Small and medium enterprises (SMEs) and microbusinesses are the backbone of many emerging and developing markets, driving job creation and economic growth. Yet, access to affordable credit remains a significant challenge. Traditional credit scoring models, heavily reliant on financial history and collateral, often exclude these businesses, as they lack formal documentation or credit histories.
Alternative data is changing the game. By leveraging non-traditional data sources like behavioural analytics, psychometric assessments, and device metadata, lenders can develop more comprehensive and inclusive risk models. These data-driven approaches are bridging the gap for SMEs and enabling financial institutions to unlock a previously untapped market.
Alternative data refers to information not traditionally used by financial institutions to evaluate creditworthiness. It includes behavioural patterns, digital footprints, transaction histories, and more. Unlike traditional methods, which depend on credit scores and bank statements, alternative data explores the borrower’s broader financial and social behaviour.
SMEs and microbusinesses are the lifeblood of economic growth; however they need investment to thrive, but they often face the same tough due diligence as much larger businesses, leaving them excluded by conventional credit systems. Alternative data provides a means to assess their risk accurately, enabling lenders to extend credit where it was previously deemed too risky.
Lenders analyse various metrics to gauge creditworthiness. Behavioural analytics, such as spending patterns, and psychometric data reveal character traits like reliability and risk tolerance. Device metadata, such as mobile app usage or location patterns, provides real-time insights into a borrower’s habits.
These non-traditional metrics enhance predictive accuracy, helping lenders identify creditworthy borrowers more effectively. Case studies show that lenders using alternative data models experience reduced default rates and increased approval rates for previously excluded groups. Alternative data credit scores apply to working capital, unsecured term loans, credit cards, asset finance and more.
Psychometric assessments measure a borrower’s personality traits, such as honesty, risk appetite, and financial discipline. These tests can take different forms. At Begini, we offer a gamified user experience to ensure high completion rates while also maximising data collected to evaluate behaviours linked to creditworthiness.
Applications in Micro SME Lending:
Example: A fintech in Africa used psychometric testing to assess rural entrepreneurs, achieving a 30% reduction in defaults compared to traditional methods.
Device metadata refers to information captured from mobile phones, such as app usage patterns, geolocation, and even battery charging habits. These data points can indicate a borrower’s stability and financial reliability.
Benefits for SME Lending:
Privacy Considerations:
While metadata offers invaluable insights, it must be handled with strict compliance to data privacy regulations to build trust among borrowers. Begini’s device data solution does not collect any personally identifiable information and ensure privacy by design.
Non-traditional payment records, such as mobile money transactions or e-commerce activity, provide a detailed picture of cash flow.
Use in Credit Scoring:
Example: In Southeast Asia, some lenders rely on transaction histories from mobile wallets to evaluate micro-SME borrowers, significantly expanding financial inclusion.
Regular payments for utilities, rent, or phone bills serve as indicators of financial discipline and repayment ability.
Advantages in Emerging Markets:
Alternative data includes non-traditional information like psychometric assessments and transaction histories, used to assess creditworthiness for individuals and businesses lacking formal credit records.
Traditional models rely on collateral and financial history, which SMEs often lack, making alternative data essential for assessing their credit risk.
They evaluate psychological traits like reliability and risk tolerance, providing insights into the borrower’s willingness to repay loans.
Yes, if used responsibly with borrower consent and in compliance with privacy regulations, device metadata can enhance risk assessments. It gives the borrower control over their own data and the choice to use their data for services which are meaningful to them. Data should never be taken without users explained consent.
Yes, many fintech platforms offer scalable solutions tailored for small lenders, enabling cost-effective adoption.
Governments and regulators are establishing enabling frameworks that ensure data privacy, transparency, and ethical use of alternative data.
Summarising the impact of alternative data in SME lending
Alternative data is reshaping SME lending by addressing long-standing challenges in assessing credit risk. With tools like psychometric assessments, mobile device metadata, and payment histories, lenders can make more inclusive and accurate decisions.
Financial institutions that embrace these innovations are finding a competitive advantage in rapidly developing markets. Partnering with fintech providers, investing in data infrastructure, and adhering to ethical practices are crucial steps.
At Begini, we specialize in leveraging alternative data to empower lenders and expand financial inclusion. Reach out to learn how we can help transform your lending strategy.
SaaS technology that provide character-based credit scores for Banks, Micro Finance, Digital Lenders, Neo Banks, BNPL and Asset Financing.
