Data economy and data security are top priorities

Using state-of-the-art technology and machine learning, finAPI focuses on efficient data minimalism in the interest of the end user

For finAPI as one of the leading open banking providers in Germany with BaFin authorization, data economy and data security always come first. Of course, finAPI abides by the strict requirements of the General Data Protection Regulation (GDPR). In addition, finAPI requests only the data required for the respective use case from the bank or reduces the data passed on to B2B customers to the required minimum by means of the finAPI outgoing data filter. This ensures that only the absolutely necessary data is processed. 

How does this outgoing data filter work?

finAPI discusses with the B2B customer which use case (e.g. proof of creditworthiness, age legitimation, identification, etc.) is required and which specific data is needed for this. This enables finAPI to process account data in a targeted and needs-oriented manner. If an end customer uses finAPI’s account information service, the account data is immediately categorized and filtered by the company’s own so-called RuleEngine, which has been reviewed as part of the TÜV certification. Only the relevant and necessary information is passed on to the customer, while all data that is not required is deleted immediately.

Machine learning and expert rules for maximum precision and security

The categorization of account transactions is based on a comprehensive set of rules that assigns specific labels to account transactions. To constantly ensure the quality and security of the outgoing data filter, finAPI relies on the Keyword Labeling Service (KLS) with more than 200 labels. Clearly predefined expert rules are used, which are verified and optimized by machine learning technologies.

The accuracy and quality of the labeling is continuously analyzed and improved manually and achieves an accuracy (correct assignment of account transactions) of up to 99 percent.
Sven Wackermann
Head of Product Management

Data economy with finAPI using the example of GiroCheck

A good example of how the outgoing data filter is used in practice is finAPI GiroCheck. Online stores use the GiroCheck, for example, as an alternative or supplement to the Schufa report to check the creditworthiness of their customers. finAPI checks four criteria that are crucial for e-commerce providers:

Through this targeted query, finAPI receives and processes only the minimum required information (in the sense of yes/no) and delivers this to the customer. All other information is automatically deleted immediately.

Identification with finAPI Giroident using a minimum of data

Another example of data economy is the product finAPI GiroIdent. This KYC (“Know Your Customer”) service enables companies in e-commerce to prove the age of their customers and identify individuals. This is necessary, for example, for age-related products or tax returns. Only the name of the account holder is retrieved and matched via the online banking login. Since no transactions are required for identification, no transaction data is retrieved. This reduces data access to a minimum and ensures the security and privacy of the end customer.

Questions about data economy and data security at finAPI?

Do you have any questions about our products or would you like to get more information about data economy and data security at finAPI?  Do not hesitate to contact us.

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