Competition information
UCF students are once again invited to collaborate with Addition Financial on a real-world analytics and machine learning project focused on Member Engagement—a vital area that shapes the long-term success of credit unions.
This project challenges students to explore behavioral, transactional, and demographic data to better understand how members interact with Addition Financial over time. The primary objective is to drive data-informed strategies that improve member retention, identify high-value segments, and personalize product recommendations that meet members’ evolving financial needs.
Rather than simply measuring performance metrics, students will take a strategic and predictive approach—leveraging machine learning models to uncover why certain members remain engaged, why others disengage or close their accounts, and how Addition Financial can proactively support member journeys. Their analysis will help uncover hidden trends and patterns, supporting more informed decision-making within the organization.
Students will gain hands-on experience in applying machine learning models with real business relevance, developing practical skills in segmentation, predictive analytics, and model interpretability. They will also refine their ability to visualize and communicate complex findings clearly to both technical and non-technical stakeholders.
Throughout the project, students will receive guidance from Addition Financial analysts, constructive feedback from faculty mentors, and the opportunity to present their final insights to industry leaders. These insights will help inform strategic planning and product development efforts, furthering Addition Financial’s mission to empower its members through trust, financial literacy, and personalized service.
Ultimately, this unique partnership offers students a powerful opportunity to work at the intersection of data science and financial services—while helping Addition Financial strengthen its impact across the diverse communities it serves throughout Florida.
Problem Statement
Addition Financial, with its mission to empower the financial well-being of its members, seeks to better understand the behaviors, characteristics, and engagement patterns that influence member loyalty, satisfaction, and retention. Member engagement plays a vital role in the growth and sustainability of credit unions and understanding how members interact with their financial institution is critical to designing personalized services and improving long-term relationships.
This project challenges students to analyze a wide range of member data—including transactional behavior, product usage, service interactions, and demographic profiles—to uncover the key factors that drive engagement. By identifying what keeps members actively involved, what causes disengagement, and which members are likely to close their accounts, Addition Financial can enhance its ability to deliver proactive support and timely product offerings.
The core challenge lies in developing a data-driven framework to segment members by engagement level, predicting future behaviors, and recommend tailored interventions that increase member lifetime value. This analytical approach will empower Addition Financial to strengthen relationships with existing members, reduce attrition, and improve its strategic member outreach and service delivery.
Through this initiative, Addition Financial aims to create a deeper, more meaningful understanding of its members—helping to fulfill its broader mission of financial empowerment, community impact, and personalized member care.
Dataset
Participants will be provided with a rich, multi-dimensional dataset compiled by Addition Financial, containing a wide range of anonymized member information. The dataset includes transactional behavior, product usage, service interactions, and demographic profiles. These data points reflect real-world member activity and are designed to support exploratory analysis, segmentation, and predictive modeling.
To ensure clarity and consistency in interpretation, students will also be provided with publicly available data dictionaries that define each field in the dataset. Familiarity with the data dictionary is essential, as many of the fields are specific tothe financial services industry and require contextual understanding.
Using these datasets, participants are expected to conduct thoughtful and rigorous analysis to uncover patterns, behaviors, and trends that influence member engagement and retention. The ability to interpret the data accurately and communicate insights effectively will be a critical part of this project—empowering Addition
Contest Structure
This year, the contest structure introduces a more flexible and experience-driven format, empowering students to personalize their learning journey while solving real-world business challenges centered around Member Engagement.
Participants will explore a robust dataset that captures transactional activity, product usage, service interactions, and demographic details. The goal is to uncover meaningful patterns that influence member behavior—focusing on impact evaluation, segmentation, and predictive modeling. Rather than following a fixed-track assignment, students will choose from a set of focused use cases aligned with Addition Financial’s mission to enhance member relationships.
All student teams will be required to submit a written report detailing their approach, findings, and actionable recommendations. This report should demonstrate analytical rigor, technical skill, and storytelling ability—clearly connecting insights to strategic value for Addition Financial.
After reviewing all written submissions, Addition Financial will select the top three teams to deliver a live oral presentation of their project at AFCU Headquarters. These final presentations will offer students the opportunity to present directly to credit union leaders, receive professional feedback, and compete for the top award.
This structure encourages students to go beyond surface-level analysis and apply real-world problem-solving in an industry context—supported by clear data documentation and expert guidance along the way.
New for 2026-2027: Embracing AI-Driven Innovation
Recognizing the growing role of artificial intelligence in today’s business environment, students are encouraged to go beyond traditional analytical approaches and explore how machine learning, generative AI, explainable AI, and intelligent decision-support tools can strengthen member engagement strategies.
Participants may focus on one or combine multiple areas of exploration, including understanding member behavior, predicting disengagement, personalizing financial solutions, exploring AI-driven innovations, and translating insights into measurable business impact.
The emphasis is not simply on building the most accurate or sophisticated model, but on demonstrating creativity, responsible AI usage, analytical reasoning, and practical business value. Students should be prepared to explain not only what their models predict, but also why their findings matter and how Addition Financial could translate those insights into meaningful action.
This structure not only encourages creativity and strategic thinking but also reflects the realities of working in data analytics and financial services—where teams often decide which questions to pursue and how best to deliver meaningful insights to stakeholders.
All entries will be judged based on the following criteria:
- Content in the Project Report
- Modeling Approach
- Results and Conclusions
- Presentation of results
Project codes must be written in R, Python, or Microsoft SQL.
Code file types should be compatible with the software used:
(example: R file should be in “*.r” (.rmd preferred), Python in “*.py” (.ipynb preferred), Microsoft SQL file should be in “*.sql”).
**From all the submissions, only three finalist teams will be invited to formally present their findings to the AFCU competition judges at Addition Financial Headquarters, located at 1000 Primera Blvd., Lake Mary, FL 32746**
Judges will need to replicate the analysis using the team’s code/model on a validation dataset. Teams must provide formal instructions on how to run their model. Judging will be based on the application of the data, the method(s) used to reach conclusions, the number of significant relationships or correlations discovered, and the presentation of their findings.
It is crucial that contest participants communicate their findings in layman’s terms. Treat this assignment as if you were presenting it to a group of decision makers that may not have strong background in rigorous statistical analysis.
Important Dates
Contest start date: November 6th, 2026 @10:30 a.m. to 11:20 a.m. (tentative venue)
Final submissions due: January 15th, 2027, before 11:59pm (early submissions are encouraged)
Group presentations: February 15th, 2027 – February 19th, 2027
UCF Analytics Dept. notification of top one winner(s): March 1st, 2027
Annual UCF Data Symposium Presentation: March 2027 (tentative)
Prizes
AFCU is offering a worthy prize structure to incentivize participation: 1st Place: $5,000
UCF requires that prize funds be distributed through the UCF Foundation.
Questions & Contact Information
AFCU encourages students to contact us at any time with questions concerning the dataset. Please direct any questions you may have to:
Dept-BusinessIntelligence@additionfi.com
Competition Documentation & Final Submissions
To download competition instructions and rules please use the button below:
To submit final competition presentations no later than January 15th, 2027, before 11:59pm (early submissions are encouraged), please use this link: