LENDING
Resolve Underperforming Lending Models
Actively improve model performance and decrease financial loss
Even though lending models aid high-stakes loan decisions in a highly regulated environment they are highly susceptible to performance challenges that can create undesirable outcomes. ML observability enables financial services companies deploying lending models to decrease the probability of default, accurately price their loans, and better manage overall business outcomes.
See how Arize can help you enable fast and actionable insights through segmenting poor-performing cohorts, surfacing a model’s most impactful features, and visualizing key metrics to maximize optimal model performance and quickly resolve issues before experiencing significant financial loss.
Identify drift between various environments and versions to manage loan-defaulting patterns and anomalous distribution behavior
Breakdown low performing segments by features to dig into which segment within each feature is underperforming
Easily visualize metrics with customized timeseries widgets to showcase metric fluctuations over time
