HCL positioned as a Leader in NelsonHall NEAT for RPA & AI in Banking | HCLTech
Analyst Firm Name
NelsonHall
HCL positioned as a Leader in NelsonHall NEAT for RPA & AI in Banking

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As per the report, 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.

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.

As per the report, 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.

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.

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