporate emissions.

End-to-End Data Traceability

Every energy data point is directly traceable to its original source, complete with page references and calculation methodologies. This level of detail ensures the reliability and verifiability of our data, giving you complete confidence in our energy dataset.

Full-Scope Boundary Verification

We tag energy figures that do not cover a company's entire operational boundaries with an 'Incomplete Boundaries' attribute. This transparency ensures that any potential limitations are clearly communicated, enhancing the comparability of our energy data.

USE CASES

Asset Management

Asset Management firms use energy data to benchmark portfolio companies against industry standards, ensuring alignment with net-zero goals and regulatory frameworks like SFDR and TCFD. They assess energy transition risks, track renewable energy adoption, and develop sustainable investment products focused on energy efficiency and climate-conscious innovation.

Financial Institutions & Banking

Financial Institutions & Banking integrate energy data into credit risk assessments and sustainability-linked loans, ensuring borrowers meet renewable energy targets. They also enhance due diligence processes, comply with climate disclosure regulations, and validate green bond frameworks with precise renewable energy metrics.

FinTech

FinTech companies leverage energy data to automate regulatory reporting, power energy management analytics, and develop APIs that assess corporate climate risk. They also build sustainable investment tools that enable investors to prioritize companies excelling in energy efficiency and renewability.

GreenTech & ClimateTech

GreenTech & ClimateTech firms use predictive energy analytics to model energy transition risks and renewable adoption trends. They optimize supply chains, facilitate renewable energy procurement, and assess the environmental and financial impacts of energy investments, supporting PPAs and carbon credit markets.

Corporates

Corporates rely on energy data for performance benchmarking, renewable energy procurement, and transition planning. By analyzing detailed energy consumption and sourcing metrics, they optimize sustainability strategies and improve energy efficiency.

Professional Services & Consulting

Professional Services & Consulting firms use energy data to advise on energy transitions, regulatory complia...

Governance Risk And Compliance Software Market size is growing at a moderate pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024-2031.

Global Governance Risk And Compliance Software Market Drivers

The market drivers for the Governance Risk And Compliance Software Market can be influenced by various factors. These may include:

Increasing Regulatory Complexity: Organizations look to GRC software to assure compliance with laws, regulations, and industry standards as regulatory requirements become increasingly complicated and demanding across many industries and geographies.
Risk management is necessary because there are more and more hazards that organizations must deal with, such as operational, financial, and cybersecurity threats. Effective risk identification, assessment, and mitigation are made possible by GRC software.

Cost Efficiency: By automating compliance procedures, lowering human labor, limiting fines and penalties for non-compliance, and improving resource allocation, the implementation of GRC software can result in cost savings.

Integration of GRC Processes: To increase efficiency and effectiveness, a lot of companies are integrating their risk management, governance, and compliance operations. A consolidated platform for controlling these interconnected operations is offered by GRC software.

Demand for Real-time Reporting and Monitoring: There’s a growing need for reporting and risk and compliance status monitoring in real-time. Proactive risk management requires constant monitoring, alerting, and reporting, all of which are characteristics that GRC software provides.

Growing Adoption of Cloud-based systems: Compared to traditional on-premises systems, cloud-based GRC software solutions are more widely used because of their scalability, flexibility, and ease of implementation.

Focus on Corporate Governance: The adoption of GRC software to guarantee transparency, moral conduct, and adherence to company regulations is being driven by an increased focus on corporate governance and responsibility by boards of directors and executives.

Growth of SMEs: The market is getting bigger as more small and medium-sized businesses (SMEs) realize how beneficial GRC software is for efficiently managing risks and compliance.

Technological Developments: To increase predictive insights, automate processes, and enhance decision-making, GRC software is integrating advances in artificial intelligence (AI), machine learning, and analytics.

Globalization and Cross-Border Regulations: Adhering to several, frequently incompatible regulatory frameworks is a problem for multinational corporations. GRC software facilitates the navigation of these complexity and guarantees cross-border compliance.

Global Governance Risk And Compliance Software Market Restraints

Several factors can act as restraints or challenges for the Governance Risk And Compliance Software Market. These may include:

Complexity and Integration Challenges: It is common for GRC software to require integration with an organization’s current IT infrastructure and procedures. Because it takes a lot of resources and experience, the intricacy of these interconnections can be a major limitation.
Cost of Installation and Upkeep: The initial setup and continuing maintenance of GRC software can be expensive. This financial consideration may discourage smaller businesses from implementing all-encompassing GRC solutions.
Insufficient Knowledge and Awareness: Without sufficient governance, risk management, and compliance procedures in place, many firms might not be completely aware of the advantages of GRC software or the hazards they may encounter. Adoption rates may be slower as a result of this ignorance.
Opposition to Change: Organizational procedures and culture typically need to be altered in order to implement GRC software. The effective deployment of GRC solutions may be hampered or delayed by management’s or employees’ resistance to change.
Data Security Issues: GRC software handles private information pertaining to risk management, governance, and compliance. Particularly in sectors with strict regulatory requirements, worries about data security and privacy can be a major roadblock to adoption.
Customization and Scalability Issues: GRC software must be adaptable to meet the unique demands and legal specifications of various businesses and sectors. The adoption of GRC solutions may be impeded by limited customisation possibilities or scalability concerns.
Regulatory and Compliance Challenges: GRC software suppliers may find it difficult to stay on top of the ever-changing regulatory landscape and compliance regulations. Their solutions may become less appealing and successful if they don’t adjust to changing rules.
issue of Being Locked Into a Specific Vendor’s Ecosystem: Companies may be hesitant to implement GRC software if they have this issue. Avoiding vendor lock-in becomes dependent on interoperability and compatibility with other systems.
Performance: GRC software needs to be dependable and effective in order to manage complicated compliance duties and massive data volumes. Organizations may be reluctant to entirely depend on GRC solutions due to performance or reliability issues.
Training and Skill Gaps: Knowledge and training specific to GRC software are frequently needed for its effective use. Inadequate expertise inside a company might hinder software adoption and lower its overall efficacy.

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Risk Management Software Market Size 2024-2028

The risk management software market size is forecast to increase by USD 11.06 billion at a CAGR of 18.69% between 2023 and 2028.

The market is experiencing significant growth due to the increasing number of data and security breaches among enterprises. This trend is driving the demand for advanced risk management solutions that can help organizations mitigate risks and protect their assets. Another key factor fueling market growth is the rising adoption of cloud-based risk management software, along with artificial intelligence and analytics. This delivery model offers several advantages, including lower costs, easier implementation, and greater scalability. 
However, the high cost and complexity of installing and configuring risk management software remain challenges for some organizations, particularly smaller businesses. Despite these challenges, the market is expected to continue expanding as more companies recognize the importance of effective risk management in today's complex business environment. Organizations must stay informed of the latest risk management trends and solutions to ensure they are well-positioned to address evolving threats and mitigate potential risks.

What will be the Size of the Risk Management Software Market During the Forecast Period?

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The market is experiencing rapid digitalization, driven by the increasing adoption of cloud-based applications and the proliferation of smartphones and digital devices. This trend is particularly prominent in industries that require the management of financial tasks, administrative tasks, and risks associated with legal liabilities, financial uncertainty, and security risks. The software enables real-time risk assessment, decision-making, and risk mitigation activities, making it an essential tool for businesses seeking to manage and mitigate potential issues.



With the association between data security and risk management growing, the market is witnessing significant investment in advanced data security features. End-users are increasingly deploying cloud-based solutions to streamline processes, reduce administrative burdens, and improve overall efficiency. The market is expected to continue growing, as businesses seek to stay ahead of evolving risks and ensure business continuity.

How is this Risk Management Software Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Component

  Software
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    Japan


  South America



  Middle East and Africa

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

The market's software segment is experiencing substantial growth due to the increasing importance of risk analysis and mitigation in various industries. Technological advancements, expanding data volumes, and the need for real-time risk assessment are driving this growth. Quantitative risk assessment software, which employs statistical tools and algorithms to quantify risks and develop mitigation strategies, is a popular example. This software is particularly valuable in sectors such as finance, healthcare, and insurance, where it is a key operational focus. The software enables organizations to assess and manage risks associated with financial tasks, administrative tasks, identity theft, security breaches, and natural disasters.

Cloud-based security solutions and integrated banking features further enhance the software's capabilities. Despite the challenges of trade regulations, production analysis, and cyber-attacks, the market's growth prospects remain promising. Organizations across the IT industry, financial institutions, and developing economies are increasingly adopting risk management software to address issues of financial uncertainty, legal liabilities, and security risks.

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The software segment was valued at USD 2.67 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 31% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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Factors such as the presence of many organizations from the banking, financial services and insurance (BFSI), IT se

Tropical Cyclonic Wind and Storm Surge hazard The tropical cyclonic strong wind and storm surge model use information from 2594 historical tropical cyclones, topography, terrain roughness, and bathymetry. The historical tropical cyclones used in GAR15 cyclone wind and storm surge model are from five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic and the tracks were obtained from the IBTrACS database (Knapp et al. 2010). This database represents the repository of information associated with tropical cyclones that is the most up to date. Topography was taken from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world. To account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). This was considered a good proxy of the spatial variation of surface roughness. A digital bathymetry model is employed with a spatial resolution of 30 arc-seconds, taken from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009). Bathymetry is the information about the underwater floor of the ocean having direct influence on the formation of the storm surge. More information about the cyclone wind and strom surge hazard can be found in CIMNE et al., 2015a. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). The vulnerability models used in the risk calculation for GAR correlate loss to the wind speed for 3-seconds gusts. For GAR15, the risk was calculated with the CAPRA-GIS platform which is risk modelling tool of the CAPRA suite (www.ecapra.org). The risk assessment was also conducted by CIMNE and Ingeniar to produced AAL and PML values for cyclone risk.

Portfolio Risk Management Software Market size was valued at USD 3.1 Billion in 2023 and is projected to reach USD 12.9 Billion by 2030, growing at a CAGR of 14.3% during the forecasted period 2024 to 2030

Global Portfolio Risk Management Software Market Drivers

Increasing Complexity of Financial Markets: The need for sophisticated portfolio risk management software is driven by the financial markets’ increasing complexity, which includes a wide range of investment products, asset classes, and interconnection across the world economy. In volatile market situations, investors and asset managers need advanced tools and analytics to evaluate and reduce risks across their investment portfolios.

Needs for Regulatory Compliance: Financial institutions and investment organizations must improve their risk management processes and transparency in order to comply with strict regulatory mandates and reporting requirements such as Basel III, Solvency II, MiFID II, and the Dodd-Frank Act. Software solutions for portfolio risk management make regulatory compliance easier and enable features like scenario analysis, stress testing, and risk reporting.

Prudent Investing Techniques: The trend toward risk-aware investing techniques like factor investing, tail risk hedging, risk parity, and smart beta emphasizes how crucial it is to manage portfolio risk effectively. With the use of quantitative risk models and optimization strategies made possible by risk management software, investors aim to maximize risk-adjusted returns, reduce downside risk, and control portfolio volatility.

Volatility and Uncertainty in Financial Markets: The requirement for real-time risk monitoring, scenario analysis, and stress testing capabilities provided by portfolio risk management software is driven by increased market volatility, geopolitical instability, and macroeconomic uncertainty. In order to control portfolio performance, investors attempt to evaluate and manage risks associated with systemic events, market shocks, and geopolitical threats.

Put Risk-adjusted Performance First: When assessing investment strategies and portfolio allocations, investors are placing a greater emphasis on risk-adjusted performance metrics including the Sharpe ratio, Sortino ratio, and information ratio. Portfolio risk management software integrates risk metrics with performance attribution and portfolio optimization tools to give investors the ability to track, evaluate, and improve risk-adjusted returns.

The need for ALM, or asset-liability management: Robust asset-liability management (ALM) solutions are necessary for institutional investors, insurance firms, pension funds, and endowments to manage liquidity risk, long-term liabilities, and asset allocation choices. ALM features like cash flow modeling, duration matching, immunization tactics, and liability-driven investing (LDI) approaches are provided by portfolio risk management software.

Technological and analytical advances: The constant progress in data analytics, artificial intelligence (AI), and technology propels innovation in portfolio risk management software. Capabilities for risk modeling, scenario analysis, and decision assistance are improved by features including big data analytics, machine learning, predictive analytics, and natural language processing (NLP).

Cloud-based solutions are in demand: Cloud-based portfolio risk management software solutions being adopted more quickly as cloud computing and software-as-a-service (SaaS) delivery methods gain traction. With web-based interfaces, cloud-based platforms provide scalability, flexibility, and accessibility, allowing users to access analytics and risk management capabilities at any time and from any location.

Emphasis on Enterprise-Wide Risk Management: Businesses want to include risk management procedures into front-, middle-, and back-office operations. By facilitating enterprise-wide risk aggregation, reporting, and governance, portfolio risk management software solutions help enterprises monitor and manage risks holistically across business units and asset classes.

1. Temporal Coverage of Data: The data collection periods are 2010, 2030, and 2050.2. Spatial Coverage and Projection:Spatial Coverage: GlobalLongitude: -180° - 180°Latitude: -90° - 90°Projection: GCS_WGS_19843. Disciplinary Scope: The data pertains to the fields of Earth Sciences and Geography.4. Data Volume: The total data volume is approximately 31.5 MB.5. Data Type: Raster (GeoTIFF)6. Thumbnail (illustrating dataset content or observation process/scene): · 7. Field (Feature) Name Explanation:a. Name Explanation: IND: Industrial Value Addedb. Unit of Measurement: Unit: US Dollars (USD)8. Data Source Description:a. Remote Sensing Data:2010 Global Vegetation Index data (Enhanced Vegetation Index, EVI, from MODIS monthly average data) and 2010 Nighttime Light Remote Sensing data (DMSP/OLS)b. Meteorological Data:From the CMCC-CM model in the Fifth International Coupled Model Intercomparison Project (CMIP5) published by the United Nations Intergovernmental Panel on Climate Change (IPCC)c. Statistical Data:From the World Development Indicators dataset of the World Bank and various national statistical agenciesd. Gross Domestic Product Data:Sourced from the project "Study on the Harmful Processes of Population and Economic Systems under Global Change" under the National Key R&D Program "Mechanisms and Assessment of Risks in Population and Economic Systems under Global Change," led by Researcher Sun Fubao at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciencese. Other Data:Rivers, roads, settlements, and DEM, sourced from the National Oceanic and Atmospheric Administration (NOAA), Global Risk Data Platform, and Natural Earth9. Data Processing Methods(1) Spatialization of Baseline Industrial Value Added: Using 2010 global EVI vegetation index data and nighttime light remote sensing data, we addressed the oversaturation issue in nighttime light data by constructing an adjusted nighttime light index to obtain the optimal global light data. The EANTIL model was developed using NTL, NTLn, and EVI data, with the following formula:Here, EANTLI represents the adjusted nighttime light index, NTL represents the original nighttime light intensity value, and NTLn represents the normalized nighttime light intensity value. Based on the optimal light index EANTLI and the industrial value-added data from the World Bank, we constructed a regression allocation model to derive industrial value added (I), generating the global 2010 industrial value-added data with the formula:Here, I represents the industrial value added for each grid cell, and Ii represents the industrial value added for each country, EANTLi derived from ArcGIS statistical analysis and the regression allocation model.(2) Spatial Boundaries for Future Industrial Value Added: Using the Logistic-CA-Markov simulation principle and global land use data from 2010 and 2015 (from the European Space Agency), we simulated national land use changes for 2030 and 2050 and extracted urban land data as the spatial boundaries for future industrial value added. To comprehensively characterize the influence of different factors on land use and considering the research scale, we selected elevation, slope, population, GDP, distance to rivers, and distance to roads as land use driving factors. Accuracy validation using global 2015 land use data showed an average accuracy of 91.89%.(3) Estimation of Future Industrial Value Added: Based on machine learning and using the random forest model, we constructed spatialization models for industrial value added under different climate change scenarios: Here, tem represents temperature, prep represents precipitation, GDP represents national economic output, L represents urban land, D represents slope, and P represents population. The random forest model was constructed using factors such as 2010 industrial value added, urban land distribution, elevation, slope, distances to rivers, roads, railways (considering transportation), and settlements (considering noise and environmental pollution from industrial buildings), along with temperature and precipitation as climate scenario data. Except for varying temperature and precipitation values across scenarios, other variables remained constant. The model comprised 100 decision trees, with each iteration randomly selecting 90% of the samples for model construction and using the remaining 10% as test data, achieving a training sample accuracy of 0.94 and a test sample accuracy of 0.81.By analyzing the proportion of industrial value added to GDP (average from 2000 to 2020, data from the World Bank) and projected GDP under future Shared Socioeconomic Pathways (SSPs), we derived future industrial value added for each country under different SSP scenarios. Using these projections, we constructed regression models to allocate future industrial value added proportionally, resulting in spatial distribution data for 2030 and 2050 under different SSP scenarios.10. Applications and Achievements of the Dataseta. Primary Application Areas: This dataset is mainly applied in environmental protection, ecological construction, pollution prevention and control, and the prevention and forecasting of natural disasters.b. Achievements in Application (Awards, Published Reports and Articles):Achievements: Developed a method for downscaling national-scale industrial value-added data by integrating DMSP/OLS nighttime light data, vegetation distribution, and other data. Published the global industrial value-added dataset.

The Risk Detection Platform market is experiencing significant growth as organizations increasingly recognize the importance of managing risks effectively in an ever-evolving landscape. These platforms play a crucial role in various industries by allowing companies to identify, assess, and mitigate potential risks i

Tropical cyclone wind footprints (m/s) at 150 arcsec (approx 4 kilometers at equator) resolution. Available as global files and per country; available for historically observed records, and synthetically created, probabilistic events, from various modelling sources, for present and future climate scenarios.

Snapshot img

Governance Risk and Compliance Platform Market Size 2025-2029

The governance risk and compliance platform market size is forecast to increase by USD 44.22 billion at a CAGR of 14.2% between 2024 and 2029.

The global governance, risk, and compliance (GRC) platform market is expanding as businesses face increasing regulatory demands and adopt advanced technology to manage risks. Key drivers include the shift toward proactive risk management among organizations and the integration of AI and machine learning (ML), which streamline compliance processes and improve decision-making.
This report delivers a comprehensive look at the market, covering its current size, growth projections through 2029, and key segments like cloud-based platforms and large enterprises. It's tailored for practical use—supporting strategic planning, stakeholder engagement, or operational efficiency—with data on market value and regional trends. A significant trend is the growing use of real-time analytics for compliance monitoring, though a notable challenge is the complexity of integrating GRC platforms with existing systems, which can slow adoption. For companies aiming to stay competitive in the global business landscape, this report provides critical insights to tackle evolving regulatory trends and integration hurdles, enabling smarter risk and compliance strategies in a fast-changing environment.

What will be the Size of the Governance Risk and Compliance Platform Market During the Forecast Period?

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Governance, risk, and compliance (GRC) platforms have become essential tools for businesses to manage their complex regulatory environment and mitigate various risks. These platforms help managers streamline business processes and ensure compliance with ever-changing requirements. However, the implementation and integration of these solutions can come with significant costs. Social media governance and cyber threats are two critical areas where GRC platforms and eGRC solutions play a pivotal role. With the increasing use of social media for business communication, it is essential to have strong governance policies in place to mitigate potential risks. Similarly, cyber threats continue to evolve, making it necessary for businesses to invest in advanced risk management solutions.



Intellectual property protection is another crucial aspect of GRC platforms. In today's globalized business landscape, protecting intellectual property rights has become a significant challenge. GRC platforms can help businesses manage and monitor their intellectual property assets, ensuring they are adequately protected. The changing regulatory environment and increasing compliance requirements add to the complexity of implementing GRC platforms. Technology integration is another challenge, especially with the adoption of artificial intelligence and machine learning. Oracle's EGC suite and MetricStream are examples of software that offer advanced risk and compliance capabilities. Despite the benefits, the high implementation expenses and complexity of integration can deter some businesses from adopting GRC platforms. Financial institutions, IT telecoms, and other industries that deal with sensitive data are particularly vulnerable to the risks of non-compliance. Therefore, investing in GRC platforms is not just an option but a necessity for businesses looking to mitigate risks and ensure regulatory compliance.

How is the Governance Risk and Compliance Platform Market Segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud-based


Component

  Software
  Services


Application

  Risk Management
  Compliance Management
  Audit Management
  Policy Management


Enterprise Size

  Small and Medium Enterprises (SMEs)
  Large Enterprises


Industry Vertical

  Banking, Financial Services, and Insurance (BFSI)
  Healthcare
  IT and Telecom
  Manufacturing
  Retail and Consumer Goods
  Government and Public Sector
  Energy and Utilities


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan


  South America

    Brazil
    Argentina


  Middle East and Africa

    Egypt

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period. In the realm of business operations, Governance, Risk, and Compliance (GRC) platforms play a pivotal role in ensuring an organization's adherence to regulatory requirements, risk management, and corporate governance. On-premises GRC solutions encompass three essential dimensions: governance, risk management,

The Risk and Compliance Resolution Platform market has gained significant traction in recent years, as organizations across various industries grapple with the complexities of regulatory compliance and risk management. These platforms provide a robust solution for companies seeking to navigate the increasingly intri

This hazard data delivery is derived from the Impact Forecasting Earthquake catastrophe model. The Impact Forecasting Earthquake hazard and risk data covers 31 countries. The data is derived from the Impact Forecasting earthquake models which have been built over a number of years by the team in collaboration with internationally recognised seismologists and earthquake engineers at a number of academic institutions and agencies. The models are developed for individual countries and provide hazard and risk scores. The original model produced hazard maps in terms of MMI. MMI values have been converted to PGA using the relationship of Wald, et al. (1999). MMI values of >10 have been limited to MMI 10 prior to conversion

The global risk detection platform market is projected to reach a value of USD XX million by 2033, driven by a CAGR of XX% over the forecast period of 2025-2033. The increasing need for organizations to mitigate risks in the face of evolving cyber threats and expanding regulatory compliance mandates is a key factor driving market growth. Additionally, advancements in artificial intelligence (AI), machine learning (ML), and data analytics are enabling risk detection platforms to offer enhanced capabilities, such as real-time monitoring, predictive analytics, and automated threat response. The market is segmented by type into cloud-based and on-premise solutions. Cloud-based solutions are gaining popularity due to their scalability, cost-effectiveness, and ease of deployment. By application, the market is segmented into SMEs (small and medium-sized enterprises) and large enterprises. Large enterprises are the primary users of risk detection platforms, due to their complex IT environments and stringent security requirements. Key players in the market include PwC, SecurityHQ, Panther Labs, Vectra AI, Abra Innovations, Inc., Dataminr, Coalition, Inc., SecurityScorecard, DataVisor, Inc., Qualys, Gurucul, ThreatQuotient, and Darktrace. The market is also characterized by a growing number of innovative startups offering specialized risk detection solutions.

Eastern Europe and Central Asia Region project – Earthquake hazard layers for 10, 50, 100, 250, 475, 975, 1500, 2500 year return periods measured in PGA (peak ground acceleration) from the ECA risk profile project in 2014. Countries covered: TR, GR, RU, AL, TJ, HR, BG, RS, KG, RO, BA, GE, CY, SI, AZ, UZ, AM, KZ, MN, HU, TM, MK, ME, PL, MD, UA, CZ, KV, SK, BY, EE, LT, LV. Resolution: 2km by 2km.

ESG DATA PRODUCT DESCRIPTION

Market-leading ESG dataset tracking corporate waste management performance across 4,000+ global companies. Our data provides granular breakdowns of hazardous and non-hazardous waste streams, alongside comprehensive coverage of disposal methods and recovery rates. Through rigorous standardization of waste categories and treatment methods, we enable precise cross-company comparisons and sectoral benchmarking.

ESG DATA PRODUCT CHARACTERISTICS

• Company Coverage:              4,000+ companies • Geographical Coverage:       Global • Sectorial Coverage:                All sectors • Data Historical Range:           2021 - 2024 • Median Data History:             2 years • Data Traceability Rate:           100% • Data Frequency:                     Annual • Average Reporting Lag:         3 months • Data Format:                            Most Recent/Point-in-Time

UNIQUE DATA VALUE PROPOSITION

Uncompromised Standardization

When company waste data do not align with standard waste reporting frameworks, our team of environmental engineers meticulously maps the reported data to the correct waste categories and disposal methods. This guarantees uniformity and comparability across our dataset, bridging the gap created by diverse reporting formats.

Precision in Every Figure

Our advanced cross-source data precision matching algorithm ensures that the most accurate data is always delivered. For instance, an exact figure like 1,542,450 tCO2e is prioritized over a rounded figure like 1,500,000 tCO2e, reflecting our dedication to precision and detail.

Accuracy in Every Metric

Our advanced cross-source data precision matching algorithm ensures that the most accurate data is always delivered. For instance, an exact figure like 15,245 metric tons of waste is prioritized over a rounded figure like 15,000 metric tons, reflecting our dedication to precision and detail.

Unbiased Data Integrity

Our approach is grounded in delivering waste data exactly as reported by companies, without making inferences or estimates for undisclosed data. This strict adherence to factual reporting ensures the integrity of the data you receive, providing an unaltered and accurate view of corporate waste management.

End-to-End Data Traceability

Every data point we provide is directly traceable to its original source, down to the page numbers and exact coordinates within source documents. This level of detail ensures you have access to the most reliable and verifiable waste data available, equipping you with data you can trust completely.

Full-Scope Boundary Verification

We tag waste figures that do not cover a company's entire organizational or operational boundaries with an 'Incomplete Boundaries' attribute. This attribute enhances transparency and ensures the comparability of our data by keeping you informed of any potential limitations.

USE CASES

Asset Management

Utilize waste management data for comprehensive portfolio management, including SFDR and TNFD compliance reporting, sustainability benchmarking, risk analysis, thematic investment strategies focused on circular economy, and stewardship activities. The data enables assessment of waste-related risks, identification of sustainability leaders, and supports engagement with portfolio companies.

Financial Institutions & Banking

Leverage waste data for credit risk assessment, green lending, environmental due diligence, regulatory compliance, and supply chain finance. The data supports evaluation of borrower operational efficiency, structuring of sustainability-linked products, and development of circular economy financing solutions.

FinTech

Develop technology solutions incorporating waste management data, including ESG analytics platforms, sustainability reporting solutions, supply chain analytics tools, impact measurement platforms, and sustainable investment apps for retail investors, enabling comprehensive assessment and monitoring of corporate waste performance.

GreenTech & ClimateTech

Use waste data to power circular economy solutions, waste management software, environmental compliance platforms, and sustainability management software, enabling optimization of waste operations, regulatory compliance monitoring, and comprehensive environmental performance tracking.

Corporates

Employ waste data for performance benchmarking against industry peers, supply chain optimization, sustainability reporting, and procurement strategy development, enabling data-driven decision-making in waste management and circular economy initiatives.

Professional Services & Consulting

Utilize waste data for industry research and benchmarking, ESG advisory services, sustainability strategy development, and regulatory compliance advisory, helping clients improve environmental performance and meet regulatory requirements.

Research & Academia

Analyze waste management data for enviro...