WorkFusion Archives - IBA Group - USA https://us.ibagroupit.com/tag/workfusion/ Mon, 14 Oct 2024 10:58:39 +0000 en-EN hourly 1 https://wordpress.org/?v=6.5.5 Bank transfers automation https://us.ibagroupit.com/cases/rpa-bank-transfers-automation/ Tue, 10 Dec 2019 12:20:45 +0000 https://us.ibagroupit.com/?post_type=cases&p=5970 The post Bank transfers automation appeared first on IBA Group - USA.

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Result

Bank receives email requests for cash transfer from one client’s account to another to pay off loans held with the bank. Transfer executed after validation. The main goal was a reduction of manual efforts, processing time and data consolidation.

BUSINESS CHALLENGE

  1. Time reduction on set-off operation execution: from 1 day to 10 minutes.
  2. 90% process automation

SOLUTIONS HIGHLIGHTS

  • RPA bot compares data in different systems.
  • Bank employees only need to update lists of debtors
  • ChatBot consults clients on loans
  • EmailBot sorts and classifies incoming emails

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]]> Contracts processing automation https://us.ibagroupit.com/cases/pilot-rpa-ai-implementation-at-multinational-it-provider/ Fri, 18 Jan 2019 09:34:24 +0000 https://us.ibagroupit.com/?post_type=cases&p=4502 The post Contracts processing automation appeared first on IBA Group - USA.

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Challenge

The customer aimed to test feasibility of a cognitive automation technology for its business processes. The pilot business process consisted in validation of the tax amount charged in a vendor contract. Tax rates vary for different groups of vendors and are defined in the customer’s database.

Process Requirements
  1. Achieve overall business process accuracy of 98 percent
  2. Reduce manual time spent on one process by 50 percent
  3. Train and support customer’s team to build automation for an SAP case.

SOLUTIONS HIGHLIGHTS

  1. Create an information extraction model for the fields vendor_name and cost, implement a predefined data storage with a list of vendors, and conduct an additional similarity check. Create a stamp detection model based on Tensorflow, Keras, and Open CV. Develop a script that locates a stamp in a document to help the business analytics team prepare a machine learning training set with 100 percent correctly marked data.
  2. Create five RPA nodes for MS Access automation using a desktop driver. As the database is encrypted, JDBC options are not applicable.
  3. Create a single RPA node for Skype automation with infinite reading of incoming messages to trigger the launch of the pilot business process.
  4. Develop an automatic tool to decrypt documents online.

 

Implementation

IBA Group acted as a subcontractor, working on the customer’s premises. The project was ongoing within 1.5 months.

IBA Group and the customer organized regular Q&A sessions to overcome language and cultural differences, transfer knowledge of RPA/AI technologies, drive SAP case development, and resolve issues with software and source code.

As the databases were encrypted in line with the customer’s policies, IBA Group developed an automatic tool that decrypts documents online using InfoCage FileSystem Shell.

Project Results

  1. Overall business process accuracy: 100%
  2. Reduction of manual effort: by 83.6%
  3. Average document processing time: 30 seconds
  4. Cognitive automation trained on 1,469 documents or 4,000 pages.

 

Ultimately, the customer’s development team built their own automation for an SAP case.

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]]> Bank Automates Document Processing https://us.ibagroupit.com/cases/bank-automated-document-processing/ Fri, 11 Jan 2019 09:06:48 +0000 https://us.ibagroupit.com/?post_type=cases&p=4212 The post Bank Automates Document Processing appeared first on IBA Group - USA.

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KEY ISSUES

To prepare financial reporting, the bank’s employees process 500 types of files. The data in the files is the same entity when it is loaded into the corporate system, but is called differently.

The goal of the project was to reduce manual processing of documents to standardize the data. At the beginning there are only a few experts who know where and what data to retrieve.

Talk to our finance and banking experts

Solutions & Key Results

The process is automated by 90%. 98% of data are extracted automatically with 96% accuracy. The figures are growing as the robots are constantly trained on “historical data”.

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]]> WorkFusion https://us.ibagroupit.com/vendors/workfusion/ Mon, 17 Dec 2018 09:43:44 +0000 https://us.ibagroupit.com/?post_type=vendors&p=3615 The post WorkFusion appeared first on IBA Group - USA.

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PROJECTS AND NEWSROOM

WorkFusion

CasesBank transfers automation
CasesRPA / AI Proof of Concept Implementation at International Bank
CasesBank Automates Document Processing
CasesRPA. AI Implementation at Multinational IT Provider

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]]> Cognitive RPA for International Bank https://us.ibagroupit.com/cases/rpa-ai-proof-of-concept-implementation-at-internationalbank/ Mon, 10 Dec 2018 04:48:36 +0000 https://us.ibagroupit.com/?post_type=cases&p=3504 The post Cognitive RPA for International Bank appeared first on IBA Group - USA.

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Challenge

The customer hired IBA Group to test, if the RPA (Robotic Process Automation) and AI (Artificial Intelligence) technologies for which they bought a license suit their needs.

 

The bank receives a daily list of transactions on currency exchange. Bank employees have to compare the list with data in the internal banking system. Data come in exls, pdf, html, and plain text formats. In cases of data error, clarification of information routed to employee (Human Task)

SOLUTIONS HIGHLIGHTS

Classify input data, automate data extraction (cognitive automation with training model based on 1,500 documents), compare input data with data in the banking system (RPA task), and send messages on process results (bot task).

 

IBA and the customer worked together on the Proof-of-Concept, implementing the most typical business processes. The project duration was three months. Of these, IBA Group spent one month at the customer’s premises and two months working from an offshore location.

Project Results

  1. Automation rate for extraction: 78%
  2. Average accuracy: 94%
  3. Reduction in manual effort per transaction: 63% (1 m 50 sec vs. 5 min)
  4. For Excel: accuracy 100%, automation rate 100%,

 

As the proof-of-concept yielded positive results, the project was put into production.

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