UAE-Based Synapse Analytics Raises $13 Million Series A for Financial AI

UAE-Based Synapse Analytics Raises $13 Million Series A for Financial AI

UAE-based Synapse Analytics has raised $13 million in Series A funding to expand its financial AI platform. The round was led by Partech, with Algebra Ventures and Silicon Badia also participating.

The latest investment takes Synapse Analytics’ total funding to $17 million. The company will use the new capital to accelerate product development, grow its team, and expand into international markets.

What Synapse Analytics Does

Founded in 2018 by Ahmed Abaza and Galal Elbeshbishy, Synapse Analytics started with a focus on AI and MLOps before moving deeper into financial risk and decisioning. Today, the company offers an agentic decisioning platform designed for banks, fintechs and other regulated financial institutions.

In practical terms, decisioning means helping financial institutions decide whether to approve, reject, flag or take another action on applications and customer activity. Synapse’s platform brings together AI models, business rules, customer data and risk policies in one system.

The platform also gives credit and risk teams more control over these decisions. Teams can build, test, update and deploy policies themselves without relying entirely on engineering teams for every change.

From Credit Scoring to Fraud and AML

Synapse Analytics is building its platform to cover multiple financial decisioning workflows, rather than focusing only on credit scoring. Its technology is designed to help financial institutions automate and manage decisions across lending, onboarding, fraud prevention, compliance and customer management.

Credit Decisioning

Synapse helps lenders assess customers and businesses before making credit decisions. Teams can combine customer data, AI models and their own risk policies to determine whether an application should be approved, declined or sent for further review.

Customer Onboarding

The platform supports onboarding by helping financial institutions process customer information and documents, apply verification rules and make decisions during the application process. This can help reduce manual work and speed up customer onboarding.

Fraud Detection

Synapse also applies AI and decisioning to fraud prevention. Financial institutions can use customer and transaction data to identify potentially suspicious activity and set rules for when a case should be flagged or reviewed.

Anti-Money Laundering

For AML workflows, the platform helps institutions apply risk policies and identify activity that may require investigation. This brings compliance decisions into the same decisioning environment used for other financial processes.

Portfolio Monitoring and Customer Management

Beyond the initial application, Synapse supports ongoing portfolio monitoring and customer segmentation. Financial institutions can use changing customer and risk data to update policies and make decisions after a customer has already been onboarded or approved.

Synapse’s Traction and Regional Expansion

Synapse Analytics works with banks, non-bank financial institutions, fintechs and telecom companies across the Middle East, Africa and Latin America. The company says its platform has supported more than $200 million in lending and processed more than 10 million applications.

The company lists financial institutions and lenders including Bank al Etihad, Raya, Aman, Souhoola and Forsa among its partners and customers. Its platform is currently deployed across markets including Egypt, Saudi Arabia, Jordan, Iraq and the UAE, while the company is also expanding across Latin America.

Synapse also reports that its technology has helped clients achieve up to a 40% reduction in non-performing loans. This is a company-reported figure and has not been independently verified.

Nicole Catapano, a proficient news writer, covers AI, tech gadgets, and software products with over 6 years of experience. Her knack for simplifying complex tech topics is honed by her education in computer science.

Leave a Comment

Professor Derpy's Notes

I have developed a highly advanced risk model. Whenever something is described as “low risk,” I immediately become interested in it.

Join our newsletter

email subscription

Receive Latest AI Insights To Your Inbox