Modernizing data platforms for risk & regulatory compliance

Project overview

Our client a leading financial services technology provider wanted to deliver solutions to help government regulators identify and combat stock market manipulation, such as insider trading, pump and dump, and accounting fraud.

Blankfactor developed two business-critical data products: a market surveillance manager (MS) and a financial auditing (FA) product. The MS product analyzes market and client data to flag areas of risk or manipulation. The FA product powers faster error identification and boosts FINRA submission accuracy. 

Our team worked to scale and modernize these data products’ ecosystems in the Snowflake cloud. 

Project goals

  • Identify and ingest public and proprietary data sources, including news feeds, social media, SEC filings, and trading data
  • Store and process data to identify anomalies and irregularities using machine learning, NLP, and data mining techniques
  • Establish reporting and alerts system to identify regulators of irregularities
  • Create a data governance strategy to ensure compliance and data security
  • Integrate with stock market regulatory systems to deliver insights
  • Conduct testing to ensure the product delivers accurate results

Team structure 

Technical Architects
Technical Leads
Data Engineers
.NET Engineers

Tech stack

The result

We delivered a highly performant cloud environment for both products, which was heavily optimized for cost efficiency and delivered competitive advantages in client onboarding.

Our data team leveraged critical scalability features in Snowflake, designing an agile cloud architecture that produces on-the-fly analytics, processes more data, supports bulk data correction, and detects risk signals nearly instantly.

time and cost savings following Snowflake migration
more market manipulation threats detected in near real-time
reduction in turnaround time for error correction
Case studies

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