Is the proliferation of alternative data making credit bureaus extinct? Not quite…

The increase in alternative data driven by digitalization has been considered by some as a potential threat to traditional credit bureaus, reducing their data advantage and allowing new data players and decentralized models for data sharing. It was anticipated that these new data players could utilize both structured and unstructured data to assess creditworthiness, thus gaining a competitive edge. However, by covering underserved groups of new borrowers, alternative data can complement the $140 billion global credit bureau industry, which has a compounded annual growth rate of 13.6% and warehouses data for more than 10 billion loans on over 1 billion customers. That is, as long as there are efforts to promote financial literacy, to invest in digital infrastructure and to address concerns over data privacy.
 

Exponential increase in data generation

Digitalization of economic activities accelerated significantly during the COVID-19 pandemic, leading to an increase in the volume and variability of data sources.  Approximately 400 million terabytes of data are now generated daily as people engage with digital platforms such as mobile apps, banking apps, and ecommerce sites. 

Data generation is expected to continue increasing exponentially as mobile and internet penetration improve due advances in technology that reduce costs. According to GSMA’s The Mobile Economy 2024, the average cost of smart phones has declined by 40% over the past decade, with the cost of data falling by 39% (inflation adjusted) over the same period. Improved connectivity is also narrowing the rural and gender gap, with estimates indicating that, by the end of 2022, global mobile internet adoption by rural and women users reached 41% and 61%, respectively.

McKinsey Global Institute found that leveraging data could raise an economy’s credit-to-GDP ratio by 20 basis points in the U.S. and the EU. In India, the lift could be as much as 130 basis points, the equivalent of about $80–$90 billion in GDP by 2030.
 

Enter alternative data

Alternative data are defined as non-traditional data (other than credit history captured by credit bureaus) that can potentially provide a more comprehensive view of a customer. These vary by markets, mainly driven by what the credit bureaus collect. For example, rental and utility data are not considered as alternative data in some markets, while they considered as such in others.

Alternative data can help expand financial inclusion in segments often excluded from traditional credit systems; improve credit scoring accuracy; and promote innovation such as development of new financial products and services.

Using alternative data enhances the ability to identify and assess potential credit customers for underwriting purposes, particularly in evaluating borrowers with no credit history or with limited data, often referred to as “thin file” customers. Beyond augmenting thin files, alternative data can provide a better understanding of borrowers. For example, adding data sets from utility, telecom, and streaming service accounts  increased the credit scores of 2.5 million consumers in the U.S. by an average of 13 points, helping them access more than $1.7 billion in credit.

During the COVID-19 pandemic, integration of alternative data helped distinguish between “false bads” and “real bads.” Real-time alternative data enabled financial institutions to differentiate between good corporate borrowers unable to meet their obligations due to the pandemic and zombie firms unlikely to recover.
 

Understanding market changes due to the proliferation of alternative data¹

A recent publication by the International Committee on Credit Reporting (ICCR), The Use of Alternative Data in Credit Risk Assessment: Opportunities, Challenges, and Policy Recommendations (2024), assessed the evolving alternative data landscape. It emphasized that leveraging alternative data can significantly enhance access to credit for underserved individuals and micro, small, and medium enterprises (MSMEs). The report notes emerging models for utilizing alternative data, associated risks and opportunities, and how regulatory environments are adapting. It also highlights the importance of robust digital infrastructure and heightened digital literacy for ensuring equitable access and responsible use.
 

Key findings of the ICCR paper

• Various types of alternative data used for credit risk assessment include consumer financial behavior, lifestyle and habits, business operations, housing and utility management, economic activity, risk management, agriculture, market insights, and regulatory compliance.
• Financial institutions are integrating alternative data across the credit value chain, enhancing visibility and access for underserved populations, reducing credit losses, and improving approval rates and borrower retention.
• Collaboration between incumbent and innovative players is crucial for building scalable solutions to leverage alternative data. Emerging models include:
  
  
  • Incumbents building in-house capabilities to leverage alternative data effectively.
  • Credit bureaus integrating alternative data into their databases, such as rental, utility, subscription, and bioclimatic information, supported by legal frameworks.
  • Financial institutions partnering with emerging alternative scoring providers to collect and aggregate data from sources that banks may find harder to access directly due to compliance constraints. 
  • Credit bureaus acquiring or partnering with fintechs and alternative scoring providers to access data typically not available at credit bureau level.
  • Advancements in open frameworks (such as open banking, finance, and data) creating new ecosystems with new players and rules. Credit bureaus in markets with open frameworks are adapting or establishing new subsidiaries to participate in these ecosystems.
  • Tech companies leverage alternative data from their own platforms to develop direct-to-consumer and B2B solutions. Examples include agtechs and telcos providing value added services.
     
• While alternative data use presents opportunities, it also poses risks, such as potential biases leading to discriminatory outcomes. The paper notes digital literacy disparities, infrastructure gaps, and data privacy concerns as key challenges limiting the full potential of alternative data.
   

Policy Recommendations

To address the challenges and harness the benefits of alternative data, the following policy recommendations are proposed:

• Adopt Alternative Data for Credit Reporting: Encourage the use of alternative data in credit reporting to enhance the visibility and credit scoring of marginalized segments.
• Improve Data Availability and Accuracy: Governments should digitize public databases and make them accessible to credit reporting services.
• Support Infrastructure Development: Policymakers should facilitate the development of robust digital public infrastructure, including identity, payments, and data exchange systems.
• Promote Digital Literacy and Consumer Awareness: Implement literacy and awareness programs to ensure responsible use of alternative data and mitigate risks such as cyber threats and privacy breaches.
• Enable Cross-Border Data Exchanges: Foster international collaboration to support the responsible exchange of data across borders.
• Use Regulatory Innovation Platforms: Use innovation platforms, such as sandboxes, to test and validate the use of alternative data in credit assessments.

Policy considerations include incentivizing digitalization, digitizing government services, supporting infrastructure development, promoting digital literacy and consumer awareness, and encouraging cross-border collaboration.
 

Conclusion

Integrating alternative data into credit risk assessment holds significant promise for enhancing financial inclusion and innovation. However, realizing this potential requires addressing digital literacy disparities, infrastructure gaps, and data privacy concerns. By implementing the recommended policies, stakeholders can ensure the responsible and beneficial use of alternative data, paving the way for a more inclusive financial system.

Are credit bureaus becoming extinct due to the expansion of alternative data? The evidence suggests that while the proliferation of alternative data may open up a traditionally closed market, it is unlikely to result in the decline of credit bureaus. Reasons include:

• They have a head start, and regulations allow them to integrate alternative data, maintaining their critical role.
• They are adapting to remain relevant through acquisitions and strategic partnerships.
• A market infrastructure that houses data for underwriting and micro- and macroprudential purposes remains important, at least for now.

_{1. This work is supported by the Swiss State Secretariat for Economic affairs (SECO) under the IFC  Global Financial Infrastructure Program.}