Case Study

Transforming Customer Engagement with Data Science

A prominent retail loan and finance company with Systech Solutions, leveraged data science for a 10% cut in costs – a $1M game-changer! Discover how advanced analytics reshaped their strategy.. 

How AI-ML Driven Strategies Revolutionized a Leading Financial Provider’s Communication Approach?


A Prominent Financial Provider: Operating over 450 branches across 22 states in the USA, offering a range of financial services including personal, auto, and home loans.  


A renowned financial services provider embarked on an innovative journey to enhance their customer communication strategy. Faced with the challenge of engaging customers across diverse channels, they partnered with Systech Solutions to leverage cutting-edge data frameworks and data science methodologies. The initiative aimed to unify customer interaction data from various platforms and utilize data science for deeper insights into customer communication preferences. 


The primary challenge was to develop machine learning models to identify the most effective communication channels for customer engagement, focusing on payment reminders and marketing communications. Key objectives included determining the optimal communication channel for each customer, tailored to specific intents, identifying the best timing for customer outreach, and calculating a propensity score for each communication channel per customer to prioritize effectiveness. 


In collaboration with Systech Solutions, the financial provider developed the ‘Propensity ML Model’, a comprehensive suite of machine learning models, each tailored to different communication types and channels. These models generated propensity scores, indicating the likelihood of a customer responding positively to specific communication channels, depending on the intent. Success was measured by customer reactions such as making timely payments or showing interest in additional services. 


The solution implementation focused on comparing propensity scores across different channels for each customer and intent type, selecting the highest-scoring channel for customer outreach. Business value was measured in terms of response probability per channel, optimizing outreach efficiency and costs. 


This strategic implementation enabled the financial provider to optimize their customer communication resources significantly. They achieved a nearly 10% reduction in communication costs, translating to an approximate savings of $1 million. This approach provided a competitive advantage in customer engagement efficiency and resource allocation. 


Moving forward, the Leading Financial Provider is looking to refine its customer engagement strategy by enhancing the Propensity ML Model with sophisticated multi-channel attribution analysis and integrating Customer Lifetime Value (CLV) metrics for more targeted marketing and service offerings. The shift towards advanced customer segmentation using unsupervised clustering techniques, will enable more personalized and effective communication tailored to the unique needs and preferences of diverse customer groups. 

Interested in seeing the transformative results delivered by AI/ML solutions? Visit our AI-driven analytics page to explore how we have revolutionized businesses with our AI/ML solution framework. Let us show you how we can make your business proactive in seizing opportunities and staying ahead in the competitive landscape.