The solution was designed for one of Italy’s most important banks. Irion implemented a data quality system for producing regulatory reports for the Bank of Italy.

This flexible, efficient, and complete system allowed our Client to control the process, significantly reducing the recycling and the processing times. Above all, it eliminated the issues the Bank of Italy encountered in the reporting data.

They needed to improve their processes. The Bank has a considerable number of branches all over Italy, which are leaders in all industrial sectors (retail, corporate, and wealth management).

Internationally, it has a network specializing in corporate client support with global coverage of about 29 countries and is particularly important in Central Europe.

In this respect, the main challenges our Client was facing were the following:

• ensure maximum flexibility for business users
• run checks with different levels of complexity
• comply with the very rigid processing times while working with enormous volumes of data.

All this was resolved by Irion.

The Irion Solution

After an elaborate selection process, including a proof of concept on actual data volumes, Irion EDM was selected as the only tool, being the most adequate for the needs. It guarantees remarkable performance while being hugely flexible in terms of check parametrization. Irion EDM enables a highly agile development methodology based on rapid prototyping logic. It considerably cuts down on the traditional initial analysis phase in favor of faster cycles based on short sessions of analysis, prototyping, and design review. This approach guarantees reduced implementation time and allows the client to concentrate more energy on the aspects where their contribution is essential (defining the business logic, algorithms, process) instead of dispersing it on the more technical and infrastructural ones, such as the architectural system, data model, UI, etc. It is thus possible to reduce the costs of inevitable recycling and control tuning in progress (filters, threshold calibration, etc.).

All the checks are performed using Irion’s Rule Engine. The different types of solution checks include:

• accounting: balancing checks between interface data streams and accounting master data;
• accuracy: consistency checks between interface data streams and the original batch to check that the data extraction was correct and complete;
• progress: checks that relate the data from a stream with the data from the same stream from the previous month, or the same month but the previous year, in order to eliminate possible periodicity effects;
• logic: checks on the data from a stream that relate different data items to each other based on the characteristics of the operations they refer to;
• logic with tables: data consistency checks within an interface data stream with the help of support tables (e.g., the Table of changes);
• logic/progress: consistency checks between the data from a stream and the data from the same stream from the previous periods.

Checks are performed on both monthly and decadal SISBA processing as appropriate. Downstream, the system is integrated with the BI tools the Bank uses.

The Benefits

Thanks to the project, the Client now has a flexible, efficient, and complete system for controlling their process. Moreover, they significantly reduced the recycling and processing times and, most importantly, decreased the issues Bank of Italy encountered in the reporting data (a 90% reduction).

The system is now operational, with about 2000 checks over a vast variety of areas. Some stats (indicative data):

• 200 registered input data streams
• 22,000 active checks
• 4 billion (unit) checks performed during one month while processing a total of circa 10,000 input data streams (with maximum file size of about 15 GB)
• 1 million checks per minute

Besides, the entire process (sources, business logic, algorithms, etc.) is extensively documented. Irion has improved the data quality and decreased the efforts and resources the Client needs to engage, thus giving them a significant data advantage.