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Use Cases regarding "Finances and Insurances"

Handwritten documents can be read out and prefilled using machine learning algorithms. By further input, these documents can be edited again, which again benefits the accuracy of the algorithm.

The optimum price of a building insurance can be determined by the customer specifying the address of a building, for example, and any existing pictures of the customer.

Neural networks are used to detect and filter out patterns of fraud cases. Conspicuous damage reports are reported to claim handlers and checked manually.

Standard documents can be classified and automatically completed using voice input and machine learning algorithms. This document can be checked and edited afterwards.

Companies receive dozens of invoices every day. Handling invoices and ensuring payment deadlines are met is a central task at every accounting division.

Machine learning algorithms allow standard clauses and deviations from the standard to be defined and identified on the basis of historical contracts. This makes it possible to highlight deviations and identify and categorize contracts according to predefined criteria.


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