Case Study

RPA: anti-money laundering has a new partner

Through RPA technology, we automate the Anti-money laundering process of a well-known Italian Private Banking Institution, reducing errors and optimizing data collection and validation.

Where: italy
Challenge
The Bank's objective was to streamline the AML process, eliminating the accumulation of backlog practices and eliminating the rework due to errors during the data collection phase.
Approach
Our Client is a Private Banking Institution, part of a large Italian Banking Group, with over 6,000 private bankers, over 700,000 customers and €220 billions of funds managed. Recently, it identified the need to streamline specific processes and, at the same time, to free up the centralized anti-money laundering unit from activities related to the research and collection of data needed for the Anti Money Laundering (AML) evaluation of its customers. This is a people-intensive, repetitive and time-consuming activity (from 40 to 60 min for each procedure), where collected data comes from multiple information providers.
Digital Ecosystem
Solution
Digital Ecosystem
To meet our client's needs, Engineering D.HUB, our company for outsourcing and Cloud migration services, developed an "attended" RPA solution, based on NICE technology. Specifically, we provided three pools of robots that, starting from a small set of information provided by operators belonging to the AML Office, carry out all activities for the collection of data from multiple information provides: data access, research, collection and storage. By arranging the pool of robots in 3 separated groups, according to the different kinds of information providers, we have optimized database access allowing to elaborate a higher number of procedures. Because of such impacts, the solution has been extended also to other business groups and process areas.
Results

Around 400 evaluations per month

Zero error margin

Reduced risk assessment time, from 60 to 2 minutes

Technologies

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