Book contents
- Frontmatter
- Contents
- List of Illustrations
- List of Contributors
- Chapter 1 Introduction
- Chapter 2 Artificial Intelligence in the United States
- Chapter 3 Artificial Intelligence in Canada
- Chapter 4 The Mad Max Interceptor Experience in the UK: Artificial Intelligence in Mortgages
- Chapter 5 Artificial Intelligence in Germany: Strategy and Policy—the Impact of AI on German Economy
- Chapter 6 Japan's ‘Artificial-Intelligence Hospital’ Project: Can It Help the Ageing Population?
- Chapter 7 Artificial Intelligence in the Middle East European Countries
- Chapter 8 A Million Products for a Billion People: Artificial Intelligence in Consumer Industries in India
- Chapter 9 “All-In AI”: What is Compelling Companies in China to Bet the House on Artificial Intelligence?
- Chapter 10 Artificial Intelligence Research in Russia: Recovering from the Polar Winter
- Chapter 11 The Fourth Industrial Revolution in Africa
- Chapter 12 The Adoption of Artificial Intelligence within the Caribbean: Resuscitating the CARICOM's Single Market and Economy
- Chapter 13 Has Australia Been Late in Addressing the Artificial Intelligence Challenges?
- Chapter 14 Conclusion
- Index
Chapter 4 - The Mad Max Interceptor Experience in the UK: Artificial Intelligence in Mortgages
Published online by Cambridge University Press: 02 March 2022
- Frontmatter
- Contents
- List of Illustrations
- List of Contributors
- Chapter 1 Introduction
- Chapter 2 Artificial Intelligence in the United States
- Chapter 3 Artificial Intelligence in Canada
- Chapter 4 The Mad Max Interceptor Experience in the UK: Artificial Intelligence in Mortgages
- Chapter 5 Artificial Intelligence in Germany: Strategy and Policy—the Impact of AI on German Economy
- Chapter 6 Japan's ‘Artificial-Intelligence Hospital’ Project: Can It Help the Ageing Population?
- Chapter 7 Artificial Intelligence in the Middle East European Countries
- Chapter 8 A Million Products for a Billion People: Artificial Intelligence in Consumer Industries in India
- Chapter 9 “All-In AI”: What is Compelling Companies in China to Bet the House on Artificial Intelligence?
- Chapter 10 Artificial Intelligence Research in Russia: Recovering from the Polar Winter
- Chapter 11 The Fourth Industrial Revolution in Africa
- Chapter 12 The Adoption of Artificial Intelligence within the Caribbean: Resuscitating the CARICOM's Single Market and Economy
- Chapter 13 Has Australia Been Late in Addressing the Artificial Intelligence Challenges?
- Chapter 14 Conclusion
- Index
Summary
Introduction
Owning a home is a keystone of wealth […] both financial affluence and emotional security.
— Suze Orman (‘Thoughts for Success’, 2010)The above words have never been truer than in a world rendered uncertain and chaotic with a virus on the loose. With rigid social distancing protocols established to combat the pandemic, the meaning of home ownership is transcending connotations of just ‘financial affluence’. For most, mortgages are now the most vital pillar of finance.
The mortgage market in the UK strives to continuously reinvent itself to meet the changing demands of its growing and evolving aspirational customer base. You may be privy to the pre-screening methods to assess the viability of a loan that have been in vogue for quite a while. Alternatively, you might even be using credit scoring vendors to check your general eligibility for getting a mortgage (or any loan for that matter) or interacting with a smart conversational AI-driven chatbot like Alexa in mortgages to get more information on product types or payment holidays. Predictive techniques powered by artificial intelligence (AI) are responsible for such optimizations. While these are some examples of the traditional and mainstream uses of AI in the loan space, this chapter attempts to describe the challenges plaguing the mortgage industry, bolstered heavily by an intermediary-led business model, and some of the latest applications of AI in the mortgage space, especially in mortgage origination, and then explain how AI can further help customers, intermediaries and lenders make more informed decisions to reduce costs, increase revenue and improve overall satisfaction especially when lenders are swamped with phone calls brimming with anxiety. We also attempt to highlight some of the challenges that organisations are facing with specifics on roadblocks to implementation of machine learning in the mortgage industry.
The Slow and the Furious
We are all aware of the impact of digitisation and other advancements in technology (Briggs 2017). Digitisation has dramatically changed business landscapes across many industries, yielding itself particularly useful in the home buying and owning experience. With a radical shift in favour of digital experiences, consumers are now expecting more from their choicest lenders. Digital transformation is becoming one of the top three strategic priorities for leaders at the helm of these mortgage businesses (Bookallil and Birkby 2017).
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- International Perspectives on Artificial Intelligence , pp. 23 - 32Publisher: Anthem PressPrint publication year: 2022