About EBL Marhaba
EBL Marhaba is an AI-powered loan-syndication platform that streamlines borrower data and coordinates collaborative workflows across banking partners. It replaces slow, document-heavy, multi-party processes with a single connected system for structuring and processing syndicated loans. Built for banks and their partners, it accelerates deals that traditionally stall on coordination.
Industry · Fintech / Banking
The problem we set out to solve
Loan syndication is a coordination problem as much as a credit one: a single deal pulls in multiple banking partners, each with their own data, review steps and sign-offs, and the whole process moves at the speed of its slowest handoff. Borrower information is duplicated, reconciled and re-keyed across institutions, while collaborative workflows run over email and spreadsheets that offer no shared source of truth. The result is a process measured in weeks, where delays cost participants money and strain relationships between partners. Scaling volume only compounds the friction, because every additional partner and every additional deal multiplies the coordination overhead — which is exactly why syndicated lending has been so resistant to the digitization that transformed other parts of banking.
How we built it
Centralize borrower data
We built a single, structured store for borrower information so every participating bank works from the same data. This eliminates the re-keying and reconciliation that slow syndication down.
Digitize collaborative workflows
We replaced email-and-spreadsheet coordination with shared, structured workflows across banking partners. Every step, review and approval happens in one system with a clear audit trail.
Apply AI to streamline processing
We used AI to organize and process borrower data and surface what each partner needs to review, cutting the manual effort in multi-party deals. Coordination overhead drops as the platform does the routing.
Engineer for speed and scale
We built the platform on a Next.js and Python stack with Redis for fast, responsive collaboration under load. It keeps multi-party workflows snappy even as deal volume and partner count grow.
Deploy on reliable cloud infrastructure
We containerized the platform with Docker and deployed on AWS with PostgreSQL for durable, dependable data. This gives partner banks the reliability that financial workflows demand.
Key capabilities
Centralized borrower data
A single structured record of borrower information shared across all participating banks.
Multi-partner collaboration
Shared workflows that coordinate reviews and approvals across every banking partner in a deal.
AI-streamlined processing
AI that organizes borrower data and routes review steps to accelerate multi-party processing.
Workflow tracking
Full visibility into where each deal stands and what each partner still owes.
Audit-ready records
A clear, structured trail of every step and sign-off across the syndication process.
Scalable cloud architecture
A Docker and AWS deployment that keeps performance steady as partners and deal volume grow.
Outcomes that moved the needle
EBL Marhaba has processed $500M+ in loans across 15+ banking partners, cutting multi-party processing time by 70% versus the traditional syndication cycle. By centralizing borrower data and digitizing collaboration across institutions, it turns syndication from a weeks-long coordination bottleneck into a fast, transparent, and scalable workflow.
