Key Takeaways
- The use of chatbots has improved the customer experience, using predictive analytics and behavioural biometrics to provide support at a much faster rate than workers can.
- AI and the use of machine learning has provided many banks with an answer to the growing threat of cyber-attacks, which have become increasingly complex and frequent since the COVID-19 outbreak.
- European banks struggle to keep pace with their American counterparts when it comes to implementing AI, reacting slowly to the digital advancements seen since the financial crisis.
Artificial Intelligence (AI) is at the forefront of innovation within the banking and professional services world, being leveraged by companies everywhere to spearhead their digital transformation. Even so, its true potential is yet to be seen, as banks have only just started to integrate AI systems into their activities.
ChatGPT’s historic launch in November 2022 gives the perfect example of how influential AI-powered systems can be for the world; it already boasts over 100 million users, having become the fastest-growing app ever.
ChatGPT’s launch has sparked widespread debate on how much of an advantage AI can offer for the customer experience and operational capabilities.
AI is set to provide one of the largest growth opportunities for the UK’s banking sector, outlined by the sector’s sizeable investment in and quick integration of AI-led systems. Prominent examples of AI tools already used in the banking and professional services include generative AI, robo-advisers, predictive analysis, cybersecurity and fraud detection tools.
AI tools help banks enhance the consumer experience
Banks in the UK continue to ramp up spending on AI to meet ever-growing client needs, with AI systems allowing them to enhance customer experience in a variety of ways.
Chatbots and robo-advisers have provided valuable improvements to the customer experience, providing clients with tailored support services at a much faster rate than traditional banking services. Chatbots use predictive analytics and behavioural biometrics to provide banks with more informed decision-making insights while streamlining time-consuming tasks.
AI’s uses in marketing, PR and social media have already proved transformative, indicating that the next step in banking clearly involves significant integration of AI tools. The rise of financial technology (FinTech) services has further urged banks to undergo digital transformation, as these firms have already implemented AI and machine learning tools into their operations at scale.
Improvements to operations
As banks continue to jump on the AI bandwagon, not only are they aiming to improve their customer experience, but also their operational capabilities.
Before the creation of AI, the finance sector was rife with human-based tasks that accumulated an eyewatering amount of paperwork, giving rise to human error.
Banks are now beginning to see the benefits that can be drawn from using AI – in this case, robotic process automation (RPA). RPA mimics rules-based digital tasks performed by humans and removes the error-prone work of entering customer data from contracts. This leaves less room for mistakes and reduces costs, aiding profitability.
On the analytical side of finance, AI has allowed banks to process larger volumes of structured and unstructured data, resulting in more accurate predictions of trends and greater investment opportunities. Data-driven decision-making helps reduce costs and boost productivity.
Another exciting area of development is the use of AI in fraud detection.
The COVID-19 outbreak marked a seismic change in the world of digital transactions, triggering a shift in the frequency and sophistication of fraudulent activity. Banks have turned to machine learning to protect themselves from such threats, which, instead of operating based on unchanging protocols, can learn from its own analysis. In other words, machine learning takes into account past transactions and applies them to future analyses to detect banking fraud.
According to fraud prevention company GBG, machine learning being used alongside rule-based fraud systems improves accuracy by 30%, allowing for complex financial crimes to be detected.
With such obvious benefits from AI implementation, banks across the globe have been pouring money into making themselves AI-ready. The Evident AI Index provides a ranking for the overall AI maturity of the largest banks in the US and Europe. Comfortably at the top of that list is JP Morgan, which is unsurprising given one of the bank’s core pillars is investing in data, AI and machine learning.
JP Morgan hopes to generate US$1.5 billion (£780 million) in value through AI by the end of 2023.
The top of the Evident AI Index is dominated by North American banks, with European banks monopolising the latter half. This has undoubtedly made many European banks sweat, given they were already at risk of falling behind their American counterparts and this difference in AI readiness is only going to widen the gap.
Final Word
As much as AI has already changed banking and the wider financial services sector, there’s undoubtedly plenty more change to come as other banks follow JP Morgan’s lead and see the benefits that come from being at the forefront of this innovation.
With experts believing human-level AI could be feasible within 100 years, the possibilities are endless and, frankly, difficult to predict given the rate it’s developing at. In fact, we’ve already seen a portfolio of stocks picked by ChatGPT rise by 4.9% in the 8 weeks since its creation, compared with an average loss of 0.8% for the 10 most popular funds on Interactive Investor.
With so many unknown variables at play, it’s not surprising that regulatory bodies like the Financial Conduct Authority (FCA) are working hard to transform and keep pace with the evolving finance industry to make sure there aren’t any unanticipated repercussions from implementing AI. For the UK, this involves establishing six cross-sector principles that focus on “high-risk” AI.
This sets the scene for an exciting finance sector in the coming years as we see not only how banks use AI to better their own operations, but also how they respond to the changing regulatory landscape. With this comes a difficult job for the FCA – it needs to find the balance of promoting innovation while safeguarding against unwanted consequences.
Read our article on how AI could affect education, law and IT companies.
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