Data Quality Assurance

Accurate, integrated quality data will drive confident, proactive decisions to support solid risk management, while incomplete and inconsistent financial data can cause massive problems for financial institutions, especially when it comes to risk controlling and decision making. 

Financial data quality is a key element of any risk management solution, particularly challenged by the diversity and complexity of data sources in banking and financial services.

• While most vendor solutions assume the data quality is adequate, the GPS DQA MODULE provides banks with the tools to accomplish their data ownership and data lineage mission.

• Our data quality management solution includes a comprehensive set of exception reporting tools that will highlight actual and potential data problems and allow for easy resolution and sign off, with full audit trail for any changes

• Vast experience in the field, strong understanding both of risk management practices and technology – ability to think strategically and at the same time be hands-on and participate directly in the product development

• Innovative technical solutions - e.g. NLQL, a framework for risk data query in a language close to ‘natural language’

• Workable solutions in addressing industry ‘pain points’, e.g. a set of data quality assurance steps, largely under-estimated by out competitors; we don’t take “garbage-in, garbage out” as a forgone conclusion

• Making meaningful use of emerging technologies – e.g. use of private blockchain solution for data lineage management