The credit risk assessment market size is expected to reach US$ 18.43 billion by 2030, from US$ 7.31 billion in 2023, at a CAGR of 14.1% during the forecast period.
Credit risk assessment involves analyzing credit data and financial statements to determine the level of risk associated with lending money to a particular entity. It helps lenders and financial institutions analyze creditworthiness, predict probabilities of default, and make informed lending decisions.
The key growth drivers of the market include the rising need for making real-time business decisions, increasing complexities in business processes, growing data and security breaches, and stringent industry regulations.
The credit risk assessment market is segmented by component, deployment model, organization size, vertical, technology, and region. By component, the market is segmented into software and services. The software segment accounts for the largest market share as AI and ML-enabled software solutions are gaining rapid traction for credit risk analysis. Software solutions enhance risk management capabilities and provide predictive insights
Credit Risk Assessment Market Regional Insights
- North America is expected to be the largest market for credit risk assessment during the forecast period, accounting for over 35% of the market share in 2023. The growth of the market in North America is attributed to the early adoption of advanced technologies, the presence of major players, and stringent regulatory compliances.
- Europe is expected to be the second-largest market for credit risk assessment, accounting for over 25% of the market share in 2023. The growth is attributed to increasing focus on operational efficiency and risk management across financial institutions.
- Asia Pacific is expected to be the fastest-growing market for credit risk assessment, with a CAGR of over 17% during the forecast period. The growth is attributed to growing credit lending activities, digital transformation initiatives, and favorable government policies in the region.
Figure 1. Global Credit Risk Assessment Market Share (%), by Region, 2023
Analyst’s Viewpoint: The global credit risk assessment market is expected to experience steady growth in the coming years. North America will continue to dominate due to stringent regulations regarding risk management. However, Asia Pacific is likely to be the fastest-growing region supported by the rapid expansion of the financial services industry in major economies like China and India. Some of the key drivers for this market include the growing demand for advanced analytics and real-time risk monitoring solutions from banks and financial institutions. Additionally, rising instances of fraudulent activities and the digitalization of financial services will compel organizations to invest in robust risk assessment platforms. Stringent regulatory compliance for assessing counterparty risks will further escalate adoption.
Credit Risk Assessment Market Drivers
- Increased application of big data and analytics: The growing adoption of big data analytics across lending and credit evaluation is a key factor supplementing the adoption of credit risk assessment solutions. Integration of alternative data from sources such as payments, social media, and e-commerce along with traditional credit data enables a deeper evaluation of creditworthiness. Furthermore, technologies like AI, ML, and NLP allow to analyze massive, complex data to build predictive models that can derive actionable insights to make informed lending decisions.
- As reported by the World Bank, in 2022, inclusion of alternative data led to 20-30% increase in approval rates for the credit invisible in Mexico during 2020-2021.
- High volumes of credit lending: The continuous growth in volumes of credit lending across consumer financing, small business loans, and mortgages is creating the need for banks and other lending institutions to deploy robust, scalable risk assessment frameworks. This is driving the demand for on-demand, flexible cloud-based solutions that allow to efficiently handle and analyze large, dynamic volumes of credit data for accurate evaluation of risk profiles. The deployment of such solutions helps achieve faster processing and underwriting of loans while preventing losses and maintaining portfolio quality.
- According to a report by the World Bank in 2022, overall debt levels of households globally had risen to nearly 34% of GDP, demonstrating huge growth in personal loans over the past 5 years alone.
Credit Risk Assessment Market Opportunities
- Cloud-based delivery models: The demand for on-demand, scalable cloud-based credit risk assessment solutions is rising rapidly. Cloud models allow faster deployment, flexible scaling, and regular upgrades and help improve operational efficiency. Financial institutions of all sizes are migrating risk management systems to the cloud to achieve enhanced performance and accessibility and expand credit access by reducing latency in decision-making. This provides significant expansion opportunities for cloud-native solutions. According to IDC, in 2022, the cloud services experienced a robust 22.9% year-over-year growth, with an even stronger revenue expansion of 28.8% observed in the foundational cloud services that underpin digital-first strategies.
- Expansion in developing economies: Developing economies offer untapped opportunities for growth owing to the large unbanked populations and underserved MSME sector with massive demand for formal credit. Financial inclusion initiatives in these economies are driving the need for agile, robust credit risk management platforms to serve consumers at scale. Furthermore, factors like the digitalization of lending and evolving regulatory policies are mandating improved risk control measures – creating substantial opportunities for the adoption of advanced credit assessment solutions. According to the Directorate General of Commercial Intelligence and Statistics, The proportion of MSME-specified products in India's total exports for the years 2020-21, 2021-22, and 2022-23 stood at 49.4%, 45.0%, and 43.6%, respectively.
Credit Risk Assessment Market Report Coverage
||Market Size in 2023:
||US$ 7.31 Bn
|Historical Data for:
||2018 to 2022
||2023 - 2030
|Forecast Period 2023 to 2030 CAGR:
||2030 Value Projection:
||US$ 18.43 Bn
- North America: U.S. and Canada
- Latin America: Brazil, Argentina, Mexico, and Rest of Latin America
- Europe: Germany, U.K., Spain, France, Italy, Russia, and Rest of Europe
- Asia Pacific: China, India, Japan, Australia, South Korea, ASEAN, and Rest of Asia Pacific
- Middle East & Africa: GCC Countries, Israel, South Africa, North Africa, Central Africa, and Rest of Middle East
- By Component: Software, Services
- By Deployment Model: On-premises, Cloud
- By Organization Size: Large Enterprises, SMEs
- By Vertical: BFSI, Telecom & IT, Healthcare, Government, Manufacturing, Retail, Others
- By Technology: AI & ML enabled Credit Risk Assessment, Traditional Credit Risk Assessment
Experian, Equifax, TransUnion, FICO, Moody's Analytics, Oracle, IBM, SAP, SAS Institute, Fiserv, Pegasystems, Genpact, ACL, Kroll, PRMIA, Riskonnect, Risk Spotter, Risk data, BRASS, Misys
- Increased application of big data and analytics
- High volumes of credit lending
|Restraints & Challenges:
- Data privacy and security concerns associated with cloud-based solutions
- Lack of skilled workforce across financial institutions
- High upfront costs involved in deployment of solutions
Credit Risk Assessment Market Trends
- Integration with automated decisioning platforms: Financial institutions are increasingly integrating credit risk assessment capabilities with automated decisioning platforms that allow straight-through processing for accelerated credit underwriting. This enables dynamic risk analysis and real-time decisions on credit approvals, pre-approvals, limit settings, etc. Solutions providers are partnering with decisioning platforms and leveraging technologies like AI/ML and APIs to deliver seamless integration. According to OECD, In 2022, A leading financial institution integrated an automated decisioning platform into their loan approval process. This resulted in a 50% reduction in decision time and a 20% increase in loan approvals.
- Hybrid and ensemble modeling: Driven by the need for greater predictive accuracy, the adoption of a hybrid modelling approach combining statistical techniques, machine learning, and deep learning is rising. Ensemble modeling utilizing the output of multiple models is also gaining prominence as it enhances predictive power and minimizes bias or overfitting compared to individual models. Providers are incorporating hybrid and ensemble modeling to strengthen risk assessment capabilities. According to the World Bank, In 2022, the adoption of alternative data and advanced analytics pushed financial inclusion to near universal levels in Brazil between 2011-2017, with the number of borrowers growing by over 50% during this period.
- Specialized solutions for evolving segments: Rising alternative lending segments like Buy Now Pay Later (BNPL) and supply chain finance are demanding tailored risk assessment capabilities specific to their needs. Solutions catering to specialized segments and unconventional data sources are gaining prominence. Customized platforms for small business lending and commercial credit evaluation are also witnessing increasing adoption. According to a 2022 report by the World Bank, the use of new alternative data and more dynamic modeling helped increase unique credit approvals in developing markets by 15% compared to traditional methods that relied mostly on credit scores and payment histories.
- Integration of non-traditional data: Analyzing non-financial alternative data derived from sources like social media, web, IoT, supply chains, etc. is gaining traction as it provides unique behavioral insights into creditworthiness uncaptured by traditional data. Advanced analytics applied to these new datasets allow a more holistic evaluation of risk. Solutions enabling the integration of non-traditional data see rapid adoption across lenders focused on financial inclusion.
Credit Risk Assessment Market Restraints
- Data privacy and security concerns: Growing instances of data breaches, cyberattacks and lack of control over consumer data in open banking create data privacy and security apprehensions that could restrain adoption. Financial institutions are cautious in deploying cloud-based solutions. Strict data regulations also limit the quality of data available for risk analysis. This requires significant investments in data security by providers.
- Counterbalance: In a credit risk assessment market facing data privacy and security concerns, implement data encryption techniques to protect sensitive data during transmission and storage. Conduct regular audits of your data security measures to identify potential vulnerabilities and address them promptly.
- High dependence on historical data: A major proportion of credit risk assessment still relies heavily on analysis of historical repayment behavior. This backward-looking approach has limitations in accurately evaluating the risk associated with new credit applicants with no prior credit history. Over-dependence on historical data also restricts the more predictive capabilities of advanced analytics.
- Counterbalance: In a credit risk assessment market with high dependence on historical data, there are several strategies, Diversification of Data Sources: Don't rely solely on historical data. Incorporate real-time data, predictive analytics, and forward-looking indicators into your credit risk assessment models.
- Integration complexities: Integrating AI/ML-based third-party credit risk solutions with existing legacy systems requires significant upfront investments. Seamless data transfer between systems while ensuring data integrity poses challenges. Lack of technical expertise in managing complex integrations often deters financial institutions from deploying advanced assessment solutions.
- Counterbalance: Standardize your data formats and processes to simplify integration. This can help to reduce errors and improve efficiency. Invest in integration technologies such as middleware, APIs, or integration platforms. These technologies can help to automate and streamline the integration process.
- In September 2022, Moody's Analytics,is a leading manufacturing of Moody's Corporation launched its new CreditLensTM credit lifecycle management solution to streamline and automate credit processes. It is designed to enhance risk analysis and decision-making
- In June 2021, Experian is a multinational data analytics and consumer credit reporting company launched its new FICO Risk Rating solution in collaboration with FICO to help lenders better identify credit risk. It uses trended credit data for precise risk assessment
- In April 2020, Equifax, a global data, analytics, and technology company partnered with Urjanet, is a driven by a diverse team that is dedicated to innovation to launch its new solution for assessing commercial credit risk using alternative data from utility payment records. It provides deeper insights into commercial lending decisions.
Key Strategic Initiatives
- In October 2021, Moody's Analytics acquired Pass Fort is a single, online platform and entered into a strategic partnership with KYC.com is to promote global transparency and make regulations to enhance its KYC and compliance capabilities for better credit risk assessment
- In April 2020, Equifax acquired Ansonia Credit Data is an American multinational consumer to expand its differentiated commercial credit data assets and analytical capabilities to provide robust risk intelligence on businesses
- In June 2019, FICO, is a leading analytics software company announced a new multi-year strategic alliance with Equifax to collaborate on product innovation and thought leadership to transform credit lifecycle management and risk management globally.
Figure 2. Global Credit Risk Assessment Market Share (%), by Vertical, 2023
Top Companies in Credit Risk Assessment Market
- Moody's Analytics
- SAS Institute
*Definition: The credit risk assessment market refers to the industry and solutions focused on enabling organizations to analyze credit risk associated with lending and credit activities. It involves evaluating credit data, financial statements, and other information to determine the creditworthiness of consumers and businesses. Credit risk assessment solutions leverage technologies like artificial intelligence and machine learning to build predictive models that can provide insights into probabilities of default and expected losses. These data-driven insights help lenders make better and faster credit decisions, monitor risk proactively, and optimize their lending strategies. The market is driven by rising need for efficient credit evaluation, digitalization in lending, increasing complexities in credit portfolios, and focus on minimizing bad debts. It is seeing strong adoption across banks, credit unions, financial institutions and fintech lenders to modernize credit underwriting, improve loss forecasting, and drive profitable portfolio growth.
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