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Advance Your RPA Initiatives

 Advance Your RPA Initiatives - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Robotic Process Automation (RPA)
Applicable Industries
  • Finance & Insurance
The Challenge

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.

About The Customer

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.

The Customer

A Global Bank

The Solution

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.

Operational Impact
  • [Efficiency Improvement - Labor]

    saved over 3000 person-hours per month

Quantitative Benefit
  • Monarch is the fastest and easiest way to extract data from dark, semi-structured data like PDFs and text files as well as Big Data and other structured sources

  • Once data is extracted Monarch cleans, transforms, blends and enriches the data using an easy-to-use interface free of coding and scripting

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