Adaptive Identity Risk Engine for MOSIP

Inspiration

As Southern Africa accelerates digital transformation across government portals, banking platforms, healthcare systems, and other online services, digital identity authentication has become a critical infrastructure layer. However, authentication endpoints are increasingly targeted through stolen OTPs, leaked credentials, SIM swap fraud, and automated credential stuffing. Most digital identity systems rely on static authentication rules that do not adapt to contextual risk. We were inspired to strengthen this weak point in digital public infrastructure by introducing adaptive, intelligence-driven authentication into MOSIP-based systems. Rather than replacing identity systems, we sought to enhance them with a risk-aware security layer.

What it does

Our solution adds an intelligent security layer to MOSIP-based digital identity systems. Instead of treating every login attempt the same, it evaluates the context of each authentication request and determines how risky it is in real time. When someone tries to log in to an online service, whether it’s a government portal, banking platform, or healthcare system the system looks at factors such as the device being used, the login location, the time of access, whether previous attempts failed, and the authentication method used (OTP, biometric, etc.). It then calculates a risk score based on this information. If the activity appears normal, access is granted seamlessly. If something looks unusual like repeated failed attempts, a new device, or suspicious login patterns the system can require additional verification such as biometric confirmation. If the risk is very high, the authentication request is blocked and flagged for review.