DataMasque has been listed as a solution provider on the Monetary Authority of Singapore's PathFin.ai programme, placing it in a library of artificial intelligence tools and implementation practices for financial institutions.

PathFin.ai is a joint initiative between MAS and the financial industry to support knowledge-sharing on AI use in finance. It brings together AI solutions and implementation examples to help institutions reduce the time needed to assess and adopt new tools.

DataMasque focuses on sensitive data discovery and masking. Its inclusion comes as banks and other financial institutions face pressure to develop and test AI models without exposing customer information or breaching privacy rules.

Financial institutions often need data that closely reflects live customer records when training or fine-tuning AI systems. This creates a challenge for organisations that must balance the need for realistic data with regulatory controls on personally identifiable information and other sensitive records.

Traditional approaches such as redaction, scrambling, and dynamic masking can reduce the usefulness of data for model training or leave some information visible. DataMasque says its system replaces sensitive data with what it describes as "synthetically identical" values that preserve format and referential integrity while keeping personal information inside a secure production environment.

The approach can also support federated learning, in which several institutions contribute to a shared model. In that setting, organisations can avoid using actual customer identities in training data while preserving the patterns a model needs to learn across institutions.

DataMasque also pointed to a deployment at a large Asia-Pacific bank migrating an on-premises SAS credit risk system to the cloud.

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