The digital lending sector in India has undergone a remarkable transformation, enabling unprecedented access to credit for millions. Despite these strides, the challenge of market saturation and over-leverage among prime borrowers looms large. A significant opportunity lies with the new-to-credit (NTC) segment, yet traditional underwriting practices fall short of effectively serving this group. Mobilewalla’s innovative data offering for digital lenders, LendBetter, leverages smartphone device data as a source of AI -driven alternative insights into user behaviour. This approach not only promises to expand your reach to the NTC population but also to do so with a keen sense of responsibility towards privacy and regulatory compliance.
The Urgency of Diversification
As digital lending platforms increasingly vie for the attention of a limited pool of 'prime' users, the risk of borrower over-leverage escalates. This situation underscores the pressing need to diversify lending practices by including the NTC segment, thereby fostering a more inclusive and sustainable financial ecosystem.
As per the latest whitepaper from Experian titled “Charting new horizons for fintech-lending”, 64% Fintech customers in India have taken 10 or more personal loans., as compared to 37% customers of Private Lenders, clearly showing that Fintech lending market is showing signs of overheating. The same whitepaper also observes that higher leverage often results in subsequent delinquency, and urges the Fintech sector to discover green shoots in the underserved segments, and enhance risk models with new data sources.
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Innovating Underwriting with Device Data
Smartphones are an integral part of daily life, holding a wealth of data on user behaviour, preferences, and reliability. This information, ranging from app usage patterns to geolocation data, offers a unique window into an individual's financial behaviour and potential creditworthiness.
The application of artificial intelligence (AI) and machine learning (ML) techniques to smartphone data enables the extraction of meaningful insights from complex, unstructured data sets. These technologies facilitate the development of predictive models that accurately assess credit risk, even in the absence of traditional credit histories.
LendBetter data and features are driving promising results for 10+ digital lenders in India and South-East Asia, showcasing the potential to responsibly extend credit to the NTC segment. Following are a couple of examples of user behaviour modelled using device data points.
App Usage and Financial Discipline: Analysis of app usage patterns revealed correlations between the use of financial management apps and higher creditworthiness, enabling targeted offers to potentially responsible borrowers.
Geolocation Stability as a Trust Indicator: Stability in geolocation patterns was found to correlate with financial stability, providing a novel indicator for creditworthiness assessment.
Leveraging Smartphone Data: Learnings and Best Practices
Drawing from our experiences and industry best practices, we've identified several key learnings for effectively using mobile device data in credit underwriting:
Data Relevance and Quality: Not all data points are created equal. Prioritizing data that offers genuine insights into financial behaviour is crucial. Continuous validation of data relevance ensures the robustness of predictive models.
Model Transparency and Explainability: AI models should be transparent and their decisions explainable, to both users and regulators. This transparency builds trust and facilitates regulatory compliance.
Dynamic Model Updating: Consumer behaviours change, and so should your models. Regular updates and recalibrations ensure that predictive models remain accurate over time.
Ethical Considerations: Beyond legal compliance, ethical considerations should guide the use of smartphone data. This includes respecting user privacy beyond the letter of the law and avoiding bias in credit decision-making.
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Embracing the Future: Innovation with Integrity
The path forward for digital lending involves a delicate balance between innovation and responsibility. By harnessing smartphone data, Mobilewalla helps you unlock new avenues for financial inclusion, targeting the NTC segment with tailored, data-driven credit products. However, this journey must be undertaken with a steadfast commitment to privacy, compliance, and ethical practices, ensuring a sustainable future for digital lending in India.
Sample our clean & privacy-compliant data now, or contact our data experts to discuss how Mobilewalla LendBetter can help your digital lending business grow sustainably.
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