Global AI For Risk Management Market 2023-2030 Size, Share, Growth Analysis, by Technology(Hardware, software) - Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional Footprints by MarketDigits

Industry : Information Technology | Pages : 176 Pages | Published On : Jul 2023

The Global Market for AI in Risk Management, which was valued at USD 8.9 billion in 2021, is expected to grow significantly. It is projected to reach USD 68.5 billion by 2030, with a Compound Annual Growth Rate (CAGR) of 11.3% during the forecast period from 2023 to 2030.
AI is gaining popularity in risk management due to its diverse applications such as ideation, data sourcing, model development, and monitoring. Its primary role in risk management is to identify regulatory and reputational risks within organizations. By leveraging existing frameworks and organizational values, AI conducts risk assessments and determines the necessary data to be collected and processed. Choosing the right datasets is crucial as it directly impacts the quality of results. Previous risk management practices can guide the selection process, ensuring suitability for AI model processing.

The adoption of AI in risk management provides several benefits, including threat analysis and management, risk reduction, fraud detection, and data classification. AI-powered engines, particularly those utilizing machine learning techniques, can analyze vast amounts of data from multiple sources to generate real-time prediction models. This capability enables risk managers and security teams to address risks promptly. Additionally, AI algorithms can evaluate unstructured data related to risky behaviors in organizational operations, identifying patterns from past incidents and using them as risk predictors.

However, there are challenges associated with processing large volumes of data and implementing specialized AI services. The cost of such infrastructure and services can be substantial, impacting the growth of the industry. Furthermore, data privacy and protection are significant concerns for the market. To address these concerns, companies uploading data to cloud services may require encryption, secure transit, mechanization, and obfuscation measures.

In summary, the global AI for risk management market is experiencing rapid growth, driven by its various applications and the benefits it offers in risk assessment and mitigation. However, cost considerations and data privacy issues must be carefully managed to ensure sustainable market expansion.

Global AI For Risk Management Market Segmental Analysis

The Global AI for Risk Management market is categorized based on offerings, verticals, technology, and regions. In terms of verticals, the market is segmented into BFSI, Retail, Government & Defense, Manufacturing, Enterprise, Healthcare, Automotive & Transportation, and Others. The Enterprise segment holds the largest market share in AI for Risk Management globally due to the numerous benefits it offers in enterprise risk management. Additionally, AI provides significant advantages across all industry verticals in risk management systems. For example, in the BFSI sector, AI enhances risk management by limiting data breaches, preventing cyber attacks, and strengthening security measures.

Regarding technology, the AI for Risk Management market is divided into Machine Learning, Natural Language Processing, Context-aware computing, and others. Machine Learning is a crucial driver of innovation and growth across all technology industries within the global AI risk management market. It is considered a game-changer in risk management practices. With the rapid adoption of deep learning across various sectors, machine learning technology is expected to experience substantial growth. Machine learning platforms are gaining popularity as they automate monitoring, detect outliers, and analyze the massive amounts of data generated by security technology. Many businesses worldwide are utilizing deep learning and machine learning capabilities to enhance their risk management protocols.

Furthermore, the market is segmented by offerings into Hardware, Services, and Software. In terms of regions, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.

In summary, the Global AI for Risk Management market is analyzed based on offerings, verticals, technology, and regions. The Enterprise segment dominates the market, and AI offers significant benefits across various industry verticals. Machine Learning plays a crucial role in driving innovation and growth, and its adoption is expected to rise. Moreover, businesses worldwide are leveraging machine learning and deep learning capabilities to enhance their risk management practices.

Global AI For Risk Management Market Regional Insights

Globally, North America holds the largest share in the AI For Risk Management market, with the presence of key market players like NVIDIA, Microsoft, and others being significant factors contributing to this growth.

Meanwhile, Asia Pacific is expected to experience the fastest growth during the forecast period. This can be attributed to the increasing adoption of AI in Risk Management technology by large organizations in the region, particularly in China and Japan. The Asia Pacific region has witnessed a doubling of data threats and cyberattacks in recent years. Furthermore, both established companies and startups are making substantial investments to offer affordable high data security services, thereby driving the demand for AI in Risk Management in this region.

Global AI For Risk Management Market Dynamics:

Swift Solutions Driving Market Growth:

Threat intelligence data plays a crucial role in providing information on attacker sources, indicator of compromise, behavioral trends related to cloud account use, and attacks on various types of cloud services. Machine learning can be employed to aggregate and analyze this data at scale, enabling likelihood and predictability models.


High Privacy Concerns Impeding Market Growth:

Startups and new entrants in the market may find it expensive to enable specialized AI services, even when utilizing cloud native services. Processing large amounts of data can be costly, and data privacy and protection are significant concerns associated with AI and machine intelligence.

Global AI For Risk Management Market Competitive Landscape

The forecast period anticipates a rise in competition within the global AI For Risk Management market due to the entrance of new players and an increase in the availability of software and services compatible with AI For Risk Management. Currently, the global market is dominated by a limited number of key players, but this is expected to change in the coming years as the number of providers offering their services in the global market grows.

Top Player’s Company Profiles

• Smart bridge
• Logic manager
• BizVibe
• Protecht
• Yodel Services
• MetricStream
• Navex Global
• Origami Risk
• Deltek
• Congruity360
• Enablon

Recent Developments

• Sphera, a prominent global provider of software, data, and consulting services for Environmental, Social, and Governance (ESG) performance and risk management, successfully finalized its planned acquisition of riskmethods in October 2022. riskmethods, a software company based in Munich, Germany, specializes in supply chain risk management (SCRM). This acquisition serves to strengthen Sphera's commitment to innovation and expansion in the field of ESG solutions. By leveraging artificial intelligence (AI), big data, and machine learning, riskmethods' Software as a Service (SaaS) solution enables the identification, analysis, and mitigation of various supply chain risks, including monitoring sustainability practices and ESG compliance within the supply chain.

• Blockchain is emerging as a noteworthy trend in the realm of comprehensive risk management solutions. Its secure data storage and transaction tracking capabilities make it well-suited for tracking risks and ensuring effective management. Additionally, the ethical considerations associated with AI usage, such as the potential for bias, have garnered increased attention in the field of risk management.


Table and Figures


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