Shift builds real-time credit decisioning with machine learning on Azure Databricks
Shift, an Australian business finance company, used the Azure Databricks Data + AI Platform and Delta Lake to consolidate disparate bank transactional data and build proprietary in-house classification models, enabling real-time credit approvals, 24x faster time-to-market for new solutions, and 90% faster data processing.
Overview
Shift, an Australian business finance company, used the Azure Databricks Data + AI Platform and Delta Lake to consolidate disparate bank transactional data and build proprietary in-house classification models, enabling real-time credit approvals, 24x faster time-to-market for new solutions, and 90% faster data processing.
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Inspect the highlighted sourceThe challenge
Shift needed a consolidated view of bank transactional data from disparate sources, but transferring and processing the different data sources was slow, making it difficult to get a consolidated picture of customer insights; structuring and running ETL pipelines also required staff to stay past business hours.
The solution
Shift used the Azure Databricks Data + AI Platform and Delta Lake to centralize disparate data sources within a unified, scalable infrastructure, building back-end data pools overlaid with proprietary in-house classification models with machine learning capabilities to automate processing and enable real-time decisioning.
Reported business value
Shift achieved 24x faster time-to-market for new solutions, implemented real-time credit decisioning for certain customer segments, cut data processing time by 90%, and reduced model iteration and retraining to within two days.
Sources
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