Risk Analytics Market size was valued at USD 27 billion in 2022 and is poised to grow from USD 32.91 billion in 2023 to USD 160.47 billion by 2031, at a CAGR of 21.90% during the forecast period (2024-2031). R
Risk analytics tools are responsible for combating with cyber threats and they measure and identify the risk more precisely. Companies are now enhancing their performance utilizing better computing abilities, big data, and advanced analytics. Risk analytics is utilized in various applications for businesses. Increasing incidences of cyberattacks and data enforcement is the businesses are boosting the development of the risk analytics market. There are many sectors that are embracing risk analytics tools for risk management, like banking and financial sector, manufacturing, medical care, IT & telecommunication, and many more., supporting the progression of the market. The primary task of the risk analysis is recognizing the challenging area of the business. The market is majorly propelled by the rising requirement of systematic risk evaluation because of the extending volume and variety of data that needs analysis. The increasing focus on compliance and regulatory necessities throughout sectors is boosting demand. Today businesses are also becoming more globalized which requires better management of various complex risks, resulting in higher investment in advanced solutions for risk management. Increase in cyber threats are also urging organizations to analyze and respond to cybersecurity risk, is positively influencing the market.
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Risk Analytics Market Top Player’s Company Profiles
- IBM (United States)
- Oracle (United States)
- FIS (United States)
- Moody’s Analytics (United States)
- AON (United Kingdom)
- ServiceNow (United States)
- SAP (Germany)
- Marsh McLennan (United States)
- SAS Institute (United States)
- ProcessUnity (United States)
- MetricStream (United States)
- Resolver (Canada)
- Milliman (United States)
- LogicManager (United States)
- Provenir (United States)
Increasing Incorporation of Artificial Intelligence and Machine Learning to Automate Complex Analysis
One of the major factors impacting the market is the incorporation of AI and ML into risk analytics solutions. This harmonious combination of analytics tools with AI and ML has evolved the way businesses understand and manage risks. These advanced technologies allow a more dynamic and predictive method, resulting in automating complex analysis that utilized to need intensive human labor. This improves both the speed and accuracy of risk assessment, allowing organizations to respond actively. Furthermore, the utilization of AI and ML enables companies to examine through the huge amount of data to recognize subtle, complex patterns that might indicate risks. The innovation of incorporating AI and ML is changing risk management practices and contributing to the market development.
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Segments covered in Risk Analytics Market are as follows:
- Offering
- Software {Type (ETL Tools, Risk Calculation Engines, Scorecard and Visualization Tools, Risk Reporting Tools (Pre-built parameterized standard reports, Drill down & through reporting, Audit & data quality reports, Enterprise reporting, Compliance reporting, other risk reporting tools), Dashboard Analytics, GRC Software and Others}, Deployment Mode (cloud and on premises)}, and Service {professional services, (Consulting services, Deployment & Integration and Support & Maintenance), and a Managed Services}
- Risk Type
- Strategic risk (Operational Risk {Real-time monitoring, Automated risk assessments, Equipment failures, Human errors, Supply chain disruptions, Model risk, Other}, Reputational Risk {Negative publicity, Customer dissatisfaction, Competitive risk, Product recall risk, Ethical controversies, Proactive crisis management, Other}, Governance Risk {Weak corporate governance, Lack of oversight, Data retention, Other}, Political Risk {Political instability, Trade restrictions, Tax policy reform, Other} and Financial Risk {Capital management, Trading risk, Inadequate financial planning, Liquidity risk, Credit risk, Anti-money laundering, Payment fraud detection, Other}), Regulatory risk {Tariffs And Trade Policies, Minimum Wage Laws, Lack Of Awareness And Training, Other}, Environmental risk {Natural Disasters, Climate Change, Pollution, Biodiversity Loss, Human Activities, Toxic Hazard Risk Assessment, Other}, and Other
- Risk Stages
- Risk identification, Risk assessment and prioritization, Risk response and mitigation, Risk monitoring, and Risk reporting
- Vertical
- BFSI, Retail and Ecommerce, Healthcare and Life sciences, Telecommunications, Energy and utilities, Manufacturing, Transportation and Logistics, Government and Defence, Mining, Construction, and Others
Rising Concern for Data Privacy Leads to Emphasis on Consumer Data Protection
The focus on consumer data protection is increasing along with the introduction of strict regulations like GDPR, resulting in substantial growth of the market. Organization of any scale are going through immense pressure to ensure that they are managing customer data by following various international and local privacy laws. This has increased the role of the tools in recognizing and reducing possible compliance risks otherwise the companies might have to pay substantial fine, which will also cause damage to the reputation. Nowadays, people expect that companies will keep their data safe with the rising concern about data privacy. This has influenced the culture of transparency and accountability. Risk analytics have become a vital tool for developing and maintain trust, along with navigating the complex regulatory settings. Therefore, this emphasis on data security and privacy is leading to the growth of the market.
- Moody’s introduced a new product in July 2024. This solution focuses on changing commercial US portfolio management by using generative AI.
- Galileo Financial Technologies introduced 3D Secure in July 2024. It will help clients against card-not-present debit and credit card fraud. The product will provide payment security across industries.
- Origami risk launched its new package generative AI solutions for risk management in May 2024 at RIMS. The solution will assist risk managers to take informed approach for embracing the latest AI tools.
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Advent of Artificial Intelligence to Enhance Risk Analytics Abilities with Predictive Modeling
The advent of artificial intelligence is presenting massive opportunities for the risk analytics market in several ways. AI technologies like machine learning and natural language processing has the potential to improve the abilities of risk analytics by enhancing data analysis, predictive modelling, and decision making. AI can also rapidly process huge amount of data from different sources, which also includes structured and unstructured data. This is especially useful in risk analysis because here large datasets must be analyzed for recognizing and assessing the risks. ML algorithms can also develop more accurate predictive models to detect potential risks.
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