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In pursuit of AI perfection - it could be a long wait!

A recent report from the Artificial Intelligence (AI) Index, assessing progress being made in AI technology, states: “There’s no question there have been a number of breakthroughs in recent years… but it’s also clear we are a long way from artificial general intelligence.”

Despite being in its infancy, conversations surrounding AI’s potential to revolutionize business have exploded. A technology both revered and scrutinized for its potentially limitless use cases, many financial services firms are now experimenting with or using AI and machine learning to some extent in their business strategy.

But those waiting for perfect AI solutions will be waiting a long time. The reality is that AI isn’t perfect, and probably never will be. In the same way as us humans are constantly learning, so too it’s natural for AI systems to be in a constant state of knowledge processing.

Banks should start reaping the benefits AI can already supply, and not hold back on the basis that it’s not perfect. While AI won’t change a bank’s business overnight, it’s important to start experimenting with the technology now.

Step one for those experimenting in AI is to establish who will own it and drive the AI strategy across the business. Responsibility could fall to the Chief Digital Officer, Chief Marketing Officer or Chief Customer Experience Officer. But it’s essential they develop a clear end-to-end AI strategy to boost success.

Below are some “quick wins” I believe banks can benefit from when it comes to AI:

1. Customer experience

Differentiation in such a competitive industry demands more tailored, personalized products and services, using data collected from across a bank. One immediate use case, and in my opinion one of the most important, is in using AI-enabled interaction for improved customer experiences. Using AI, not only can banks increase the efficiency of their customer interactions, but it will allow them to provide a more consultative offering to their customers.

2. Customer service

With regard to customer service, applications of AI can vary from an intelligent robo-advisor for investors to efficient, chatbot-enabled onboarding services for a bank. Such implementations can allow for quick responses to FAQs and simple customer queries, providing relief for the back-office and enhancing efficiency around customer service. For the bank, AI can give time back to customer service staff to tackle more strategic tasks that require human input. AI will, in most cases, be a technology that’s used to complement human activity, not replace it.

3. Detecting errors & fraud

Stepping into the back-office, many banks are already implementing AI for fraud detection or AML purposes – monitoring and reporting on suspicious behaviour to help avoid hefty compliance fines. AI can also help detect so-called ‘fat finger’ errors before a trade is even processed, meaning banks can avoid significant losses. The same technology can also prevent such errors from occurring again, as even seemingly minor errors in the fast-paced trading environment can cost banks a huge amount of capital.

4. Supporting workflow

Back-office workers in a bank can often be stalled with banal, process-driven tasks that take time away from more strategic ones which would better benefit the bank. AI can support several processes via mass automation of document and data processing. This doesn’t just add value by easing back-office work, but allows staff to focus on more valuable tasks which require a personal touch, potentially freeing up as much as 80% of their time.

Over the course of the next 10 years, banks will be seen more and more as commodity service providers, like electricity, internet or telco suppliers. In this respect it will be vital for them to seek and use AI to differentiate themselves through better customer service and convenience offerings, or risk being left behind.


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