Speaker

Tim Collins, head of Consulting, Product Development and Analytics, TransUnion

Tim Collins

Head of Consulting, Product Development and Analytics, TransUnion

Tim is a technology strategist with over 12 years' experience in consulting and technology businesses. His expertise is in helping organisations leverage analytics, data and technology to address their strategic objectives. Collins was a judge for the Accenture Innovation Index in 2017.

His current role is managing a team of 50+ resources who develop new information risk solutions for TransUnion's African customers. He is also responsible for engaging with these customers at C-suite level to help them understand how TransUnion's solutions can address their critical business issues.

Collins has extensive emerging markets experience, having successfully completed over 40 consulting engagements across SA, Kenya, Dubai, India, Angola, Mozambique and Zambia. He has worked across the financial services, communications, technology, utilities and retail sectors.

Collins holds an honour's degree in information systems from the University of Cape Town and is a certified ITIL and TOGAF practitioner. He completed studying Disruptive Strategy with Clayton Christensen at Harvard Business School in 2016.

Tim Collins will be speaking on the following topic:

10:45
Case study: Credit The use of machine learning, alternative data and smart algorithms to better predict consumers behaviour and improve financial inclusion

A look at how AI and alternative data can help you better understand consumers financial behaviour. This presentation will illustrate how this system is able to predict the future behaviour of consumers and how it then hyper customises or personalises the products based on the profile of the consumer.

  • Gain insight into how a better understanding of consumers spending patterns can assist with mitigating risk
  • Learn how to customise and personalise products for individuals to provide better product offerings to your clients
  • Discover the value of using alternative data

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