- Analytics & Modeling - Robotic Process Automation (RPA)
- Finance & Insurance
A global financial institution was using a report repository connected to dozens of applications and database systems used across the enterprise, from different geographies and multiple business units. Weekly, hundreds of thousands of reports from these applications were manually downloaded to a centralized location for people to use.
The file formats were typically unstructured data, usually in text or PDF. There was no consistency in report formats across the different applications, or even for reports created using the same application. End users would then manually copy data from the text / PDF formats to Excel-based reports used for reconciliation, attestation, financial reporting, journal entries, and other uses.
A Global Bank
Based out of North America, the bank serves close to 20 million customers worldwide, has more than 85,000 employees, and has a net asset value of close to $1.5 trillion with annual revenues of ~$50 billion. It is a member of the Financial Stability Board’s list of global systemically important banks.
Familiar with Altair® Monarch®’s capabilities as it was earlier used in large projects that reduced by more than 1500 hours per-month people on the Shared Finance Services team previously spent on reconciliation tasks (about 50%), the bank turned to Altair to add automatic report modeling and standardization to its RPA architecture. The team created a ‘bot’ to interact Monarch with a well-known RPA provider, which was automating the download of relevant application and database files from the central file repository to a target folder and completed the bulk extraction of data from those files. Altair Monarch
Server Automation Edition automates the transformation of this extracted data into thousands of standardized report formats that meet end-user and regulatory requirements. Using its no-code interface, users can quickly design data models that define the report structures they need and set up the automation processes so that newly extracted data is made consistent with reporting requirements.
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