Solutions We Provide

Client Engagement Prediction Modeling
We use spacial analysis and behavioral modeling to shape engagement strategies.
Dynamic Segmentation
Traditionally financial institutions only segment on income and expense. As financial behaviors are shifting towards the “gig-economy” with multiple income streams and diverse spending patterns, new approaches are needed.
Client Attrition Analytics
Do you know why your customers are leaving? Do you know why they’re not spending on your financial product any more? Using behavioral modeling through computational social science, new insights are extracted that be acted upon.
Financial Institutions Digital Intelligence
We assist financial institutions worldwide with their digital banking solutions by finding machine-intelligent ways to utilise data to improve digital channels & customer engagement.
Philosophy of Money and Wellbeing
Financial health is an important framework to consider because it is measurable and focused on impact.
Technology Modernization
Technology modernization processes include the use of agile approaches, devops, continuous delivery and full-stack technology understanding.

Reasons for Choosing Us

Full-stack Prediction

Service customer behaviors and expectations change, and organizations are becoming more digital. At the same time, lifestyles shift and the institution is not able to keep up. To move with these shifts in behavior, banks need state-of-the-art technology and expertise that can easily integrate into their organizations. ecosystem.Ai provides end-to-end client intelligence solutions that enable retail banks to provide a positive, practical and exciting customer experience.

  • ­Full-stack view of your prediction needs
  • ­Getting to automated solutions quickly

ecosystem.Ai shields the complexity of modern machine learning and artificial intelligence technologies. Our prediction products guide you through the process of producing predictors that can be deployed in days.

Latest Blogs

August 28, 2018

Prediction and the importance of continuous recalibration

Prediction is a key element of the work of Computational Social Science. Why? In a company environment, implementing actions based on accurate predictions creates opportunities for generating and maintaining competitive advantage.  It can become a key driver to propel you to success over your competitors. But before examining the value of Computation Social Science and

August 20, 2018

A view on how Computational Social Scientists see money in a digital world

The concept of money has evolved over centuries. Concurrently with this evolution, society’s psychological and social relationship to money has evolved from the original “philosophy of money.” Little did we know how things would change. Bartering is the exchange of items of perceived similar value, which was the main method of transacting before the progression

August 7, 2018

Computational Social Science: A shift from the abstract to the precise

If Social Science is the study of human society and the relationships between these people (using surveys and interview data, among other methods), what is Computational Social Science? Computational Social Science has the same intent as Social Science — understanding human society and relationships. But this field has shifted analysis and prediction from the abstract