The credit African SMEs deserve.
TrustScore assesses SME creditworthiness from their mobile money transactions — MTN MoMo, Orange Money — not their collateral. An objective, fair and transparent score that unlocks credit access, including for the informal sector and women entrepreneurs.
$8.7 billion of credit wrongly denied in Cameroon
In Cameroon and the CEMAC region, SMEs — especially women-led ones — are seen as 'high risk'. Yet this is not a bankability problem, but a perception gap.
No formal collateral
60–70% of women-led SMEs operate without a trade register or real-estate collateral — automatically excluded from traditional credit.
Ignored data
Mobile money transactions, tontines, bill payments: a wealth of real financial data, never valued by banks.
Gender bias
Lending processes reproduce systemic biases that unfairly penalize women entrepreneurs, despite a genuinely low risk.
TrustScore — scoring built for Africa
A scoring engine designed for African realities: native mobile data, built-in gender fairness and full transparency.
Native mobile money
Integration underway with MTN MoMo and Orange Money, with the customer's consent. TrustScore rates SMEs even without a formal bank account — from their real financial activity.
Gender fairness
Algorithmic fairness module (IBM AIF360) that detects and removes gender bias. Independent quarterly audit ensures fair scoring.
Transparency & formalization
Every score is explained (SHAP/XAI). A formalization journey guides informal SMEs toward bankability.
From mobile data to credit — in 3 steps
A simple, fast and secure process. Result in under 2 seconds.
Consent & data
The SME shares its MoMo data via explicit consent. No data without agreement.
Real-time AI analysis
TrustScore analyzes 39 alternative variables in under 2 seconds — GradientBoosting, 300 estimators.
Score + fairness report
The bank receives a 0–100 score with full SHAP explanation and a certified fairness report.
Simulate your TrustScore
Enter data representative of your business to estimate your alternative credit score.
Illustrative simulator — synthetic data. The real score uses 39 variables and requires your explicit consent.
Explainable AI, built for francophone Africa
TrustScore (prototype) is powered by an AI model trained on 10,000 reference records, currently in field validation, able to rate an SME within seconds from its mobile money data. Built in Canada by a team from the African diaspora.
Aligned with the AFAWA initiative
TrustLayer Africa supports the economic empowerment of women entrepreneurs, in line with the African Development Bank's AFAWA program.
What TrustScore will make possible
A diaspora fintech, for Africa
TrustLayer is driven by a Cameroonian-born founder, combining Canadian technical expertise and direct knowledge of the African field.
Patrick Martin KENFACK
Cameroonian-born software architect holding a Master's degree in web technology (2011) and 15+ years of experience in information technology (Hydro-Québec, CGI, Devoteam). Based in Canada, he maintains close ties with the African entrepreneurial fabric.
He designed TrustScore precisely to solve the paradox documented by AFAWA: financially sound SMEs perceived as risky for lack of suitable measurement tools. A solution built BY the diaspora, FOR Africa.
Areas of expertise
A partnership approach
TrustLayer Africa builds partnerships with local financial institutions, development programs (AFAWA / AfDB) and mobile money operators to deploy scoring at scale for the benefit of SMEs.
Let's build financial inclusion together
Financial institutions, development programs, mobile money operators: join the TrustLayer Africa ecosystem.
Become a pilot partner
We are seeking financial institutions and development partners to deploy gender-sensitive scoring in Cameroon and the CEMAC region.
Discuss a partnership →Let's talk about your project
SME, financial institution or development partner? Write to us and we'll get back to you quickly.