Omnisient, a South African-founded fintech and data analytics company, won the 'Best Technology Provider – Data, Analytics & Infrastructure' category at Britain's Credit Awards, an annual programme run by industry publisher Credit Strategy. The company was selected ahead of a shortlist that included Experian, a FTSE 100 credit-data company employing approximately 23,300 people across 32 countries, and SAS, a privately held analytics software firm with annual revenue exceeding $3 billion. Omnisient developed a secure, privacy-compliant method enabling credit lenders to access and analyze grocery retail data directly from retailers, using built-in AI to create predictive models determining individuals' risk profiles based on purchased products and shopping behavior without exposing consumers' personal details. The technology addresses a gap in credit systems that traditionally assess only consumers with existing credit records, offering an alternative creditworthiness indicator for individuals with little or no formal credit history through shopping behavior analysis.
Omnisient's method allows credit lenders to access and analyze grocery retail data directly from retailers. Lenders apply built-in AI to develop predictive models determining individuals' risk profiles based on purchased products and overall shopping behavior. Data never changes hands and consumers' personal details are never exposed during this process.
The analysis takes place on anonymized data within a secure and neutral environment. Personal information is never shared or accessible to third parties, including Omnisient itself. According to the company, shopping behavior — the contents of a household's grocery basket over time — serves as an alternative indicator of creditworthiness for consumers with little or no formal credit history.
Shopping data is described by the company as rich, universal (almost everyone shops for groceries regularly regardless of financial status), and fresh, updated every few days or weeks depending on individual shopping habits. Jon Jacobson, CEO and co-founder of Omnisient, stated: "Most credit systems can only assess people who already have a credit record. We set out to show that everyday data, used with strong privacy protections, can responsibly extend credit to people the system currently cannot see."
In South Africa, Omnisient's technology has been used to score more than 8 million consumers, of whom 3.2 million subsequently qualified for credit for the first time. The company reported that the approach improved the accuracy of participating lenders' risk models, as measured by the Gini coefficient, by 41%.
These figures relate to deployments with Omnisient's banking and retail partners and were provided by the company.
In 2025, TransUnion, one of the three largest global credit bureaus, acquired a minority stake in Omnisient and took a seat on its board. TransUnion later co-led a $12.5 million funding round for the company.
Omnisient stated it is using the investment to expand in markets including the United Kingdom, the United States, and Brazil.
What award did Omnisient win at Britain's Credit Awards?
Omnisient won the 'Best Technology Provider – Data, Analytics & Infrastructure' category at Britain's Credit Awards, an annual programme run by industry publisher Credit Strategy. The company was selected ahead of a shortlist that included Experian and SAS.
How does Omnisient's grocery data credit scoring technology work?
Omnisient's technology allows credit lenders to access and analyze grocery retail data directly from retailers using built-in AI to develop predictive models. The analysis determines individuals' risk profiles based on purchased products and shopping behavior. Data is analyzed in anonymized form within a secure environment, with personal information never shared or accessible to third parties, including Omnisient.
What results has Omnisient achieved in South Africa?
In South Africa, Omnisient's technology has been used to score more than 8 million consumers, of whom 3.2 million subsequently qualified for credit for the first time. The company reported that the approach improved participating lenders' risk model accuracy, as measured by the Gini coefficient, by 41%.
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