RPA Case Studies/Success Stories

See RPA in action through real life case studies

Case Study 01 – Helping improve Fraud Prevention and SLA Adherence in the Front Office for a large Italian Bank
Summary Problem         :   Agent wrap up time, causing loss of time while entering data
Summary Solution          :   Automating wrap up time
Summary Outcome        :   Improve Agent satisfaction, dramatic improve in KPI
Problem Statement:
One of Italy’s major financial services groups had established its own contact center to provide business process outsourcing services for financial and insurance organizations. Guided by a customer-oriented business philosophy, it had built a strong reputation for exceptional personal customer service. Operations however were flagging as the contact center reached capacity; 500 agents were roughly handling 650,000 calls per month and the agents were under immense pressure to meet SLAs that needed agents to take action within five minutes of receiving a fraud alert for a suspicious credit card transaction. Agents were spending a lot of time on data entry and after call activities after a customer interaction ended. The centers needed a new way to reduce the repetitive and low value tasks interfering with the core activities of the agents – without sacrificing accuracy or undermining customer relationships.
The banking organization evaluated it’s contact handling process to identify robotic automation opportunities – those routine, critical jobs that require accurate, fast and single-minded handling. After the initial discovery, the organization implemented NICE RPA with desktop automation. The solution guided agents with pop-up screens during fraud investigations and call handling with customers.
The solution allowed the contact center robots to execute a series of data entry actions, including ticket and database entry log and filling of claim requests. It freed up agent time to focus on fraud investigations, decision making and on the customer interactions.
The financial services organization was able to drive quality, accuracy and speed and it’s contact center realized significant results across a range of key performance parameters. Some of the outcomes are listed below:
  • Agent satisfaction improved significantly as they could focus on customer engagement
  • SLA adherence improved to 100%
  • +20% increase in addressing fraudulent credit card transaction alert
  • 82% reduction in ACW time
  • Improved quality, speed and accuracy
  • Avoided additional agent costs
Case Study 02 – Sales Order Management & Delivery Scheduling Automation for a Home Furnishing Retailer
Summary Problem         :   Manual delivery schedule cause delays in supplying furniture
Summary Solution          :   Automating Scheduling of deliveries
Summary Outcome        :   Reduce man power, decrease errors, improved customer satisfaction
Problem Statement
One of the world’s largest home furnishing retailers, which operates more than 300 stores in 43 countries, depended on a powerful infrastructure to keep operations on track and maintain customer satisfaction. Its order entry and automatic delivery systems, however, had become weak spot for the retailer, which had 135,000 employees and 775M customer visits each year. Bulky spreadsheets were used in the order management and delivery scheduling process which were prone to human error and wastes enormous hours during handling. The complications were increasing as the company was growing and the management needed a better order and delivery management solution.
The retailer assessed its processes and after a quick discovery, decided to use NICE RPA. The NICE RPA solution automatically checked for customer orders, including 3rd party manufactured goods and generated labels for the containers. Robots handled majority of the spreadsheet work that wasted human hours and led to errors. Through desktop automation, it delivered call-outs to agent screens to suggest open slots for scheduling delivery based on business rules. The solution was flexible enough to work with 20+ vendors across multiple geographies.
The RPA solution saved time and improved accuracy by eliminating order entry and scheduling errors. Some of outcomes are as below:
  • 16 FTEs work automated, redirected to other high value work
  • 15% cut down in errors in delivery scheduling due to manual work with negative impact on CX; 100% accurate order management
  • 23% higher volumes handled by robots
Avoided operations team costs
Case Study 3
Summary Problem                        : Multi site dual recording systems of archived and on-going transactions. Risk in audit non-compliancy and service Massive spending.
Summary solution          : Multi Site process automation to retrieve archive into one ongoing audio system
Summary Impact            : All audit compliance satisfied while achieving massive savings in infrastructure and support.
Problem statement:
A leading US bank is a diversified, financial services company with $2 trillion in assets, hundreds of branches and thousands of agents.
All agents’ calls were recorded since the 2000’s. As the bank acquired different banks 2 recording systems were running in tandem.
Convert a multivendor system archived and online and consolidate to one system. Challenges included massive volume, changing record formats, distributed infrastructure departments and storage.
The project includes Recovering / Transforming / Importing and injecting, more than 150M calls. old and new (on the go) recording from a different recording system to Nice systems state of the art new recording system:
  • Converting archived calls records from multiple years/storage systems into Nice format and inserting to the Nice archive system.
  • Converting recent calls records (while system is working) to the Nice on-line recording
  • Pull call recordings and manoeuvre storage placement to adhere to converted records
  • Import all information to Nice system echo system
  • Due to the volume, multiple BOTs were required to speed up performance.
Nice automation was used to insert data records and audio clips into the new formed Nice database. CirriusImpact professional services designed developed implemented and maintained, 3 different BOTS to provide:
  • Automatic verification conversion BOT designed to detect incoming data stream verify coherence of format and convert old format to Nice Format
  • Manoeuvring BOT designed to direct all formatted data as well as calls recordings to designated storage
Importing BOT designed to plug all incoming records and calls into the new Nice recording system.

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