iscore, Synapse Analytics to launch AI-powered credit decision platform
The platform will enable banking and non-banking financial institutions to automate credit assessments, improve accuracy, and accelerate loan approvals.
By combining traditional credit data with alternative data sources, it promises to shift the process from lengthy data gathering to real-time decision-making within seconds.
Officials from both companies said the collaboration aligns with Egypt’s financial inclusion strategy and will boost operational efficiency.
“This partnership reflects iscore’s ongoing commitment to innovation in financial technology and our dedication to delivering best-in-class digital solutions,” said Mohamed Korayem, CEO of iscore.
“Our collaboration with Synapse Analytics will help financial institutions increase efficiency, expand access to credit services for citizens, and support the broader vision of the CBE and the Financial Regulatory Authority to promote financial inclusion.”
The platform will feature a secure interface for making real-time credit decisions, supported by automated alerts and performance monitoring tools to reduce credit risk, improve collections, and extend services to underserved customer segments.
Ahmed Abaza, Co-founder and CEO of Synapse Analytics, described the project as a “turning point” in Egypt’s approach to credit assessment.
“iscore plays a pivotal role in the country’s financial data ecosystem, supporting the evaluation and monitoring of individuals, SMEs, and microenterprises,” said Abaza.
“This partnership marks a major step towards a smarter, tech-driven financial environment. It shows how modern AI tools can reshape credit policies, enhance risk modelling, and accelerate the evolution of financial services.”
Synapse Analytics' platform allows institutions to test, deploy, and continuously refine credit scoring models through real-time analytics.
The integration of AI is expected to streamline operations and widen access to finance in line with Egypt’s digital transformation goals.