Why Finance Data Quality Needs Rule Engines, Not ML Hype

About this episode

The episode discusses the importance of rule engines over machine learning hype in ensuring financial data quality.

This story was originally published on HackerNoon at: https://hackernoon.com/why-finance-data-quality-needs-rule-engines-not-ml-hype . Why financial data quality depends less on ML hype and more on rule engines, governance, vendor controls and audit trails that regulators can understand. Check more stories related to data-science at: https://hackernoon.com/c/data-science . You can also check exclusive content about #data-quality , #reference-data , #financial-data , #data-governance , #audit-trail , #data-validation , #regulatory-reporting , #auditability , and more. This story was written by: @nithish_6q9kh89 . Learn more about this writer by checking @nithish_6q9kh89's about page, and for more stories, please visit hackernoon.com . Why financial data quality depends less on ML hype and more on rule engines, governance, vendor controls and audit trails that regulators can understand.

Topics covered

• finance
• data quality
• rule engines
• machine learning
• data governance
• audit trails

Keywords

• data quality
• financial data
• rule engines
• data governance
• audit trails
• regulatory reporting
• data validation

Mentioned in this episode

Organizations: HackerNoon

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