{"id":9515,"date":"2023-12-14T11:52:23","date_gmt":"2023-12-14T11:52:23","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=9515"},"modified":"2023-12-14T11:52:24","modified_gmt":"2023-12-14T11:52:24","slug":"why-making-the-most-of-ai-in-banking-starts-with-the-right-humans","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/eu\/blog\/why-making-the-most-of-ai-in-banking-starts-with-the-right-humans\/","title":{"rendered":"Why making the most of AI in banking starts with the right humans"},"content":{"rendered":"\n

The banking sector \u2013 both corporate and retail \u2013 has always had a distinctly cautious relationship with technology. Technology is the key to achieving efficiencies, streamlining processes, lowering costs and, most importantly, providing a better more engaging customer experience. But every tech comes with a certain amount of risk. Banking is, of course, the art of balancing risk with potential value. So, whenever a financial institution considers adopting emerging technologies, the risk specialists get to work. And so do the regulators.<\/p>\n\n\n\n

It’s nothing new. I think it\u2019s always useful to remind ourselves that the sector has a long tradition of adopting technology focused on meeting customer needs. More than 50 years ago the rollout of the ATM is a great example. It was designed to free customers from the tyranny of banking hours. Until of course the digital revolution and the rise of mobile banking.<\/p>\n\n\n\n

What\u2019s that got to do with AI? Well, the same thought processes apply to the introduction of AI, Generative AI<\/a>, Machine Learning, and Large Language Models (LLM). Making the most of the technology demands a relentless focus on tangible benefits to the bank, its customers, and its stakeholders, linked to a clear understanding of the risks involved with reference to an ever-evolving regulatory landscape.<\/p>\n\n\n\n

But I believe that getting the right professional services professionals involved is the key to making the most of AI in banking.<\/p>\n\n\n\n

AI isn\u2019t one thing; it is many things (and it\u2019s not a person)<\/strong><\/h2>\n\n\n\n

Any casual search for the benefits of AI in all forms of banking (especially if you ask Chat GPT to do it) will come up with the same key points. AI and Machine Learning frees skilled banking staff (at all levels) from mundane, repetitive tasks whilst improving accuracy and reducing errors. That makes sense. Machines don\u2019t lose focus or take breaks. More importantly, the coming of Generative AI is adding to an employee\u2019s ability to streamline their own expertise. They can use technologies like Salesforce\u2019s own Einstein GPT<\/a> to leverage aggregated data (a task done expertly by our Data Cloud) and LLMs to rapidly generate personalised communications. It enables you to send them out automatically to match a wide range of scenarios \u2013 from investment decisions to choice of accounts. That can in turn boost employee capacity (and morale) and deliver a responsive and deeply personal service to clients.<\/p>\n\n\n\n

So, the AI in itself is not the point, it\u2019s what it does for the banker, broker, or advisor that counts. Their <\/em>capacity is increased, and their<\/em> skills are both augmented and improved. That\u2019s why Salesforce has invested significantly in AI as well as our Data Cloud. It\u2019s why we\u2019ve recently integrated with OpenAI and developed Einstein GPT. The point is to provide the range of technologies which often get lumped together under the now generic title of \u2018Artificial Intelligence\u2019 and focus them on the individuals that matter. Which are, as I\u2019ve stressed, your employees and your customers. The point is to enhance core relationships and not just automate them. Automation without true customer-centricity is a risk to your business in itself.<\/p>\n\n\n\n

Leaving it all to AI is risky<\/strong><\/h2>\n\n\n\n

As Marc Cooper, CEO of Solomon Partners, stressed in a recent Forbes article, it\u2019s important to curate how your AI learns from data. There is a risk it could just replicate the mistakes that humans have made in the past. That could lead to market volatility in certain circumstances. \u201cI do worry about the very human tendency to relentlessly push out our technology and capabilities without perfect insight into the possible outcomes,\u201d he wrote.<\/p>\n\n\n\n

For me, that\u2019s why it\u2019s important to start with the humans. To deploy the right internal and external (human) skills to ensure a successful journey into the still-developing world of AI. It\u2019s also vital to, as Marc Cooper stresses, \u2018balance risk with prudence.\u2019 And to do that it\u2019s important to engage with human <\/em>experts to map out your adoption path. That\u2019s how you can make \u2018no regrets\u2019 moves which will help you find the right solutions for your bank.<\/p>\n\n\n\n

As Dr Kate Darling, Research Scientist at the MIT Media Labstressed, machines don\u2019t perceive the world the way we do. While they can compute different scenarios based on massive amounts of data much faster than we can, they don\u2019t have the \u2018mental\u2019 flexibility to make contextual judgments that are as nuanced as those that humans are capable of. Machines are at the mercy of their algorithms until those algorithms are rewritten by people who can experience the depth and complexity of a situation.<\/em><\/p>\n\n\n\n