The challenges of data modeling in the credit sector have intensified with the advancement of digital transformation. While greater data availability offers valuable opportunities, it also requires greater precision in the collection and processing of this information.
Irrelevant or inconsistent data can compromise models that should be netherlands mobile database decision-making tools. Notable obstacles include overcoming historical biases and the difficulty of integrating large volumes of data.
Based on an analysis carried out with our data science team, in this article we will look at some of the main challenges of data modeling in credit.
We will look at the complexities of working with transactional data and how creativity can transform obstacles into competitive advantages.
Find out the order of topics covered.