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Andy Efstathiou

Andy is the Banking Sourcing Research Director at NelsonHall where he has global responsibility for Retail and Commercial Banking BPS, Capital Markets BPS, and RPA, AI, and FinTech services in Banking, including consulting, design & deploy, and operations support.

IBM - RPA and AI in Banking BPS

Vendor Analysis

by Andy Efstathiou

published on Oct 31, 2016

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Report Overview:

This NelsonHall vendor assessment analyzes IBM's  offerings and capabilities in RPA and AI in Banking BPS.

Who is this Report for:

NelsonHall’s Retail Banking BPS Vendor Assessment for IBM is a comprehensive assessment IBM’s RPA and AI offerings and capabilities for the banking industry designed for: 

  • Sourcing managers monitoring the capabilities of existing suppliers of RPA and AI services and identifying vendor suitability for banking industry (consumer banking, commercial banking, and capital markets) RPA and AI services RFPs 
  • Vendor marketing, sales and business managers looking to benchmark themselves against their peers 
  • Financial analysts and investors specializing in the support services sector. 

Scope of this Report:

The report provides a comprehensive and objective analysis of IBM’s RPA and AI services for banking offerings, capabilities, and market and financial strength, including: 

  • Identification of the company’s strategy, emphases and new developments 
  • Analysis of the company’s strengths, weaknesses and outlook
  • Revenue estimates
  • Analysis of the profile of the company’s customer base including the  company’s targeting strategy and examples of current contracts
  • Analysis of the company’s offerings and key service components
  • Analysis of the company’s delivery organization including the location of  delivery locations.

 

Key Findings & Highlights:

This NelsonHall assessment analyzes IBM’s offerings and capabilities in RPA and AI services for the banking industry. IBM is one of a number of banking services vendors analyzed in NelsonHall’s comprehensive industry analysis programs.  

Overview 

IBM began its automation journey ten years ago by deploying simple  scripting and macros into client operations to automate manual processes. Over the past two years, clients have been increasing their demand for automation services and IBM has been delivering RPA for data management and processing. IBM’s roadmap for automation adoption is:

  • Desktop automation: focus of past ten years of client engagement: 
    •  Automation of simple transactional data  
  • Robotic process automation: majority of banking clients today are at this level of maturity: 
    •  Management of structured data and simple rules 
  • Autonomic process automation: early adopters beginning to deploy these  capabilities:
    •  Management of unstructured data and complex rules 
  • Cognitive automation: early adopters considering strategy and deploying a few POCs: 
    •  Combining RPA and AI to improve processing

IBM works with third party and proprietary solutions and platforms for its  RPA and AI offerings. 
  

 

 

Table of contents:

Table of contents:

  • Background
  • Revenue Summary
  • Key Offerings
  • Delivery Capability and Partnerships
  • Platforms
  • Pricing and Contracts
  • Changes to Operations
  • Target Markets
  • Strategy
  • Strengths and Challenges
  • Strengths
  • Challenges
  • Outlook

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