Royal Bank of Canada: Streamlining Audits with Dataiku's IoT Solution
Technology Category
- Analytics & Modeling - Machine Learning
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Cement
- Finance & Insurance
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Experimentation Automation
- Time Sensitive Networking
Services
- System Integration
- Testing & Certification
About The Customer
The Royal Bank of Canada (RBC) is one of Canada’s biggest banks and among the largest in the world in terms of market capitalization. RBC, as the company and its subsidiaries are collectively known, is a leading diversified financial services company in North America, providing personal and commercial banking, wealth management, insurance, investor services and capital markets products and services on a global basis. At RBC, the CAE Group has begun a transformational journey that adopts a data-driven approach to provide assurance to its clients. To address the challenges of identifying insufficient controls that could result in financial loss, the CAE Group utilizes analytics to uncover exceptions or outliers.
The Challenge
The Royal Bank of Canada (RBC) was facing challenges in its control testing process, which was manually intensive and only conducted periodically. The process involved selecting control tests, designing test procedures, sampling the resulting dataset/transactions, and checking samples for adherence to criteria. This process was repeated anywhere from annually to once every two years. The CAE Group, burdened by the administrative overhead, had less time to review and revise the outliers. The process was difficult to scale, as the platforms retreated into their silos, where they built and managed their own control testing process. This duplicated effort made consolidation into CAE Group’s holistic enterprise view a cumbersome, manual process. The challenges were both technical and organizational. Technical challenges included the need for platform analysts to onboard and update their models in production, support for the variability of different models and schemas of outliers, categorization of each control test, and managing data governance requirements. Organizational challenges included a shift in mindset for auditors, updating and onboarding existing control tests, and developing incentives for adopting the new platform.
The Solution
RBC partnered with Dataiku to overcome these challenges. Dataiku provided an all-in-one platform for Control Testing at RBC. Using a self-service process, RBC data scientists and analysts focused on building control testing in Dataiku. Once ready to onboard, they simply “tagged” the final dataset which contains the final list of outliers. For rollup to organizational attributes, an editable dataset could be entered. Using the Dataiku API, a background looped through each project containing the metadata and tagged dataset. The outlier dataset’s schema varied for each use case. Dataiku’s SQL API allowed a schemaless approach to dump each final dataset to a centralized database. The metadata, on the other hand, had a deterministic set of columns and was imported to a summary table. This approach provided scalability, flexibility, and data governance. The new process created greater certainty over the status of the control, allowing auditors the freedom to explore ideas.
Operational Impact
Quantitative Benefit
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