Can ‘Observational Learning’ Help Improve Data Quality?
Data quality is a pre-requisite for financial institutions seeking to automate their operations. But given the huge volumes of transaction data, often in a wide array of formats, it is very difficult to achieve.
Can newer AI-based techniques such as observational learning actually help or are they just hype?
This white paper explores:
- What observational learning is in a data management setting
- How it can help with specific data quality issues
- Examines use cases in critical operational and regulatory processes
- Considers benefits such as improved STP rates, operational efficiency, better data quality results and more.