Summary of Towards Financially Inclusive Credit Products Through Financial Time Series Clustering, by Tristan Bester et al.
Towards Financially Inclusive Credit Products Through Financial Time Series Clustering
by Tristan Bester, Benjamin Rosman
First submitted to arxiv on: 16 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computers and Society (cs.CY); Statistical Finance (q-fin.ST)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a solution to enhance financial inclusion by developing a novel time series clustering algorithm for understanding consumer financial behavior. The algorithm allows financial institutions to provide tailored products and services without relying on conventional credit scoring techniques, which can be restrictive. The authors aim to address the challenge of obtaining segment annotations from domain experts, enabling the use of time series classification models for customer segmentation based on transaction data. By clustering customers into homogeneous groups based on their spending behavior, the algorithm promotes financial inclusion and increases consumer spending, ultimately contributing to economic growth and investment opportunities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps make it easier for people to access important financial products and services. Right now, it’s hard for companies to understand how people spend their money without asking too many questions or using strict credit scores. The authors are working on a new way to group people into similar spending groups based on their transaction data. This will allow companies to offer personalized financial products that meet people’s needs without being too restrictive. It’s an important step towards making it easier for everyone to access the financial services they need. |
Keywords
* Artificial intelligence * Classification * Clustering * Time series
