Crédit Agricole CIB Optimizes Value of Risk Analysis with Qlikview
Customer Company Size
Large Corporate
Region
- Europe
Country
- France
- United Kingdom
Product
- QlikView
Tech Stack
- Microsoft Excel
- TXT
- XML
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Services
- Data Science Services
- System Integration
About The Customer
Crédit Agricole CIB is the corporate and investment banking division of the Crédit Agricole financial services group in France. The bank specializes in capital markets, offering customers a range of products and services, including wholesale banking, investment banking, and structured finance. Crédit Agricole CIB provides support to its customers in major international markets due to its global network in leading countries in Europe, the Americas, Asia, and the Middle East. The bank's fixed income markets monitoring & control (FIM M&C) business unit is a small team tasked with cross-functional missions with a wide area of research— principally market and credit risk across all FIM products worldwide.
The Challenge
Crédit Agricole CIB's fixed income markets monitoring & control (FIM M&C) business unit faced the challenge of optimizing the use of reports produced by market and credit risk teams. The team needed to deploy tools to help consolidate data from various Crédit Agricole CIB risk teams. Prior to QlikView, the FIM M&C team received Microsoft Excel spreadsheets containing information on different fixed income market product lines by email. Consolidating and analyzing such data volumes was a challenge, but there was the added challenge of all the different file formats. Each product line had its own front-office and back-office system. Terms used, file formats, and information sending frequency were all different. This made it difficult for the FIM M&C because it needed to obtain a transversal and consolidated view of the data. The objective was also to compare historical data, which was difficult with the previous system.
The Solution
The QlikView deployment required implementation of a rigorous data model to harmonize references and create the necessary cross-reference tables. The system stores source files in a QlikView directory. They are then read and interpreted by the relevant QlikView applications. This functionality supports the move from a multitude of disparate sources to centralized monitoring. QlikView applications also ensure easier detection of variations, either graphically or by implementing appropriate technical and functional integrity checks. If a figure appears to be unexplained, it's easy to detect and it's possible to return the file to the relevant department for amendment. With QlikView, different types of checks have been implemented. For the technical integrity of data, automatic checking of the date of a file, as well as its size and name, means it's easier to evaluate information consistency.
Operational Impact
Quantitative Benefit
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