“The global cost to the financial services industry of compliance with regulatory authorities is estimated at $100 billion per year — a number that’s risen drastically since the 2008 financial crisis. For many financial firms, compliance is 20 percent of their operational budget.”
- Techcrunch

Regulatory compliance is a labour intensive and rule based task. The emergence of RegTech is to handle this growing need to be compliant. Getting equipped with correct methodologies and Big Data tools is of utmost importance for improving profitability of institutions. Probyto offers its understanding into how Data Science tools can be impacted, and should be developed to remain compliant with regulators.

Audit of Data Science

Model Risk Management

Scenario and Extreme Case Analysis

Data Lineage

  • Provide model assessment services to measure impact of GDPR regulation on the current models.
  • Help analyse the machine learning algorithms used in modelling and forecasting of financial instruments e.g., Basel III and CCAR compliance.
  • Many models are not designed to work in extreme scenarios and expose business for regulatory risk of rejection or wrong decision. We do stress testing of the models and scenarios analysis to pre-emt any risk of using the models.
  • Perform end-to-end data lineage tracking and testing for potential issues for deploying a model live. Finding critical and non-critical components for data governance of deployed models.

Probyto have combined experience of domain knowledge for Data Solutions, Technology, Algorithms and use-case knowledge to help you create more impact with Data in Regulatory Compliance. We can help you uncover data sources and integrate them into one platform. Also assist to deploy visualisation platforms and build stories for business metrics.


Abhishek Singh


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