Increase efficiency
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The tool-based preparation of data makes it possible to achieve regulatory certainty with optimal time efficiency. |
Efficient implementation of the requirements according to § 24c KWG
The conflicting demands of requests for information from the authorities authorised to make enquiries, internal and external audits, internal bank requirements for customer master data, partly manual data entry and heterogeneous system landscapes result in a high additional effort for operational units, compliance and auditing. Here, the necessity of effort- and cost-efficient control actions to check the data quality is of particular importance.
3x
The automated analysis of mass data (no random sampling) significantly increases the data quality and reduces the costs and efforts of the audit.
50+
The Data Cruncher 24c has already been used successfully many times. This gives you a meaningful benchmark comparison from us.
3 in 1
Various advantages within the framework of control actions and remediation projects of the compliance function as well as in the digital audit approach of the internal audit. By drawing conclusions from KYC data, you can achieve synergy effects, e.g. on the identification of beneficial owners.
The use of Data Cruncher 24c starts with the collection of framework and raw data and enables the analysis of detailed results and the derivation of concrete measures to increase data quality.
Before using Data Cruncher 24c, we usually conduct a scoping meeting to determine all relevant framework conditions. In this way, the data set to be analysed can be specifically adapted to your needs. Subsequently, we read the data sets into the Data Cruncher 24c.
Before using Data Cruncher 24c, we usually conduct a scoping meeting to determine all relevant framework conditions. In this way, the data set to be analysed can be specifically adapted to your needs. Subsequently, we read the data sets into the Data Cruncher 24c.
We provide an initial indication for the assessment of the procedure free of charge.
per reported data analysis