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Revolutionising credit decisioning in digital banking: harnessing AI/machine learning, LLM and alternative data sources

The panel

  • Sayantan Banerjee, Head, credit and lending advisory – strategy and consulting, banking South-east Asia, Accenture
  • Sarah Murphy, Principal director, Accenture
  • Terisa Roberts, Global solution lead, risk modelling and decisioning, SAS
  • Chu Hong Minh, Head of credit risk modelling and risk analytics, VP Bank
  • Matthew See, Executive director, head of credit analytics digital solutions, DBS Bank

This webinar explores how financial institutions can leverage artificial intelligence (AI), machine learning, large language models (LLM) and alternative data sources, including open banking data, to modernise credit risk assessment and application fraud prevention.

Key discussion points:

  • The current challenges in the implementation of AI/machine learning, LLM and alternative data sources within the credit decisioning process
  • Using alternative data to help assess borrowers
  • The power of LLM in credit analysis and fraud prevention
  • AI/machine learning for accurately modelling credit risk
  • The future trajectory of AI/machine learning, LLM and alternative data in the digital banking landscape

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