SAFIR
Financial Document Processing and Analysis Automation
It is an artificial intelligence application aimed at operational efficiency by recognizing customer instructions with wet signatures, which are frequently used in the banking sector, and extracting the information contained in them.
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Problems
Manual document processing burden
Information in customer instructions being entered into the Expert System manually.
Repetitive tasks
Similar information entry processes being repeated with different information.
Volume of documents in image format
Volume of documents with wet signature, which cannot be copied as text.
Solution
It eliminates repetitive workloads by automatically extracting information in customer instructions rather than manually entering them into expert systems, and speeds up the process.
It provides maximum extraction success in documents specific to the sector thanks to its deep learning models trained specifically for banking terminology and the Turkish character set.
It integrates with your existing systems thanks to database integration while maintaining data security with the ability to run on internal servers.
It minimizes reading errors even in difficult texts with low image quality or those described as "unclear" by utilizing past processing memory.
It eliminates repetitive workloads by automatically extracting information in customer instructions rather than manually entering them into expert systems, and speeds up the process.
It integrates with your existing systems thanks to database integration while maintaining data security with the ability to run on internal servers.
It provides maximum extraction success in documents specific to the sector thanks to its deep learning models trained specifically for banking terminology and the Turkish character set.
It minimizes reading errors even in difficult texts with low image quality or those described as "unclear" by utilizing past processing memory.
Model
Information extraction
OCR
History
