It is fascinating what international financial policymakers are doing, without any public discussion.

Large-scale analysis of financial transactions by DNB

Last year, top central bank executive Steven Maijoor (De Nederlandsche Bank, ‘DNB’, the Netherlands) already revealed that DNB is working on a large-scale analysis of financial transactions:

At DNB we applied an outlier detection tool in Know Your Customer examinations. We used it to detect anomalous transactions in a dataset that contains millions of customers and bank accounts and billions of transactions.

Where does DNB get this huge dataset from? What is the legal basis for this data processing?

The ChatDNB tool

The day before yesterday, it was announced that DNB’s chatGPT project has been designated ‘initiative of the year’ and that the organisation has sold its digital soul to the Microsoft devil:

Initiative of the year: the Netherlands Bank’s ChatDNB
Generative AI tool helps improve supervisory work and shows wider promise (…)

Starting in April 2023, a group of data scientists, software engineers, large language model specialists and regulatory experts at the central bank worked around the clock to design ChatDNB, with the support of Microsoft’s Azure OpenAI Service. In May, the team had already built a proof of concept, trained with five publicly available annual reports used as textual source material. This proof of concept showcased the potential of the tool and sparked interest from supervisors. (…)

Unlike the web version of ChatGPT, which gives answers based on a large dataset, including information available on the internet, the Dutch central bank’s inhouse GenAI tool returns answers based on specific documents provided by the bank. In developing ChatDNB, they set up safeguards to prevent the system from referring to the internet or taking questions out of its permitted scope, Severeijns says. In addition, ChatDNB also cites the sources it consulted when it gives an answer. 

In future the tool will also analyse confidential information:

DNB is currently looking into developing more use cases for ChatDNB. The first step is to train the tool not only on publicly available information, but also confidential information. In December, the team gained approval from management to explore use cases using confidential data, where the most potential for the tool can be achieved internally.

Will DNB later do the data processing Maijoor talked about last year with their ChatDNB tool? What about safeguards for citizens, GDPR compliance and oversight of what DNB is doing?

There are many unanswered questions.

No doubt there are good intentions, but where is the critical challenge that comes with far-reaching projects like this?