First ever Neural Network Language model trained on regulatory text

Mapped 1300 Banking Laws and Acts from over 12K Popular Acts

Extracted 160,000 rules

'Classified’ and ‘Clustered’ rules into

5 Product Classes

267 Product sub-classes

6 Rule Types

9 Rule Matters

Regulation Type (Conduct of Business vs. Prudential)

Mapped Popular Acts to US code sections and downstream to the Code of Federal Regulations (CFR)

Daily changes connected to existing regulations

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