GOALS

• Mitigate operational risks and ensure compliance with regulatory frameworks such as BCBS 239 and GDPR by implementing robust data management solutions.
• Leverage data analytics to identify and assess potential risks, enabling proactive risk management and mitigation strategies.
• Improve data quality and governance to ensure the accuracy and reliability of risk models and reporting, facilitating informed decision-making.

Frustrations

• Struggling to integrate and analyze data from various sources, leading to incomplete risk assessments and potential compliance gaps.
• Dealing with inconsistent data quality and a lack of a single source of truth, hindering effective risk reporting and analysis.
• Facing challenges in keeping pace with evolving data privacy regulations and the associated compliance requirements.

GOALS

• Establish a robust data governance framework to ensure data quality, consistency, and compliance with industry regulations and internal policies.
• Implement data management solutions to streamline data operations, improve data discoverability, and facilitate efficient data sharing across the organization.
• Enhance data literacy and promote a data-driven culture within the organization through training and awareness programs.

Frustrations

• Resistance to change and lack of adoption of data governance policies and procedures across different departments.
• Difficulty in enforcing data quality standards and ensuring accountability for data accuracy and completeness.
• Managing and securing large volumes of data from diverse sources, including sensor data, operational data, and customer data.