AI and Automation: Spotlight on the Financial Services Industry
The convergence of technology and banking has contributed to a major transformation in the financial services industry in recent times. Artificial intelligence (AI) and automation are playing a major role in this transformation, and will have a significant impact on the industry in the years to come with predictions that AI technologies could deliver up to $1 trillion of additional value.
Key Drivers of Change
Several factors are driving the adoption of AI and automation in banking, including:
Slow and inefficient existing systems: Many existing banking systems are outdated, inefficient, and difficult to maintain. AI and automation can help banks to modernise their systems by automating tasks and improving decision-making.
Changing client expectations and demands: Customers are increasingly demanding personalised and convenient banking services. AI and automation can help banks meet these demands by providing 24/7 customer service, personalised product recommendations, and seamless integration with other services.
The shifting regulatory environment: Regulators are increasingly focused on promoting competition and innovation in the financial services industry. AI and automation can help banks to comply with regulations more easily and efficiently.
New entrants: Telcos and FinTech companies are entering the financial services industry with deep client networks and a strong understanding of customer needs. AI and automation can help banks compete by providing better customer service and more personalised products and services.
How AI and Automation are Changing Banking
From the introduction of ATMs in the 1960s to the rise of mobile banking in the 2010s, technology has already transformed the way we bank, and AI is now poised to make an even greater impact. Here are some ways AI and automation are already being used to revolutionise banking:
Improvements to customer service: AI-powered chatbots can answer basic customer questions 24/7, freeing up human customer service representatives to focus on more complex issues.
Integrations: Many banking apps also have seamless integration with non-banking apps, allowing customers to pay bills directly from their account, purchase and manage insurance policies and buy and sell stocks, bonds, and other investments.
Reduced costs: AI-powered automation can automate repetitive tasks, such as data entry and processing, which can lower operational costs.
Increased risk management capabilities: AI-powered risk analytics systems can identify and assess risks more effectively, which can help banks to prevent fraud and losses.
Personalised products and services: AI can be used to analyse customer data to personalise products and services, which can help banks to attract and retain customers.
Ability to fight financial crime: AI can help banks identify and track financial criminals and boost the safety of transactions.
AI-Related Challenges Banks Need to Address
Although AI and automation offer many benefits, there are several challenges that banks need to be aware of and prepared to address to ensure effective and safe adoption of AI. Some of these key challenges include:
Data privacy and security: Banks need to collect and store large amounts of high quality (and sometimes sensitive) data to train and operate AI systems, which raises privacy and security concerns both regarding protecting customer information from cyber-attacks and breaches, and ensuring it remains accurate and up to date.
Job displacement: As AI and automation become more widespread, there is a risk of job displacement particularly for customer-facing jobs like customer service representatives, bank tellers, lending officers, investment advisors, compliance officers, etc.
Regulatory challenges: The adoption of AI technologies in banking raises many questions around transparency, accountability, and legality that need to be addressed (see the following link for a risk-based taxonomy of AI applications in banking supervision).
Ethical considerations: AI systems can be biased, which can lead to unfair or discriminatory outcomes. Banks must take steps to ensure their AI systems are transparent and free from bias.
Virality of information: When information moves fast, it can create both threats and opportunities for banks. For example, social media can spread misinformation at speed, which could cause a run on the bank. However, it can also speed up the finality of transactions, improving the efficiency of customer service.
Reduced human-to-human interaction: While task automation can improve efficiency, reducing the need for human-to-human interaction comes with several costs, including reduced customer satisfaction (some customers prefer interacting with people rather than a chatbot, which are often only useful for solving simple questions rather than complex issues), increased risk of fraud (fraudsters can more easily impersonate bank employees and trick customers), and reduced employee morale and productivity through fear of job replacement.
The Future of AI and Automation in Banking
AI and automation have the potential to revolutionise the banking industry, making it more efficient, secure, and customer centric. In the next few years, we are likely to see further advancements and widespread use of AI-powered fraud detection systems, risk-analytics systems, investment advisors, and compliance systems. Clearly, to remain competitive, banks need to find ways to use AI and automation to their advantage, while still providing human interaction that many customers value.