Traditional credit scoring systems often exclude billions of people in emerging markets who rely on cash, mobile money, or informal payment systems instead of formal banking. This creates a significant gap, preventing access to loans, housing, and other financial services despite many individuals being reliable bill payers. For example, in Mexico, only 16% of the population has a credit card, leaving the majority "credit invisible."
One way to address this gap is by developing a credit scoring system that uses non-traditional data points to assess creditworthiness. Instead of relying solely on credit card history, this system could analyze:
By aggregating this data (with user consent), the system could generate a "flex score" that reflects real-world financial behavior. Lenders, landlords, or employers could then access this score via an API, paying per check or through subscription plans.
This approach benefits multiple groups:
Data providers, such as telecom companies, could be incentivized through revenue-sharing or reduced customer churn, while lenders gain access to previously untapped markets.
A simple MVP could start by partnering with a single telecom provider to pilot scoring based on mobile payment history. Once validated, the system could expand to include utility companies and subscription services. Regional customization would be key—for example, mobile money transactions might carry more weight in Africa, while utility payments could be prioritized in India.
Compared to existing solutions like Experian Boost or Tala, this idea focuses on emerging markets where traditional data is scarce, offering a more inclusive and adaptable approach to financial inclusion.
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