Vendor Analysis
published on Jan 04, 2019
Report Overview:
This NelsonHall assessment analyzes WNS' offerings and capabilities in RPA and AI in Banking. WNS is one of a number of RPA and AI services companies analyzed in NelsonHall’s comprehensive industry analysis programs.
Who is this Report for:
NelsonHall’s The Advance of RPA and AI in Banking Vendor Assessment for WNS is a comprehensive assessment of WNS’s RPA and AI in Banking offerings and capabilities designed for:
- Sourcing managers monitoring the capabilities of existing suppliers of capital market process outsourcing and identifying vendor suitability for RPA and AI in Banking 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 RPA and AI in 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:
WNS RPA and AI activities are part of the Digital Automation practice. WNS started its RPA and AI practice in 2011. The first RPA client was a regional U.S. bank where WNS implemented a desktop integrator for account administration. The practice grew rapidly with 90 BOTS deployed by 2012 across the banking and insurance industry. By 2013 WNS had 12 clients using its RPA services across BFSI.
In 2015 WNS invested in a framework, TRAC, which would support a domain led approach to automation and facilitate partnering with automation product vendors. See Delivery for a description of TRAC.