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Flexible Regulatory Reporting

Solutions Gallery > Flexible Regulatory Reporting

Solution overview

One of Trifacta’s clients, a highly-respected Globally Systemically Important Bank (GSIB) with 70 years of experience, 60 offices worldwide, and $995B under management, was grappling with all of the above compliance issues. Like most Trifacta clients, this client wanted an enterprise-wide solution to accelerate time to insight while reducing the costs of data preparation. But as a financial services firm they must also comply with The Basel Committee on Banking Supervision (BCBS) rule 239, which applies specifically to a firm’s data architecture, lineage, and governance policies. In short, Trifacta’s client couldn’t implement any data solution that put their source data or data lineage at risk of non-compliance.

Built from the ground up by financial services professionals, Trifacta Wrangler helped this financial services company save money and time on compliance analytics – while still staying in compliance– by:

  • Moving from home grown, hand coded SQL/Java/Oracle applications and Excel, all requiring idiosyncratic institutional knowledge; to one enterprise wide source of data “truth. “
  • Preserving source data and data lineage—actually improving on prior lineage tracking methods—so that they as a GSIB can prove where their aggregated risk management numbers came from. In a way it’s as though a recording was made of the data’s path from the Hadoop warehouse to the analyst’s report. This way, a financial services company can provide this information if ever needed by an auditor, including metadata and a business glossary.
  • Making more data available to end users on a self service basis, reducing IT overhead costs and accelerating speed to business insight.
  • Moving from disparate data sources into a standardized regulatory reporting infrastructure and data analysis workflow process across all workgroups
  • Increased agility in turning around compliance and regulatory reports.

Compliance In Financial Services: Trifacta For The Win

A standardized data wrangling approach will not only reduce costs by limiting time spent importing, formatting and manipulating by individuals, it will do so by also improving the accuracy, speed and quality of reporting enterprise-wide. This is especially critical for financial services providers, who must understand who has touched data throughout the firm and provide in-depth data lineage to prove compliance with BCBS 239, among other new requirements.

Solution Benefits

  • Data preparation times reduced by up to 15x with automated and predictive data preparation easily shared throughout the organization. Imagine being able to see what’s in a file before importing it.
  • Ensure compliance by preserving source data and data lineage
  • Up to 80% faster reporting speeds, as you and your data science teams can now focus on analysis instead of data preparation.
  • More users leveraging Hadoop investments with Trifacta’s easy to use, visual interface that doesn’t require R, SQL or a traditional ETL process to get value.
  • Infinite data storage and  processing capabilities
  • Empowered analysts who can adapt quickly to regulation changes
  • Ability to combine diverse and inconsistent sources into accurate reports

Key highlights

Security, Risk & Compliance

About Trifacta
Trifacta is designed to help data analysts do the work associated with data preparation without having to manually write code. The joint solution from Trifacta and Cloudera provides a workflow optimized for transforming data at scale. Trifacta Wrangler Enterprise empowers analysts to visualize data stored in Cloudera Enterprise,  to interact with data to define transformation rules that define a Hadoop job (either through  Spark or MapReduce), and to process the data in the desired form for analysis. Trifacta Wrangler Enterprise sits between the Cloudera Enterprise and the visualization, analytics, or machine learning applications used downstream in the process.

Solution Brief

Data: The New Focus for Financial Institutions in 2017 and beyond

Learn more about the solution

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