GDS Modellica
GDS Modellica, with many locations worldwide, is a decision software company, helping companies make better decisions in their daily business. For over 14 years we have helped thousands of lending institutions and diverse organizations around the globe to achieve higher growth while successfully managing risk. Rather than one size fits all solutions, our industry-specific risk management insights helps guide the development and implementation of solutions tailored to individual needs.

The company provides decisional software and analytics to manage risk, fight fraud and build profitable customer relationships. GDS Modellica solutions leverage cloud computing to maximize flexibility, speed deployment and reduce costs. Our solutions include predictive analytics, big data and decision management. GDS Modellica has clients in 30 countries including banks, insurers, retailers, credit card issuers and more.

Because we understand the importance of improving risk management practices and realizing a solid return on investment when deploying such important analytics and technology, GDS Modellica Decision Architecture application can be customized to deliver a complete solution or enhance your existing applications with the necessary elements. By being highly attentive of our client’s needs and leveraging our own industry-leading knowledge and experience, GDS Modellica can deliver exceptional value and an enhanced customer experience.

Example Customers


GDS Modellica has been working with both Santander and Santander Consumer Group for more than 13 years on the credit decision Management side with solutions on the cloud and on premise implemented in most of the geographies where the group operate as well as in Santander´s Digital Bank, Openbank in Spain. GDS Modellica technology, has been approved by Santander Group Technology and therefore complies with its corporate standards.

Recently, GDS Modellica’s High Performance Engines have been selected and successfully implemented as part of the Group Corporate solutions in more than 10 countries throughout the world.

GDS Modellica Suite has proven to be very stable, with excellent performance and response time and with little or no incident during the last 13 years of use within the Santander Group.


RenMoney MFB Limited is a consumer finance organization that focuses on the provision of simple money solutions for individuals. They specialize in applying class-leading analytics and expert risk and operations management to the business of retail lending in Africa. RenMoney operates in Nigeria under a Micro-Finance Banking license.

RenMoney signed an agreement with GDS in July 2015 for the provision of a Decision Engine for Origination hosted on Amazon cloud. RenMoney went live in September 2015 and the integration with Mambu, their core Banking platform, was smooth and successful. For RenMoney , going for  Cloud technology has resulted in a fast project execution and delivery, which was one of the main requirements.  They didn’t have to bother about technology procurement and installation thus concentrating their efforts on real business challenges and requirements. In the last two years their credit application volumes have increased significantly and they have recently decided to upgrade to a newer and richer version of Decision Engine. 

Integration with Mambu

GDS Modellica provides decision management solution that will help automate Mambu processes like credit decisions or customer management. Through a seamless integration between both platforms, clients will benefit from smarter decisions that will lead to improved customer service and operational efficiencies. Key benefits for clients are:

- Automate decision making
- Control of business rules and decision strategies
- Speed, accuracy and consistency across growing volumes
- Support for expanding and changing business and regulatory conditions
- Integration and scalability in existing infrastructure
- Consistent common platforms across multiple business units
- Flexibility to incorporate more sophisticated data sources in decisioning