TristanBester/berka_clustering

This repository contains the official implementation of "Towards Financially Inclusive Credit Products Through Financial Time Series Clustering", published in AAAI W5: AI in Finance for Social Impact. # Financial Time Series Clustering ## Overview This repository contains the official implementation of "Towards Financially Inclusive Credit Products Through Financial Time Series Clustering" by Tristan Bester and Benjamin Rosman, published in AAAI W5: AI in Finance for Social Impact. The project presents a novel time series clustering algorithm designed to help financial institutions understand consumer financial behavior through transaction data without relying on restrictive credit scoring techniques. This approach promotes financial inclusion by enabling institutions to create more tailored financial products based on actual spending behavior. ## Abstract Financial inclusion ensures that individuals have access to financial products and services that meet their needs. As a key contributing factor to economic growth and investment opportunity, financial inclusion increases consumer spending and consequently business development. It has been shown that institutions are more profitable when they provide marginalised social groups access to financial services. Customer segmentation based on consumer transaction data is a well-known strategy used to promote financial inclusion. While the required data is available to modern institutions, the challenge remains that segment annotations are usually difficult and/or expensive to obtain. This prevents the usage of time series classification models for customer segmentation based on domain expert knowledge. As a result, clustering is an attractive alternative to partition customers into homogeneous groups based on the spending behaviour encoded within their transaction data. In this paper, we present a solution to one of the key challenges preventing modern financial institutions from providing financially inclusive credit, savings and insurance products: the inability to understand consumer financial behaviour, and hence risk, without the introduction of restrictive conventional credit scoring techniques. We pres …