Tim Hood, Vice President of EMEA & APAC at Hyland
Customer experience enhancement, internal risk management, investment strategies, regulatory compliance; almost no technology is driving as swift a transformation across the banking and finance sector as artificial intelligence (AI).
AI is predominantly used in automation, alleviating the heavy lifting of menial tasks. But as it continues to evolve, the technology holds the promise of reshaping the way financial services are delivered, and it’s capable of revolutionising the industry’s future.
So, what are the sweeping changes AI is ushering into the sector – and what are the potential benefits and inherent challenges?
The evolving landscape of AI in financial services
In the banking sector, AI streamlines tasks with precision. The loan approval process is one traditionally cumbersome, time-consuming example that has been transformed by AI-driven automation. This tool can expedite decisions and lighten the load on human resources, allowing staff to focus on higher-level strategic undertakings.
A significant leap lies in enhanced security. Wells Fargo, for instance, has harnessed AI in its fraud detection unit. AI’s real-time analysis enables the identification of transactional anomalies that might elude human scrutiny – and can update its model with each result, ensuring that effectiveness doesn’t diminish over time. Coupled with advanced machine learning models, this curbs false positive identification while simultaneously improving user identity verification. Responses are faster and more accurate.
Beyond traditional banking, AI integrates seamlessly into investment banking – a fiercely competitive area reliant on analytics. The speed at which investment banks need to operate makes AI a natural fit to help the sector evolve.
Goldman Sachs exemplifies this, using AI to model stock market trends. AI can analyse and deliver information on everything from market health to share value at a rapid rate – and then automate a corresponding response, drastically accelerating an organisation’s reaction times. This is critical in a sector where mere seconds can translate to substantial financial gains.
Navigating AI concerns
While these examples demonstrate the normalisation of AI in financial services, reservations remain – especially on data privacy.
AI is inherently data-intensive. It’s only as valuable as the information it can access – and in this industry, sensitive information abounds. That makes safeguarding paramount, for fear of breaking the stringent data security and regulatory standards in the sector. Beyond huge financial penalties, these businesses would also have to battle a serious loss of public trust. Reputations take years to build, but moments to undermine.
Job displacement is another common worry, with global concern that AI will replace certain roles in the workplace. As automation absorbs more day-to-day tasks, some roles in banking and finance may become obsolete.
It’s important to distinguish between the types of jobs that are at risk, and the roles that can’t be replaced by AI. Even generative AI – one of the most compelling illusions of agency or human intelligence available to the public – is entirely dependent upon the prompt that it’s fed. AI can’t replace the creativity or intentionality of human input.
AI also brings new opportunities through new roles like data scientists and AI engineers. From model development to regulatory compliance, new positions will emerge – and businesses must anticipate this evolving landscape with investment in employee training. AI won’t eliminate humans from the workforce, but employees must know how to effectively use this new tool. Otherwise, they risk being replaced or overlooked by someone who does have this expertise.
Speaking of regulation, nascent AI will require well-defined frameworks. Staying abreast of emerging regulations such as the European Union’s AI Act is vital to maintaining compliance while navigating uncharted terrain.
With AI already so prevalent and gaining momentum, institutions should embrace these challenges. A diligent approach to security, and an understanding of how roles are going to change in a business augmented with AI, is fundamental to long-term success in the field.
AI’s potential in compliance and risk management
Although AI comes with its own set of concerns around compliance, it also proves a potent ally in adhering to financial regulations. There is an abundance of regulation that the financial sector must abide by should they wish to operate in certain countries or marketplaces.
The “Top 8” cybersecurity regulations in the financial sector include guidance or rules from the EU, UK, US and international governing bodies. Each has their own standards and guidelines – and each one addresses different aspects of cybersecurity. Amid this tangle of cybersecurity mandates, it can be difficult for organisations to ensure they are abiding by the rules.
AI can support this, monitoring for irregularities and suspicious activity to ensure stringent compliance. Morgan Stanley’s adoption of AI-enabled transaction monitoring exemplifies this proactive approach, effectively preventing fraudulent activity.
The technology further tackles financial risks, like market volatility, shielding assets and customer funds. Asset management companies are currently making use of AI to develop algorithms that automatically rebalance portfolios in real time to reduce risk and maximise returns; the Chartered Financial Analyst Institute identifies market risk and credit risk as “the most important [use of AI] in asset management… producing more accurate forecasts of aggregate financial or economic variables.” Again, this is an excellent example of AI both improving user and customer experience.
Finally, customer experience is a priority for financial institutions – without satisfied customers, there would be no business. Therefore, it’s no wonder that this cutting-edge technology is being used to enhance customer experience. AI enhances user-centric services, providing bespoke financial advice and solutions. Banking giant HSBC employs AI for enhanced personalised customer experience, providing advice based on each customer. This implementation has boosted satisfaction while trimming operational costs.
AI as an enabler of business enhancement
In essence, AI is a force multiplier that supercharges existing operations. Automating mundane tasks ensures their completion faster than any human, reclaiming the time and energy that the workforce needs to focus on intricate problem-solving and strategic endeavours.
Given its foothold in the industry, the buzz around generative AI solutions, and the spiralling volumes of data that modern businesses produce, AI’s momentum is unstoppable. As it matures, its innovative and disruptive potential will expand, opening pathways for even more transformative applications across the financial spectrum.
