Banking Solutions
Use Case:
Underwriting Origination
Culture and keeps Culture top of mind throughout the journey.
Enhancing the risk assessment of underwriting in commercial real estate with AI/ML powered business insights
Increase in Revenue & Profitability through enhanced credit decisioning, lower cost of acquisition, higher automation and better customer experience
Reduction in Credit-Loss using AI/ML models that better determine customers’ likelihood to default and provide crucial KPIs and enable data-driven decisions
Efficiency Gains using automated data extraction, data integration with a unified data source, case prioritization and compliant model development
01
Intelligent Data Extraction
Capture the relevant information from unstructured formats
02
Merge Data in Data Factory
Refine and merge rich internal and external (dark) data sources
03
Risk Assessment
Build risk rating models to assess PD1, LGD2 and EAD3
04
Automation of Portfolio Mgmt
Use Automated BI for continuous tracking and management of portfolio
Enhancement of existing internal data sources for advanced analytics requirements like statistical models, forecasting, and reliable reporting of KPIs
Digitize & streamline large volume of underwriting paperwork
Automate and integrate document and digital workflows
Optimize data insights and risk data driveranalysis
Rely on more accurate & real-time risk scorecards
Supplement inhouse data with external 3rd party data
Enhance credit rating and model monitoring with ongoing live data feed
Receive more precise risk predictions (PD, LGD & EAD)
Automate notifications and inform proactive mitigation strategy
Use Case:
Underwriting Origination
Culture and keeps Culture top of mind throughout the journey.
Enhancing the risk assessment of underwriting in commercial real estate with AI/ML powered business insights
Increase in Revenue & Profitability through enhanced credit decisioning, lower cost of acquisition, higher automation and better customer experience
Reduction in Credit-Loss using AI/ML models that better determine customers’ likelihood to default and provide crucial KPIs and enable data-driven decisions
Efficiency Gains using automated data extraction, data integration with a unified data source, case prioritization and compliant model development
01
Intelligent Data Extraction
Capture the relevant information from unstructured formats
02
Merge Data in Data Factory
Refine and merge rich internal and external (dark) data sources
03
Risk Assessment
Build risk rating models to assess PD1, LGD2 and EAD3
04
Automation of Portfolio Mgmt
Use Automated BI for continuous tracking and management of portfolio
Enhancement of existing internal data sources for advanced analytics requirements like statistical models, forecasting, and reliable reporting of KPIs
Digitize & streamline large volume of underwriting paperwork
Automate and integrate document and digital workflows
Optimize data insights and risk data driveranalysis
Rely on more accurate & real-time risk scorecards
Supplement inhouse data with external 3rd party data
Enhance credit rating and model monitoring with ongoing live data feed
Receive more precise risk predictions (PD, LGD & EAD)
Automate notifications and inform proactive mitigation strategy
Use Case:
Underwriting Origination
Culture and keeps Culture top of mind throughout the journey.
Enhancing the risk assessment of underwriting in commercial real estate with AI/ML powered business insights
Increase in Revenue & Profitability through enhanced credit decisioning, lower cost of acquisition, higher automation and better customer experience
Reduction in Credit-Loss using AI/ML models that better determine customers’ likelihood to default and provide crucial KPIs and enable data-driven decisions
Efficiency Gains using automated data extraction, data integration with a unified data source, case prioritization and compliant model development
01
Intelligent Data Extraction
Capture the relevant information from unstructured formats
02
Merge Data in Data Factory
Refine and merge rich internal and external (dark) data sources
03
Risk Assessment
Build risk rating models to assess PD1, LGD2 and EAD3
04
Automation of Portfolio Mgmt
Use Automated BI for continuous tracking and management of portfolio
Enhancement of existing internal data sources for advanced analytics requirements like statistical models, forecasting, and reliable reporting of KPIs
Digitize & streamline large volume of underwriting paperwork
Automate and integrate document and digital workflows
Optimize data insights and risk data driveranalysis
Rely on more accurate & real-time risk scorecards
Supplement inhouse data with external 3rd party data
Enhance credit rating and model monitoring with ongoing live data feed
Receive more precise risk predictions (PD, LGD & EAD)
Automate notifications and inform proactive mitigation strategy