HM Magazine 5, Time and Technology wait for no-one, fintech, future of banking, AI

It is 2026.

You need to do your business banking. You raise your wrist, say ‘bank’ and your smartwatch scans your retina to biometrically authenticate your identity through your self-controlled Blockchain Identity Passport. This is the beginning of a technology-driven process – in the scenario below can you separate fact from fiction from this transaction?

You have given permission for the bank the access your profile which is checked annually. Passwords are archaic. Your device syncs with your smart eyeglasses and a holographic virtual assistant appears. The last time you dealt with a human at your bank was when the final local branch closed five years ago, but you are comfortable with the security of your money because of the extent of cryptography in your identity.

You would like to transfer funds to another country, and you advise the Artificial Intelligence (AI) powered Smart Bot Holographic Assistant. It feels like you are speaking to a real person and your voice is constantly authenticated and your face scanned for security purposes. A nod or shake motion detector enables you to carry out most operations. 

All data is owned by you the customer, and can be provided to all other institutions via open APIs in moments. The funds are transferred instantly because of advances in blockchain technology and settlement.

Your second financial brain

The transaction is complete. Next, your Smart Bot Personal Finance Adviser appears. On the basis of big data and deep learning capability of quantum computing learning your personal behaviours through previous account history, algorithmic personality, and current affordability, it asks you if you would like to make a further deposit as now is good time to invest. Your stocks are traded with a Robo Adviser at little cost.

You have a ‘Thin File’ credit history, but would like to arrange a business loan. A Smart Bot Loan Adviser appears. Through behavioural analytics of the ‘big data’ shared by your device, your credit risk can be evaluated through the use of profiling models to underwrite the loan request. Your loan request is accepted in moments and funds are transferred to you immediately.

The bot offers other personalised services.

It explains that it will use your previous spending data to predict the best time for you to save (and how much you can afford to put aside). It will transfer a small amount to your savings account when, according to the algorithm, you will miss it least, and sends you a message to ask if you are happy about it. If you say no, the money is instantly returned to your main account. This way, it explains, we can develop better saving habits, and remove the most difficult part of the savings equation – ourselves. You agree. 

It says that the bank has noticed that you have been using your mobile wallet a lot and asks: with Christmas coming, would you like to look at offers we have prepared for you? In moments you are skimming selected brands personally matched to your taste. You select several and your device receives the codes. The bot adds: just so that you don’t go over budget this year, would you like me to limit your spending during Christmas to the same level as 2026? You agree. It signs off with a reminder that it will contact you next month for your annual review.

Your experience has been positive, convenient and thorough. You can instantly switch providers and trust, integrity and security of your bank will always remain important to you.

How realistic is this financial scenario?

The technologies illustrated above are incremental developments of digital banking today. By 2025, millennials will make up 72% of the global workforce (Accenture 2017 report); their aspirations and attitudes will focus on platform and applications rather than products. This sea change is expected to lead to the increasing prevalence and acceleration of smart technology – reshaping the way to do business.

The disruption to current retail banks will predominantly be in diminishing their physical footprint but extending their geographical reach through digital technologies, alongside a reduction in headcount. Using data intelligently is already providing customer insights – predicted to be a focal point for differentiation. This intelligence, when applied correctly, will add value for customers by offering a truly personalised experience. For financial centres, technology has the capacity to increase revenue via access to internal and external Big Data and AI. 

The technologies are becoming a reality because of the following:

  • It is relatively inexpensive to apply technology to current friction points.
  • Technology start-ups can grow very quickly through easy access to data and strategic partnership opportunities.
  • There are many more opportunities to access growth capital today than historically.    

It is suggested that by 2025-2030, a market economy could readily exist without banks of the traditional kind (see PWC 2017: The Future Shape of Banking). The report suggests barriers to entry for technology driven non-banks to provide formerly ‘core’ banking services continues to decline, and today’s banking business model will be increasingly intermediated.

To survive, businesses must remain flexible and respond to the accelerating pace of change, driven by their customers’ expectations for convenience and appetite for new technology.

Author: Steve Barber, Managing Director of Bridging Finance Solutions. Steve is an Alumni of Oxford University Fintech Programme and holds an MBA from Henley Management School.

Is the financial technology above fact or fiction?

The majority are in development, but this brave new interconnected world is already happening in other industries.

  • Biometric identification: visual ID recognition is used by devices such as the iPhone X, for security via finger printing and voice recognition.
  • Blockchain technology: has been adopted to track supply chains such as shipping, and British Airways used the technology to manage flight data.
  • Virtual assistant: well-known examples include Siri, Cortana, Alexa and Google. The race is on to perfect a truly human-like hVA (holographic virtual assistant).
  • Smart bot: Google has developed a robot assistant using Google Duplex technology, the most human bot to date. Companies are using AI machine learning to better understand and respond to their customers.