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In this utility case we can show the power of our extraction framework - a lady declares that her attended person has a different bank account number as indicated and askes to change it. In this case the aim was to automate the process. Therfore several data points (eg IBAN, effective date, account holder,...). Our AI detects the name entities, it understands the concept of custodianship and selects the right name for further processing. We also are able to interpret relative dates eg. "yesterday" or "with immediate effect".
Having set up the model for eg incomming faxes you could immediately use the same model also for your email inbox. Our solution is based on one knowledgebase and serves all channels with the same model.
In advance via fax: 0221 799658904
Admin.- / Customer-Nr:
Date: 01. September 2016
Custodianship Susanne Wagner
Attention: Please consider new bank account!!!
I am the custodian of Susanne Wagner. She receives a credit advice over EUR 142,67 as stated in the letter from 26.08.2016.
Unfortunately the indicated bank account is not the one of my attended person Susanne Wagner.
The correct bank details are:
IBAN: DE16 1604 0000 0571 4442 00
DEEPSEARCH automatically detects the proper solutions that apply to the situation. It weights the cases with probabilities and ranks them from highest to lowest. In the video shown the intent is properly identified:
Notification – Change Bank Account
Further the defined entities are identified and extracted:
3. Account holder name
4. Transaction type: refund