BKT Bank x B2Metric Success Story

The roots of Banka Kombëtare Tregtare can be found on November 29th 1925, when the first branch was established in the oldest Albanian financial institution in Durres.

The largest and oldest bank in Albania, BKT, was founded in 1993 by Banka Tregtare Shqiptare and Banka Kombtare e Shqipris.

The privatization process of BKT was completed in 2000 and on June 30th 2009, Alk Holding became the sole shareholder of BKT.

Challenge Overview

Analyzing Vast Customer Data for Informed Decision-Making

To draw accurate predictions and insights from the sheer volume and diversity of data, including customer demographics and bank account information, a meticulous approach is required. Identifying patterns and trends that can guide strategic decision-making requires thorough investigation.

Complexities in Predictive Analytics

Predictive analytics is complex when big banking data is involved. It is difficult to extract meaningful information from such a vast dataset, ensuring accurate predictions based on customer behavior, financial patterns, and demographics. It is often difficult to navigate the complexities of predictive modeling using traditional methods of analysis.

Inability to Define Different Types of Churn

One of the main problems is that BKT Bank needs different definitions of churn, but they were having difficulty interpreting the big banking data effectively. To accommodate different churn definitions, there was a need for different predictive models.

The Solution: B2Metric Predictive Analytics

Customer Churn Prediction

Using a variety of machine learning models, BKT Bank developed a comprehensive solution to predict customer churn. Customer data was carefully examined to ensure a robust approach to prediction. Several rigorous validations of the model were conducted, guaranteeing high accuracy and reliability.

Adaptive Learning

Using an adaptive learning approach, the model remained continuously up-to-date as new data accumulated, ensuring that predictions of customer churn were accurate regardless of changes to data or customer behavior.

Customer Micro-Segmentation

Aktif Bank's marketing and growth teams were empowered by B2Metric customer micro-segmentation, which was meticulously crafted by our solution. Detailed reports provided invaluable insights into each micro-customer segment, making it easy to analyze and optimize growing marketing budgets.

Optimizing Marketing Budgets

Through the use of micro customer segments, Aktif Bank was able to optimize marketing budgets and achieve customer satisfaction and loyalty through targeted marketing strategies.

Data Preparation and Detailed Analysis

The NPL scoring model was meticulously cleaned from dirty data from past loan applications, ensuring accuracy and reliability. A detailed analysis of customer information collected during loan applications further refined the predictive capabilities of the model.

Benefits

27% Customer Churn Reduction

By leveraging the insights gained from accurate B2Metric ML-Based churn predictions, BKT Bank implemented proactive measures to reduce customer churn. The result was a notable 27% reduction in churn, showcasing the effectiveness of the preventative actions taken. BKT Bank can maintain customer relationships now as well as save substantial amounts of money due to this reduction.

Optimized Loan Application Approvals

With B2Metric NLP Scoring, the strategic use of past loan application data and demographic characteristics allowed the bank to optimize its loan approval process, ensuring resources were allocated efficiently.