Can You Score Credit Without Financial Data? Find Out How!

Missing and incomplete data is fast becoming a critical challenge for credit decisions across the Middle East and Africa (MEA). Rapid digitisation, rising credit demand, the push for financial inclusion, and economic instability are all accelerating the problem. 

This data gap has serious consequences for lenders, businesses, and individuals. High unbanked populations and the rapid rise of digital lending reflect just how widespread the issue has become. Traditional lending models are no longer sufficient. Addressing the gap will require stronger credit reporting, smarter use of alternative data, digital identity frameworks, and improved financial literacy. 

This piece delves into: 

• The cost of missing numbers in MEA credit decisions 
• Assessing company health beyond finance  
• What qualitative credit risk assessment entails in the MEA  
• How Cedar Rose supports qualitative credit risk assessment   
  
  

The Cost of Missing Numbers in MEA Credit Decisions 

The high cost of missing financial information significantly impacts small and medium enterprises (SMEs) in the Middle East and North Africa (MENA) region. These SMEs make up over 90% of all businesses and generate nearly 70% of formal jobs. Yet, they face an estimated credit gap of $250 billion. This gap is exacerbated by the lack of access to formal credit, as many SMEs are either too large for microfinance or too small and high-risk for traditional banks. 

Weak credit infrastructure, limited reporting, and financial opacity prevent accurate risk assessment. As a result, banks raise interest rates, demand collateral, or decline loans, pushing SMEs toward expensive informal lending or reliance on internal funds. This restricts their ability to scale, innovate, and hire. Lenders, in turn, miss viable opportunities and face costly inefficiencies. 
 
At the macro level, this gap slows job creation, hinders productivity, and constrains economic diversification. The solution requires not just more lending, but smarter lending, grounded in better, more accessible data. 
 

Assessing Company Health Beyond Finances 

Since traditional financial data often struggles to accurately assess the creditworthiness of SMEs in the MEA region, alternative data offers a more comprehensive and inclusive approach to risk assessment. It also aligns with the G20 High Level Principles on Digital Financial Inclusion and encompasses information beyond standard financial statements and credit reports. 

Relevant types of alternative data for MEA SMEs include: 

• Digital Transaction and Payment History: Includes bank account activity, mobile money and e-commerce records, accounting software data, and payment behaviour with suppliers and customers.   
• Behavioural Insights and Public Records: Covers personality assessments, tax filings, court judgments, business registration details, and management demographics.  
• Supply Chain and Utility Data: Includes trade credit histories, supplier-buyer payment records, platform-sourced operational data, and utility/bill payment records. 

When used effectively, alternative data enables lenders to uncover patterns traditional financial statements often miss. Driven by AI and machine learning, advanced analytics convert complex datasets into practical intelligence for enhanced credit assessments. It exposes vital metrics like financial responsibility, operational health, business continuity, customer trust, and repayment capacity combining multiple sources creating a stronger, multi-dimensional risk profile.  

To What Extent Are MEA SMEs Adopting Alternative Data for Credit Risk Assessment? 

Across the MEA, alternative data adoption for SME lending varies by country and sector. 
The UAE and Saudi Arabia are leaders, driven by fintech and open data.  
 
UAE fintechs like LNDDO use varied digital data for collateral-free loans, while Saudi Arabia's Vision 2030 and Open Banking enable data sharing for enhanced risk assessment. Credit bureaus like SIMAH explore telecom/utility data for SME scoring, benefiting sectors from retail to construction. The UAE's ADGM revolutionary Numou lending platform further simplifies and optimises SME assessments. 

In more informal markets like Egypt and Jordan, fintechs such as MNT-Halan use mobile/transaction data for microloans. Egypt is also piloting utility data integration, while Jordan is using POS-based and cluster lending models for key sectors, with cautious regulatory support for financial inclusion. 

Meanwhile, South Africa, despite its mature financial sector, integrates alternative data into mainstream credit. TransUnion, a major South African credit bureau, incorporates mobile, asset registration, and geolocation data in SME scores, while fintechs use bank transaction data for cash-flow lending.  

What Qualitative Credit Risk Assessment Entails in the MEA  

Qualitative credit risk assessment in the MEA region evaluates borrowers, particularly SMEs, using non-financial factors such as management quality and market conditions, a necessity given the widespread scarcity of data.  

Lenders formalise this through qualitative credit scoring: weighting subjective factors to create a credit rating. Whilst the 5 Cs of Credit are a foundation, MEA lenders adapt them, placing greater emphasis on Character and Conditions, and often informally adding "Connections" due to the influence of networks. 

In practice, qualitative judgement can override formal scores. Doubts about a borrower's integrity can lead to loan rejection despite sound financials. Collateral and guarantees mitigate uncertainties in Capacity and Capital, whilst relationship management and short-term lending aid monitoring. External reports from agencies supplement internal assessments.  

Thus, in the MEA, Character and Collateral are prioritised in the adapted 5 Cs framework. Capacity and Capital are harder to assess, and Conditions like evaluating political instability/ market volatility are key. Credit risk assessment here blends formal analysis with local intuition. 

Variations in Qualitative Credit Assessment Across MEA Countries 

Credit risk assessment across the MEA region varies significantly. 
 
The UAE applies all 5 Cs, with particular emphasis on Capacity and Character while managing sector volatility. It leverages its credit bureau but also values qualitative insights, especially for private firms with limited credit histories, with Collateral remaining important for larger loans or where credit data is sparse. Saudi Arabia, guided by SAMA, prioritises Character and Capacity with robust KYC procedures; "name lending" remains influential, alongside rigorous SME assessments reflecting a trust-based lending culture.  
 
Lebanon’s ongoing economic crisis has made macroeconomic Conditions the dominant factor. In contracts, lenders in Egypt focus heavily on Capacity and Character, with state-owned banks often factoring in national policy goals alongside financial evaluation. 

Nigeria, through its centralised CRMS (Credit Risk Management System), prioritises Character and Capacity amid high economic risk, with Collateral frequently required from SMEs. Kenya places particular emphasis on Character and Collateral, increasingly adopting credit scoring and alternative data, although traditional relationship-based lending remains influential. South Africa’s mature credit system prioritises Character (credit history) and macroeconomic Conditions, using comprehensive credit data and mirroring international best practices. 
 

Table: MEA Region's Practical Application of the Traditional 5 Cs 

How Cedar Rose Supports Qualitative Credit Risk Assessment  

Cedar Rose supports qualitative corporate credit risk assessment by combining over 25 years of MEA expertise with advanced data intelligence.  

Our CRiS Intelligence platform unlocks one of the region’s premier corporate and legal entity databases, seamlessly integrating financials with critical qualitative insights and a proprietary CR Score. It delivers comprehensive firmographic profiles, ownership structures (UBOs), reputational analysis, and quick compliance screening, offering a comprehensive counterparty view beyond standard financial metrics. 

Our multilingual, culturally aware team interprets non-standardised registry data and conducts enhanced due diligence investigations to deliver critical operational insights. We strengthen the assessment of the 5 Cs through UBO tracing, business network analysis, reputational due diligence, and executive risk investigations.  

Contact us for more confident qualitative credit risk assessments.

Sources

1. https://www.middle-east.kearney.com/documents/d/middle-east/gcc-retail-banking-radar-2024-making-the-shift-from-resilience-to-regeneration 
2. https://www.smefinanceforum.org/post/fintech-platforms-disrupting-sme-finance#:~:text=Lnndo%2C%20digital%20lending%2C%20represented%20by,based  
3. https://www.fico.com/blogs/how-use-alternative-data-credit-risk-analytics  
4. https://iol.co.za/business-report/economy/2024-08-24-alternative-data-can-grow-sas-sme-sector/  
5. https://www.pwc.com/m1/en/services/assurance/manage-risk-in-business/implications-of-cbuae-credit-risk-management-regulations-guidelines.html#:~:text=The%20Central%20Bank%20of%20the,operational%20resilience%20within%20the%20LFIs 
6. https://rulebook.sama.gov.sa/en/55-credit-risk-measurement  
7. https://www.econjournals.com/index.php/irmm/article/download/17257/8345/40062#:~:text=study%2C%20there%20is%20a%20positive,to%20assess%20credit%20risk%20accuratel  
8. https://wijar.westcliff.edu/wp-content/uploads/2024/01/Ghazi-Andrews.pdf  
   
9. https://www.econjournals.com/index.php/ijefi/article/download/14482/7357