“FaMLy” — Empowering Families Through Smart Financial Recommendations
In the context of the FAME project, Sonae MC and Universo are driving innovation with Pilot 1, FaMLy – A powerful financial recommendation engine for families. Focused on families’ financial empowerment, the pilot is exploring new frontiers in financial services by leveraging AI and machine learning tools developed within FAME.
Our role has been to explore how data-driven technologies can transform customer engagement and product offerings. Using Universo’s extensive customer data ecosystem, Pilot 1 is creating two core use cases: a recommendation engine for families, and advanced consumer profiling for risk scoring.
The goal of Use Case 1 is to deliver tailored financial and partner offers to Universo clients by leveraging Machine Learning (ML) and Explainable AI (XAI) capabilities provided by the FAME platform and partners. The recommendation engine uses a wide range of data assets, including sociodemographic information, transactional history, and digital engagement patterns.
In Use Case 2, we focus on instalment risk management. By profiling customers through a blend of transaction data and behavioural insights, we aim to extend access to Universo Flex, the “Buy Now, Pay Later” solution, beyond conventional credit card users. Here, FAME’s AI/ML analytics and federation capabilities enable risk modelling with external data, opening opportunities for financial inclusion.
Key milestones include stakeholder workshops held in August 2024, where we gathered feedback from Customer Service and Data Science teams at Universo. Their insights helped fine-tune our approach, particularly around user engagement, compliance, and transparency — critical pillars for trust in digital financial services.
Looking ahead, our next steps focus on consolidating the foundations built so far. We plan to involve business stakeholders once again to validate the progress of the recommendation engine and risk model initiatives. In parallel, we will start exploring the capabilities of the newly premiered FAME platform, identifying how it can further support our pilots’ objectives in terms of data sharing, AI training, and federation. This exploratory phase will be crucial to shape the next developments and ensure that the final solutions are aligned with the project’s goals.
Author(s): Beatriz Vieira (R&D and Innovation Project Manager, MC Sonae) and Anabela Silva (Data Scientist, Universo)
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