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The global risk analytics market size was valued at USD 22.18 billion in 2019 and is projected to reach USD 54.95 billion by 2027, exhibiting a CAGR of 12.2%. North America dominated the global risk analytics market share of 33.77% in 2019.
The global market is primarily driven by an increasing need for a unified platform that enables risk managers and companies to assess, calculate, forecast, and mitigate risk more easily. Additionally, increasing demand from the emerging economies and the introduction of Artificial Intelligence (AI) into this analytics are projected to create significant opportunities for software developers. Several vendors in the market are focusing on providing AI integrated solutions that help businesses tackle emerging risks.
For instance, in April 2019, Citigroup, Inc. launched an AI-powered NextGen project, an advanced risk analytics scoring engine by collaborating with Ernst & Young Global Limited (EY) and SAS Institute, Inc. NextGen was developed to further streamline time-consuming, heavily manual procedures involved with the analysis of large amounts of foreign trading transactions while maintaining regulatory compliance.
The rapid adoption of vast volumes of structured and unstructured data in the different sectors is increasing demand for risk mitigation to handle and preserve data from attacks. The businesses are shifting towards a holistic approach to risk governance and the implementation of integrated strategies that enable improved regulatory reporting and stay ahead of the competition.
An Infographic Representation of Risk Analytics Market
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Within weeks, the COVID-19 pandemic has ravaged the globe and put significant pressure on individuals and companies across the world. In particular, the risk management industry is impacted by competitive market dynamics, declining credit standards, and threats to business continuity, among others. The unforeseen recession often poses concerns regarding the firms' current risk control systems in terms of their efficacy and agility.
In the face of such a health emergency, governments are responding by unexpectedly implementing stringent quarantine steps, such as the Wuhan chain. Such reactions may trigger business interruptions and compel companies to slow down or even halt operations altogether.
The impacts of a global pandemic of the disease may be especially problematic for organizations that do not have appropriate communicable risk policies and response plans. The COVID-19 crisis depicts companies that need to amend and extend their risk administration and business continuity strategies with a concentration on employees, clients, supply chain partners, stakeholders, and corporate properties.
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Businesses Adopting Reactive and Predictive Risk Models to Adequately Manage Risks has become Major Trend
Reactive risk management is the primary reporting system through which the company monitors and records failure incidents in real-time since they have happened. This model enables companies to adapt to post-risk scenarios with a remediation strategy and the potential to deter comparable incidents from occurring in the future.
Predictive risk management allows companies to identify potential risks and challenges, particularly forms of dangers not addressed by established risk indicators. It applies analytics to current and historical knowledge from internal and external data sources to detect emerging threats with a brief effect period. This capacity aims to modernize the existing system from periodic risk reporting to actual and near-real-time risk reporting. Integrated methodologies provide a summary of risk perception by offering a comprehensive understanding of risk across the enterprise. As the risk environment continues to change and challenges the stability, sustainability, value-creation processes, and success of organizations, businesses are moving from traditional risk methods to advanced risk evaluation models such as reactive and predictive.
Thus, the adoption of reactive and predictive risk management models is considered as an emerging trend and helping organizations redefine understanding of emerging risks.
Data Mining and Machine Learning Capabilities helping Businesses stay Competitive in an Era of Ever-changing Risks
Risk analysis helps mitigate potential business risks by leveraging a variety of tools and technologies to extrapolate observations, quantify possible outcomes, and forecast potential incidents. These solutions enable businesses to mitigate the risk of a data breach by analyzing the amount of structured and unstructured data. This enables businesses to obtain actionable information into data sources and take possible steps to reduce data breaches. Risk analysis may be used to combine all data into a single, coherent vision, collect valuable information, and offer actionable insights that can help business plan their strategy and drive organizational growth.
The sheer amount of accessible data has risen steadily in recent years, and innovative methods have been built to translate this explosion of raw data into actionable business insights. Machine learning, a concept that covers a variety of algorithmic solutions including mathematical techniques such as neural network regression has quickly progressed to the mainstream.
Integrating data collected by companies with risk analysis solutions help organizations and management teams discover and classify potential risks and offer actionable knowledge, allowing them to simplify the business processes. Data analytics will provide a forward-looking perspective of evolving risks, such that leaders can analyze these possible hazards, identify and manage the causes. With growing data-driven culture being adopted by the companies across the industries is projected to supplement the demand for these solutions.
Organizations Implementing Artificial Intelligence (AI)-based Risk Analytics Models to Mitigate Risks will Boost Risk Analytics Market Growth
In an increasingly dynamic, challenging, and fast-paced environment, companies need to continuously improve their management strategies, expanding from a solid basis of security and enforcement to a wider perspective that affects strategic decision-making and improves organizational efficiency. AI is evolving as the next great technological stream by enabling businesses to address and mitigate specific threats such as data breaches, cyber-attacks, and others.
AI can be used to develop advanced methods for tracking and evaluating actions and events in real-time. Such programs may respond to increased risk situations and help to improve the management capability of the enterprises in fields such as regulatory enforcement and corporate governance. AI technologies may also be used to minimize threats in certain key areas.
For example, machine learning might provide more accurate decisions about the probability of a person or company defaulting on a loan or contract, which can be used to create different revenue forecasting models. Similarly, businesses that leverage cognitive technology and AI to predict and proactively mitigate threats will achieve a strategic edge and utilize risk to improve the efficiency of their organizations.
The financial services sector, IT companies, and retail businesses are emphasizing in AI technology, especially for the development of key functions. AI adoption has been swift and continues to be increasing traction, as a significant number of companies are intending to implement machine learning and other aspects of AI. All these factors indicate that AI technology will disrupt the market and will become an extremely valuable resource for risk monitoring, modeling, and analytics. These solutions and service providers are planning to extend their abilities, combining experience in the area with intensely quantitative and analytical capabilities.
Mismeasurement of Known Risks and Complex Nature of Unstructured Data to Impact Business Functionalities
Data collection and interpretation are the key foundation, and several organizations have discovered that the vast volume of data used to accurately evaluate operating threats can be overwhelming. A top-down methodology is used to effectively optimize risk reduction results, methodically analyzing each variable before correlations are identified. Risk management teams find it extremely important that the correct data is always obtained in the process. It is also important to monitor the volume and accuracy of the assessment data using tools and models.
Most businesses struggle to see the value of data in recognizing risk exposures, especially from a compliance viewpoint, and failing to do so may have disastrous consequences in terms of regulatory prohibitions.
The expense of adopting analytics solutions into business processes and the presence of legislative obstacles have inhibited companies from implementing risk management models. Besides, major analytical and technological problems need to be addressed in designing management strategies that can identify and measure various forms of risk across a broad variety of business activities. However, recent developments in computer infrastructure, legislative reforms, and breakthroughs with new techniques indicate the obstacles may collapse in the coming months and years.
Software Segment have Gained Significance Owing to its Numerous Benefits
The risk analytics market is segmented into software and services.
The software segment is expected to earn a large market share during the forecast period. Risk software includes sophisticated technology platforms that can tackle dynamic scenarios and complexities. This software has started to improve business assessments and control efficiency alongside human reasoning and conventional analytics. Businesses and public sector organizations have made strides in leveraging large volumes of internal and external data to adopt a more reactive risk approach.
Modern techniques of risk analysis have now been largely unable to manage vast data quantity. The tools and software complement are utilized across such large data sets to better define measures of known and unknown risks.
Analytics software enables organizations to create a framework for risk assessment around the enterprise by aggregating several specific forms of risk data into one unified program. This tool offers a transparent method for decision-makers to define, evaluate, understand, and handle the risks of the brand. The software segment is further segmented into the extract, transform & load (ETL) tools, Governance, Risk and Compliance (GRC) software, risk calculation engine, scorecard and visualization tools, risk monitoring, and strategic planning, and others.
The GRC software segment has gained huge momentum across businesses over the forecast period. GRC provides the opportunity to provide a more comprehensive picture of the organization and operations, allowing businesses to gain exposure to the risks and challenges included in business functionality.
Financial Risk Segment Accounted for Largest Market Share Attributed to the Constantly Evolving Threats in BFSI
Based on risk type application, the risk analytics market is segmented into financial risk, operational risk, compliance risk, strategic risks, and others.
Regulatory and business conditions have been more complex and uncertain as compared to the previous years. Recently, financial companies have encountered a range of additional regulatory standards. Financial risks give rise to the possibility of damages resulting from the inability to meet financial goals. Uncertainties related to international exchange levels, interest rates, asset costs, stock values, credit quality, liquidity, and access to financing by the company poses a threat to the businesses. Advanced risk analytics solutions are helping banks and financial firms to predict consumer behavior and preferences and to enhance evaluation.
Moreover, as banking is becoming more customer-centric, analytics is becoming an important part of creating loyalty and maximizing profitability. Data collected from Smartphone devices, internet banking, and ATMs enable banks to truly identify the needs of their clients and the degree of risk they might face. Although risk skills have increasingly evolved, most banks have established their key risk supervision strategy in the face of new legislation or supervisory findings. As a response, banks are searching for ways to become more productive by streamlining procedures and rising automation.
The operational risks segment is expected to grow with the highest CAGR during the forecast period. Operational risk management is a technique for organizations that aim to incorporate practical risk control regulation and policy. Every business is confronted with circumstances or fundamental changes in its condition, which can be seen as portraying risk levels to the business, from minor annoyances to endangering its existence. These analytics solutions enable businesses to improve the reliability of business operations by strengthening the decision-making process where most of the risks are associated.
Adoption of Risk Analytics Solutions to Expand among Large Enterprises
Based on enterprise size, the risk analytics market has been bifurcated into small and medium-sized enterprises (SMEs) and large enterprises.
Large enterprises segment holds dominance as prudent risk management strategies enable large companies to recognize threats connected with ongoing projects, thereby allowing them to resolve the issue before it escalates. Risk management systems enable large enterprises to improve risk control, monitoring, and review. Structured reports that monitor corporate risks can improve the focus of managers and executives by gathering data that allows better risk reduction decisions. The diversity of data (i.e. status of main risk factors, prevention methods, current and existing threats, etc.) allows leadership to identify the most relevant risk fields. Such studies can also help leaders gain a clearer understanding of risk sensitivity, risk levels, and risk tolerances.
On the other side, SMEs are considered to be of significant importance to the growth of any economy. However, they are susceptible to threats, such as market risk, finding, budgeting, etc. Small and medium-sized enterprises are exposed to many risks in their normal course of business. Some of these risks include interest rate risk and foreign exchange risk, and so on, which could reduce their profits and lead to financial losses. Risk assessment tools develop leading measures that help SMEs to predict a potential risk incident as well as mitigate the risk exposure.
Cloud-based Solutions to Witness Surging Demand Owing to Efficiency Offered
Based on deployment, the risk analytics market has been segmented into the cloud and on-premises.
Among these segments, the on-premises segment holds the largest share. Through deploying risk assessment tools installed within the business premises, the risk supervision department has actual access to the system and can closely monitor the configuration, maintenance, and protection of the computer network and data.
Cloud-based solutions provide several features including data mining framework, efficient data storage platform, and risk assessment tools that help businesses to improve their operations. A cloud-based solution is a modern trend for companies looking to upgrade their existing solutions. These solutions provide many benefits over on-premises systems such as better user interface, frequent product upgrades, enhanced monitoring, and analysis, among others.
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BFSI Sector is Expected to Witness Large Adoption of these Analytics Solutions
Based on industry, the market is segmented into banking, financial services and insurance (BFSI), IT and telecommunications, healthcare, retail and consumer goods, energy and utilities, manufacturing, and others.
Banks and financial firms across the globe require a reasonable solution to handle an increasing multitude of uncertainties in the banking and financial industry. With the increase of computational resources and modern risk analytical methods, banks will now derive greater and more useful information from their ever-growing data sources. Therefore, it has enabled banks to implement sophisticated analytical strategies on an industrial scale.
Financial companies are under extreme strain to reduce fraud and meet with stringent regulatory enforcement criteria as their market is increasing. Data and security breaches are the main forms of abuse that financial companies currently face. These Analytics tools defend against these and other malicious behaviors through online and mobile platforms through machine-based risk analysis, a type of AI.
Manufacturers often face loss of non-public information beyond intellectual property issues. Manufacturers should consider the threats inherent in maintaining and storing company assets and design models. In addition to an efficient risk reduction plan, which involves information protection awareness services and reporting, internal assessments may help industrial businesses fully identify the threats involved with the business. Supply chains of manufacturers are extremely diverse and constantly subjected to a range of threats, both within and beyond their supply chains.
Macroeconomic threats emerge from global stresses, legislative criteria, environmental/social concerns and problems confronting emerging markets. Resilient risk management tools enable manufacturers to balance risks and expenses to avoid or rebound efficiently from a variety of complex and intermittent risk-related disturbances.
North America Risk Analytics Market, 2016-2027 (USD Billion)
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Geographically, the risk analytics market is widespread across five major regions, namely North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. They are further categorized into countries.
North America is projected to hold the largest market share. The region's domination is attributed to the growing acceptance of risk governing technologies by industries. Organizations in the region are more leaned towards reshaping their existing risk strategies to eliminate risks and redundancies. For example, banks and financial firms in the region are increasing their focus on managing cybersecurity risks in the wake of numerous cyber-attacks.
Advanced technologies such as robotic process automation (RPA), machine learning, and cognitive analysis are being adopted by analytics solution vendors in the region. With these technology integrations, companies are focusing on reshaping risk assessment models. Adoption of such technologies can help SMEs and large enterprises in the region to improve business efficiency by automatically testing a vast amount of unstructured data and identify potential risks and allow preventive actions.
With rising market uncertainty, companies in the region are focused on taking risk administration approaches that can help them identify the various types of threats that emerge from diverse international, economic, and technical factors. Besides this, risk management tools are allowing corporations to defend their firms from disruptions, and the extreme non-compliance actions taken by the government and various regulatory authorities in the country.
Asia Pacific (APAC) is an ideal environment for cybercriminals to prosper due to high internet access, less cybersecurity practices among businesses, rising cross-border data flows, and law enforcement. Rapidly rising networking and speeding the pace of digital transformation has made companies in the region adopt analytics solutions. Cyber vulnerability and data protection violations are rooted in the activities of the companies across all sectors in the country, rendering them susceptible to information threats irrespective of their cybersecurity initiatives. Losses from these attacks may often be major – including losses to damaged consumers, company interruptions, or harm to credibility.
Therefore, to overcome such challenges, businesses in the region are adopting risk assessment methods and solutions. The Asia Pacific region has a developed and well-established sector with an inclining trend towards technical advances, providing a variety of opportunities for risk management companies and service providers.
Moody's Analytics, Inc. Focusing on Enhancing Product Portfolio to Address Complex Risks
Moody's Analytics, Inc., business, and financial services company headquartered in New York, United States is one of the leading players that provides risk management solutions across various industry verticals. With its strong and diverse product portfolio and innovative application of advanced technology, the company has been able to strengthen its market position. It follows a holistic approach to growth strategy and aims to strengthen its innovation by ongoing product developments, technological acquisitions, alliances, and partnerships.
Key Players Focusing on Enhancing Product Efficiency
The key players in the risk analytics market are focusing on extending business opportunities by offering risk solutions. Key players are investing aggressively in research and development to expand their product range and create a world-class portfolio of emerging technology, software, and solutions through internal innovations and acquisitions.
Major players concentrate on delivering advanced and personalized risk management tools to clients, engaging in cloud-based technologies and processes, and penetrating the existing and adjacent markets.
The risk analytics market research offers qualitative and quantitative insights on risk management solutions and a detailed analysis of the market size & growth rate for all possible segments. Along with this, our market research provides an elaborative analysis of market dynamics, emerging trends, and competitive landscape.
Key insights provided in the report are the current trends, details about individual segments, recent industry developments such as mergers & acquisitions, consolidated SWOT analysis of key players, partnerships, Porter’s five forces analysis, and business strategies of leading market players, macro, and micro-economic indicators.
ATTRIBUTE | DETAILS |
Study Period | 2016-2027 |
Base Year | 2019 |
Forecast Period | 2020-2027 |
Historical Period | 2016-2018 |
Unit | Value (USD billion) |
By Component |
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By Risk Type Application |
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By Deployment |
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By Enterprise Size |
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By Industry |
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By Region |
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As per our study, the global market is predicted to reach USD 54.95 billion by 2027 with a CAGR of 12.2% (2020 -2027).
Banking, financial services and insurance (BFSI) is the leading adoption area for the risk analytics solutions.
In 2019, the global market was USD 22.18 billion and it is anticipated to reach USD 54.95 billion by 2027, reflecting a CAGR of 12.2% during the forecast period from 2020 to 2027.
In the global market, the software is the leading segment
Need for a unified platform that enables risk managers and companies to assess, calculate, and even forecast risk is the prime driving factor of the market
Some of the key players are SES SAP SE, Oracle Corporation, IBM Corporation, Moodys Analytics, Inc., and Verisk Analytics, Inc.
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