Capgemini Insurance

Capgemini Insurance

Commercial Lending Technology Advisor - Digital Transformation

Toronto, Ontario, Canada

Sponsorship not specifiedDetected 27 days ago
SQLStakeholder ManagementLeadershipCommunicationUnderwriting

About the role

  • As a Commercial Lending Technology Advisor, you will act as a senior subject matter expert supporting both client engagement and delivery teams across lending transformation initiatives.
  • You will play a critical role in shaping client solutions, driving workshops, supporting pre-sales cycles, and advising on end-to-end lending transformation programs-from initial visioning through implementation.

Responsibilities

  • Own end-to-end lending transformation outcomes across commercial lending programs · Act as a strategic advisor to client leadership on lending operating model, technology modernization, and digital channels · Support modernization of lending platforms including LOS and workflow tools Provide industry best practices across
  • Engage with CXO stakeholders (CIO, Head of Lending, COO) to shape transformation agendas and strategic roadmaps. · Lead client workshops and requirements sessions ·
  • Advise on implementation scope and estimation Solution Design & Delivery Advisory:
  • Drive solutioning and participate in large deal pursuits / RFPs and contribute to practice growth. · Develop solution architectures and process designs · Act as advisor to delivery teams ·

Requirements

  • You will combine knowledge of commercial lending operations (e.g., loan origination, underwriting, risk assessment) with expertise in technology platforms and implementation approaches.

Nice to have

  • Bachelor's degree or equivalent.
  • 15+ years of experience in commercial lending or consulting.
  • Strong knowledge of lending lifecycle and credit processes.
  • Experience in LOS or lending technology implementation.
  • Strong communication and stakeholder management skills Preferred Skills.

This listing is sourced directly from Capgemini Insurance's careers page and normalized into a canonical job model.