To measure the effectiveness of data governance and risk management , organizations must define SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) controls.
These controls apply to banking business processes such as:
- KYC and loan applications.
- IT processes like application and database access.
- Business process automation, including ITSM follow-ups and updates.
When designed correctly, data, IT, and system-related controls can be automated, bringing significant efficiency to the organization.
The Challenge of Measuring Business Impact
Designing SMART controls follows the well-established SMART goal framework, yet many organizations struggle to quantify business impact. At the end of the year, outcomes are often described as outputs rather than measurable business results.
Focus Control Design with Business Processes
Let's examine a loan servicing process , where loans are originated in one system but serviced in another. In many cases, customer information across these systems is out of sync, impacting customer service and regulatory compliance. Organizations should implement controls such as:
- Ensuring data quality - Customer attributes like date of birth, phone number, and email should have a 99% accuracy rate .
- Preserving change logs - Customer record updates in call center applications should be tracked for audit purposes.
- Tracking customer updates - Any modifications via online applications should be systematically logged.
Now, let's apply the SMART framework :
- Specific - Track the quality of customer attributes in loan servicing.
- Measurable - Maintain a data quality score of 99% or higher.
- Achievable - Establish a baseline data quality score and improve it within six months.
- Relevant - Align with business objectives to enhance customer service and increase retention.
- Time-bound - Conduct monthly assessments, identify and resolve issues, and track improvements.
How Auditrol Enables Control Automation
Auditrol provides a programmatic canvas via SQL, Python, and Webhooks to automate controls effectively.
- Data Quality (Control #1) - Auditrol executes SQL queries via service accounts to assess data quality metrics and track improvements.
- Change Log (Control #2) - If organizations use log management tools, Auditrol connects to them via APIs through Python programming . It also provides libraries that integrate seamlessly within notebook-based IDEs.
- Real-time Event Tracking (Control #3) - If an application supports Webhooks, Auditrol captures events when customers update their personal information, ensuring auditability and compliance.
Proactive and Automated Risk Management
Once these controls are designed and tested, they can be scheduled to run monthly or on-demand triggers:
- Controls #1 and #2 run monthly assessments to ensure continuous compliance.
- Control #3 operates in real-time, triggering actions when customer data is modified.
This systematic and automated approach helps organizations be proactive in risk management and mitigation, ensuring better compliance, efficiency, and operational resilience.