Deconstructing The Data Dilemma In Banks: Banks Have A False Sense Of Having Data

Banks often find themselves with a false sense of data availability, believing they have enough data for loan portfolio analysis, decision-making, and machine learning models. In reality, much of this data is inaccessible or in a format incompatible with their systems. This issue is a critical roadblock to improved data-driven strategies and predictive analytics. To combat this, banks should use integrated data transformation tools to ensure data is in a tabular format and consistent over time. This will allow them to improve models without expending significant time and effort to retrieve additional data.