A fictional story follows, but is the typical narrative for millions of under-served South Africans. Sarah is a twenty-something living in Johannesburg, working two jobs and sending financial support back to her parents in Limpopo every month. Like many in Joburg, she is paid cash in hand for her job in hospitality.
She hasn't missed a rent payment in three years, and yet when she's declined a personal loan to support her sister's tuition fees by her mainstream bank, she's confused and concerned. She’s made no mistakes regarding her economic equity; in fact, Sarah has excellent financial reliability. But she's never had a credit card, and she's never taken out a personal loan. What more could she do? Live on credit? Drive her family into a debt hole? Ignore financial responsibility altogether?
A little hyperbole here, granted. But this is a glimpse into the sometimes-absurd world of credit scoring, where credit reliability is decided not necessarily by your financial literacy and money management skills but by how well you’ve balanced debtors and creditors in the past.
South Africa’s leading short term loan provider Wonga Online is now asking the right question: what about the wider financial picture across all demographics of the country?
What follows are insights from Wonga’s leadership on the future of credit scoring to widen credit inclusivity across the nation.
The Tyranny of Credit Scoring 1.0
For decades, credit bureaus have acted with exclusivity; entry is denied unless you meet (what are for many people) unrealistic requirements. Yet credit history is needed for credit, a chicken-and-egg dilemma that much of South Africa faces. Due to bureaucratic barriers to entry, millions are systematically denied access to formal financial services.
Imagine this: a typical average Joe with a consistent monthly income who keeps up with all his bills is considered “riskier” than someone with three maxed-out credit cards because the first guy doesn't have the credit history to prove traditional good citizenship. But that second individual has gained that “good citizenship” irresponsibly, through indulgence in credit. This is the power of bureaucracy, rewarding excess and irresponsibility.
No wonder about 40% of South African adults cannot access formal credit markets because scoring 2.0 systems don’t come into play. Eighteen million people are financially invisible through conventional ‘ascriptive’ processes.
What the 1s and 0s Really Mean
Enter alternative data assessments, and Wonga, where digital short-term loan providers utilize methods that would drive traditional analysts crazy. Instead of assessing loans from the past nine months, Wonga assesses digital markers today.
Mobile money transfers tell interesting stories; digital wallet usage on its own, and especially when supplemented by frequency and consistent transaction values, shows better fiscal reliability than traditional means. Every company has the capacity for equity control from a standard bank but must use mobile avenues in South Africa. For example, a man who keeps his payment at R100 and doesn't overspend shows better fiscal responsibility than anything a traditional credit system can show.
Utilities become character references. A man who continually pays his electricity bill monthly is reliable at meeting expectations, access needs trump social expectations. Necessary expenses highlight a good citizen who balances limited resources.
Employment becomes more than yes/no. Through alternative data, Wonga can assess not just employment, but employment stability, consistent income, and employment patterns. A taxi driver who worked for three years for one company might not have pay stubs, but his employment would still be documented, and therefore assessable.
Your Smartphone Becomes ‘Sherlock Holmes’
The use of alternative data essentially turns one's smartphone into a digital fingerprint. Brett van Aswegen notes from Wonga's digitized approach: "As such, AI-based lending models make more accurate predictions of financial reliability based on these datasets than traditional credit scores."
People are figuratively fingerprinted based on how often their phone interacts with bank apps, their location presence, and their social interaction patterns. For example, if someone's GPS shows constant movement in a work–home pattern, that might acknowledge employment, even if formal verification is lacking.
The same goes for behavioural analytics. How does someone manage their money? Are balances checked? Are spending controls used on the app? These micro-behaviours become part of major predictive analyses that measure reliable financial stewardship.
Breaking Down (Digital) Barriers
It's less about the technology used to deliver such information than the philosophy that underwrites it. Traditional scoring systems have yet to adapt to modern realities, where traditional banking platforms remain the primary formal avenues. However, this is not true in South Africa, where informal systems, mobile platforms, community efforts, and digital payment tools help build equity assessments that banking would otherwise assess unfairly.
This approach recognizes multiple valid paths to responsible action. Credit reliability should not be assessed only on how well someone fits categories designed for banks, but on the fuller literacies of real-world responsibility.
In addition, socioeconomic disparities, compounded over time, have rendered some people “riskier” through no fault of their own. People from communities historically excluded by apartheid-era banking systems lack traditional credit histories precisely because they were denied access. Alternative data assessments empower them with mechanisms to demonstrate reliability instead of punishing them for circumstances beyond their control.
The Positive Feedback Loop
Alternative data assessments create positive feedback loops wherever responsible action can be measured. The unbanked get loans; they build payment histories; they access more banking options down the line. It’s step-by-step accessibility to financial inclusion, not a system that extracts resources from struggling communities.
Without formal credit markets, people turn to informal moneylenders (read: mashonisas/loan sharks) offering 30–50% monthly interest rates. Alternative data assessments empower individuals to secure loans through regulated systems, giving them opportunities that traditional credit scoring would have denied, often unfairly.
Technological assessments must still address privacy concerns, algorithmic bias, data equity, data protection, but at the end of the day, responsibility trumps 1.0 history every time.
Alternative data assessments give millions of vulnerable people a fighting chance to prove their credibility through real-world behaviour rather than limited historical metrics. No one should be punished for where they came from or rewarded simply for navigating a system designed to exclude others.
