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HCL- The Advance of RPA and AI in Banking

Vendor Analysis

by Andy Efstathiou

published on Dec 06, 2018

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Report Overview:

This NelsonHall assessment analyzes HCL’s offerings and capabilities in RPA and AI in Banking. HCL 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 HCL is a comprehensive assessment of HCL’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:

HCL Technologies’ (HCL) started working with RPA and AI in late 2013. RPA and AI services started as part of HCL’s autonomics and orchestration business. HCL has developed frameworks and built tools for managing RPA and AI, including:

  • DryICE framework: an autonomic and orchestration framework
  • Toscana: a business process management solution for operations
  • EXACTO: Artificial intelligence driven content digitization platform
  • Lucy: a cognitive use agent for cloud operations.

See the Delivery section for more detail on the tools HCL uses in its RPA and AI practice. 

HCL’s first banking RPA engagement began in 2014, for a global bank based in Europe. The engagement goal was to reduce the TAT for account opening and residential mortgage approvals. Using RPA tools, HCL was able to reduce average handle times by 80%, Reduce TAT from 96 hours to same day processing and overall costs by 41%. This was achieved by improving the sourcing of information across disjointed systems in the bank and increasing the accuracy of processing the data using automated processing.

Table of contents:

Table of contents:

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

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