Financial Crime: Conduct Risk Dashboarding With Qlik Sense

Solution

• Successful dashboard implementation that complies with the principles for Effective Risk Data Aggregation and Risk Reporting (RDARR)

Banking area

• Financial Crime (Conduct Risk)

Skill sets

• SQL

• Qlik Sense

• Hadoop

• Data Analysis

Themes

• Data Automation

• Data Extract-Tranform-Load

• Business Specifications

•  AML and conduct risk reporting

Insights

• Understand the granularity of source system data

• Involve downstream users as early as possible, especially if there is a change in data structure.

• Buy-in from important stakeholders at the start of the project is key

Overview

A large retail and commercial bank required assistance with the sourcing, standardisation development and reporting of conduct and compliance data for critical financial crime metrics. The resulting dashboard incorporated various market conduct metrics such as frequency of complaints and incidents, usage of products, reporting exceptions and other important cost, customer experience and risk figures.

These metrics were utilised for regulatory reporting as well as for consumption by the group board and relevant compliance committees.

Monocle was tasked with unpacking the data lineage of the metrics to be tracked and monitored. Monocle ensured the automation of data from source into the AML data mart where possible. Sourced data had to be migrated in line with the strategic architecture of the bank, therefore we identified and led the resolution of all data quality and formatting issues.

Monocle assisted with the documentation of the ETL process for the reporting data in line with the principles of RDARR and robust data governance.

Additionally, Monocle provided training for data owners on the new data upload process into the AML data mart and ensured delivery of all deadline and tasks.

Results

• Automation of the ETL process for key data sources

• Accurate and timely reporting of key conduct risk metrics

• Comprehensive documentation of ETL and reporting processes

Key skills required

• Automation of data ETL for conduct risk reporting

• Data analysis with strong SQL coding capabilities

• Business analysis skills including ability to document data processes and conduct source data investigations

• Strong communications skills to guide collaboration between business and the development teams