Vendor Analysis
published on Oct 31, 2016
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.
