ROCKET
Financial Document Processing and Analysis Automation
It is an early warning system that uses machine learning methods to predict whether there will be any delays in loan payments 3 or 6 months in advance, before the due dates, by using both the payment behavior of commercial customers who have taken out loans from the Bank in the past and the commercial relationships and financial situation analyses extracted from financial documents.
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Problems
Manual risk analysis process
The process based on the knowledge of banking specialists being slow.
Non-automated risk management
Insufficient adaptation to rapidly changing economic conditions.
Solution
It conducts in-depth analysis of the credit risks of commercial customers using explainable artificial intelligence models that maintain the transparency of decision-making mechanisms.
It enables proactive measures to be taken before risks materialize, thanks to an early warning system that detects potential payment delays before the due date.
It increases operational speed by end-to-end automating manual and slow risk assessment processes.
It generates the most up-to-date and highly accurate forecasts with real-time data streams that can instantly adapt to changing economic conditions.
It conducts in-depth analysis of the credit risks of commercial customers using explainable artificial intelligence models that maintain the transparency of decision-making mechanisms.
It increases operational speed by end-to-end automating manual and slow risk assessment processes.
It enables proactive measures to be taken before risks materialize, thanks to an early warning system that detects potential payment delays before the due date.
It generates the most up-to-date and highly accurate forecasts with real-time data streams that can instantly adapt to changing economic conditions.
Efficiency
Forecast
Early Intervention
