AI and the future of banking
September 7, 2020

Thinking about AI and the Future of Banking with Tony

By Paul Laughlin

How can data leaders working in banks prepare their colleagues for the impact of AI and the Future of Banking?

So much published on this topic tends to be superficial. A few successful pilots or use cases here, a speculative futurology crystal ball session there. In particular, the focus tends to be on technology, with the industry to be transformed almost added as an afterthought.

So, it has been a pleasure to read the much more considered & broader view shared by Tony Boobier in his latest book “AI and the Future of Banking“. Regular readers of this blog will recognise Tony’s name as a regular contributor here. I’ve also previously praised his prequel, “Advanced Analytics and AI“.

His previous book was focussing on a broad view of how AI might transform the world of work across many sectors. In this one, he dives deep into banking and in so doing reveals the thinking that is needed by leaders.

What to consider about AI and the Future of Banking

This is a well-researched book. Tony is to be commended on both the frequent examples of research & case studies cited, plus the supporting material included so you can continue your own learning. Each chapter concludes with at least a couple of pages of references. That alone would make this a useful textbook for students of Banking.

As well as citing quotes from industry leaders & case studies throughout, Tony also includes a 22-page appendix. Many data leaders working in Financial Services may find this useful, as it is a list of FinTech companies that are ‘making an impact‘. Tony covers a broad range of functions & banking sub-sectors in this handy list.

However, my main praise for this book is the focus it gives to understanding Banking and the other forces driving transformation. In the very structure of this book, Tony avoids the temptation of being overly focussed on AI or technology as the whole story. He includes chapters covering:

  1. Understanding & purpose of Banking
  2. Imperatives (need for change) in Banking
  3. Data & Analytics in Banking overview
  4. Key elements of Banking Analytics
  5. Machine Learning, AI & Apps
  6. AI & the importance of Brand
  7. AI Leadership & Employee transformation
  8. The Bank of the Future
  9. Open Banking & Blockchain
  10. Innovation & Implementation
  11. CyberCrime & IT Resilience

Don’t overlook the Leadership & Implementation aspects

I mentioned above that I praise this book for focusing on understanding the business domain being transformed by AI. A previous post shared the importance of analysts having strong domain knowledge, the same is true for leaders of digital or AI transformation. For that reason chapters, 1, 2, 6 & 8 of this book should be required reading for technology leaders in banking.

It is also so important to learn from the history of implementing technological change. Time and time again such projects fail because of insufficient focus on two elements, effective leadership & understanding implementation challenges earlier. That is why chapters 7 & 10 are also so important.

Not only will AI-infused organisation require different types of leaders (and employees), but what’s needed should be understood by those leading AI change. In chapter 7, Tony rightly explored the leadership approach needed to blend risk-averse compliance with the competencies for innovation.

Building on this, chapter 10 explores how different models for innovation & how to avoid frequent blockages. Once again this could be seen as a distraction from a focus on AI technology, but it is a key requirement to delivering change. I also praise the focus on execution. Good to see the role of Design Thinking acknowledged. Plus, a number of the changes identified for successful implementation reminded me of the principles in “The 4 Disciplines of Execution“.

Consider multiple technological changes not just AI

Just as some reviewers may not approve of the ‘distraction’ from AI of the above focus on business & leadership, some may not agree with other chapters. In chapter 9, Tony focussed on the global potential of blockchain to transform Banking, together with the Open Banking regulation. In chapter 11, he focusses on Cyber Security & legal risks.

In both cases, I agree with this ‘distraction’. Tony rightly (in my view) avoids the reader myopically focussing on solely AI. The reality for today’s banks is it is not the only technological innovation driving change. The potential of the distributed ledger approach of Blockchain, together with the increased need for more robust cybersecurity are but two examples.

Leaders in banks do well to step back and still consider the classic strategic tools when preparing to think well about transformation. A well thought through PESTLE analysis & Porter’s 5 forces exercise will always identify multiple drivers of change. Plus, as Tony rightly highlights, the convergence of Blockchain + AI and AI-enabled Cyber Security make possible better solutions.

How are you preparing for AI and the future of Banking?

So, if you are a senior leader in Banking today, I recommend both reading Tony’s books and taking time to note your reflections. Once again the structure of this book supports such annotation & pauses. Each chapter has a brief introduction of what to expect and a conclusion that reflects on what to consider.

So, what are you going to do as a result? If you work in banking, using this book as a source to prompt your own further research & thinking makes sense. If you work in other sectors, could you use the structure of this book to prompt you what else to consider? Because successful transformation by deploying AI are never just about AI.