Exploring The Future of Finance
Artificial Intelligence in Banking
July 10th 2024 | Authored by: Cyder
Artificial intelligence (AI) is transforming the financial services sector. Financial institutions are adopting AI into their operations on a global scale, with 45% of financial institutions having integrated AI into their available technology stack, and 30% being in the early stages of implementing AI solutions.
AI is causing major shifts in banking. But this shift goes beyond organizational changes; AI impacts the entire financial landscape. New technology means new competition. Emerging fintechs are also leveraging AI to push the financial landscape forward and develop innovative products that make people’s lives easier. Fintech’s popularity positions it to grow to a $1.5 trillion valuation by 2030, five times today’s valuation.
Across the globe, millions of people are switching to fintechs to manage their daily finances. Over half (55 percent) of U.S. citizens rely on fintech tools, according to Plaid. In addition, trust in fintech applications is growing and will continue to grow as governments worldwide introduce open banking systems.
When factoring in AI, fintechs provide many opportunities that help consumers navigate their financial lives. Banks and other traditional financial service providers need to keep up with innovation trends and leverage AI to remain competitive.
The financial sector’s spending on AI is expected to increase to $97 billion over the next three years. This is a massive investment that will bring immense changes to banking and ultimately shape the future of finance.
Defining Artificial Intelligence
Artificial intelligence (AI) refers to any machine learning algorithm that can simulate human intelligence to solve problems. AI can be programmed to perform a variety of tasks to achieve a specific goal. AI algorithms are powerful prediction machines capable of analyzing vast amounts of data.
Recent developments in AI go beyond data analysis and prediction. Now, AI can create new content altogether based on prompts or input. The rise of generative AI (or Gen AI) pushed AI into the public limelight, sparking discussions, concerns, and opportunities surrounding its use.
Generative AI refers to AI algorithms that can create content. Examples include large language models (LLMs) ChatGPT or image generators like MidJourney. Gen AI is trained on vast amounts of data, and similar to its prediction-based predecessors, it can act on a string of predictions in response to a prompt and generate original content.
In banking, AI brings massive opportunities to boost efficiency and improve services, primarily by making things faster and reducing room for errors. Generative AI has the potential to automate repetitive and time-consuming tasks that make up 25 percent of an employee's work time. Automated tasks include anything from fraud prevention, financial planning, chatbots, investment support, and personalized banking.
The Banks of Tommorow
Future banks will adopt and integrate AI into their daily operations. Beyond automated systems, employees will use AI daily to optimize their workflow.
Marketing
Marketing departments across the financial sector will use AI to power the creation and execution of marketing campaigns. AI can generate compelling copy, design eye-catching images and templates, and recognize patterns in consumer behaviour.
Marketing teams will be able to produce content much more quickly and efficiently, continuously optimizing campaigns in real time through constant A/B testing. This will ensure that marketing efforts have higher success rates of reaching and converting target audiences.
Analytics
AI can process large amounts of data and predict a customer's next move. This helps banks analyze and understand their customers' financial behavior, allowing banks to improve customer experience by offering personalized financial advice, product recommendations, and targeted offers to individuals.
Scotiabank leverages AI analytics to provide customers with tailored, personalized services that increase customer retention. The bank achieves this by constantly analyzing customer data to determine the best advice possible for a specific customer.
Fintech Partnerships
Banking will be shaped by strategic partnerships between traditional banks and fintechs. Collaborating with fintechs provides opportunities for both entities to innovate and expand their offerings.
Partnerships between banks and fintechs will increase in popularity as the competitive landscape changes. Open banking systems will likely be implemented or in the process of implementation, leading to more common data transfers between banks and fintechs.
Banks are also acquiring and investing in fintech platforms that benefit their operations. In addition, many banks have in-house accelerator programs that help launch and connect emerging fintech startups with funding and growth opportunities.
The Customers of Tomorrow
As AI use continues to grow in banking, customers will engage with a new era of financial products and apps that are more personalized, efficient, and accessible. AI-driven products will reshape the way customers interact with their banks, providing a seamless and highly customized experience.
AI will significantly enhance customer service in banking. AI-powered chatbots and virtual assistants will become the first point of contact for many customers, handling inquiries and resolving issues with remarkable speed and accuracy. These intelligent systems will be available 24/7, ensuring that customers receive immediate assistance regardless of time or location.
The Bank of America created a chatbot for mobile banking that has helped over 98 percent of customers get the exact answers they need. The large language model (LLM) is an AI virtual assistant capable of responding to customers' individual needs and concerns.
Customers will also receive AI-powered personalized financial advice from their banks. This will improve their financial well-being and strengthen trust between customers and their banks. AI-powered financial advice can offer tailored recommendations that help customers make informed decisions on saving money, investing, and budgeting.
Fintech applications will further enhance the banking experience. These apps will offer features such as real-time spending insights, automated budgeting, and personalized alerts for unusual transactions or opportunities for savings.
Open banking will play a large role in customers' financial journeys. Customers will have access to a broader ecosystem of fintech apps that integrate seamlessly with their bank accounts.
Customers will benefit from various fintech apps for needs like peer-to-peer payments, investment tracking, and personalized budgeting while still maintaining their primary bank relationships. This interconnected ecosystem will offer greater flexibility, control, and access to a wider range of financial services and features.
Risks and Regulations
AI is only as good as the data it is trained on. Data is information created by humans, which ultimately has bias. The future of AI development will have a heavy emphasis on ensuring that AI algorithms remain as unbiased as possible and respect the individual's right to privacy.
Beyond financial institutions, governments worldwide will outline and enforce legislation concerning the responsible and ethical use of generative AI. For instance, the White House released a blueprint for an AI Bill of Rights, containing guidelines that ensure AI remains safe, free from bias, and accessible to the public. Governments are also investing in AI research, innovation, and development, increasing their focus on ensuring AI systems operate transparently and safely.
Implementing effective AI systems requires high-quality and ethically sourced data. Ethical data collection practices ensure that AI systems are reliable and unbiased.
Preparing for the Future
Integrating artificial intelligence (AI) into banking is reshaping the industry. To prepare for the future, banks must develop a clear and strategic roadmap to AI integration. Thriving means banks must focus on AI ethics, customer experience, partnerships, and quality data sourcing in their AI integration efforts.
AI Ethics: Banks must ensure that their AI systems are transparent, fair, and unbiased. This involves developing ethical frameworks (or using existing frameworks) that guide the design, deployment, and monitoring of AI technologies. Banks should prioritize transparency by making AI decision-making processes understandable to the public.
Customer Experience: Enhancing customer experience should be at the heart of any AI strategy. Deliver personalized, efficient, and seamless services that meet the evolving needs of customers. AI-powered chatbots and virtual assistants can provide instant support and resolve customer queries in real-time. This will improve service accessibility and reduce wait times. Personalization through predictive analytics can offer tailored financial advice, product recommendations, and customized offers, fostering stronger customer relationships. By focusing on creating a superior customer experience, banks can differentiate themselves in a competitive market and drive customer loyalty.
Fintech Partnerships: Partnering with fintech companies is essential for banks looking to thrive in the AI-driven future. It allows banks to tap into innovative solutions that enhance their services. As open banking is implemented, more consumers will prefer variety in their financial products. This will push banks to work with fintechs. Embracing these partnerships will allow banks to expand their services and retain an increasingly fragmented customer base.
Quality Data & Consent: Successful AI requires quality data. Banks must focus on ethically collecting, managing, and utilizing high-quality data to train their AI models effectively. As data ownership becomes more mainstream, banks will have to create avenues for ethically sourcing data in compliance with privacy laws.
How AI is Used Today
Personalized Mobile Banking: TD Bank uses data analytics and AI to deliver personalized mobile banking suggestions to its customers. By analyzing customers' past behaviors and transaction patterns, TD’s mobile app can alert them when they are likely to hit a low balance, helping them budget for upcoming payments and plan for their financial obligations.
Ad Optimization: ArtsAI uses artificial intelligence and predictive analytics to optimize messaging for the best business results. The ad tech startup can automatically determine which combination of messaging has the highest success rates for reaching different customers
Real-time Insights: The need for quality data is growing, but data is becoming increasingly difficult to source. Cyder helps financial institutions (FIs) ethically source real-time data, allowing FIs to know the exact moment a customer shows interest in a product. This enables banks to instantly send tailored messages to their customers the moment they show interest in a financial product.
Get Real-Time Customer Insights With Cyder
If you're looking to thrive amidst a changing data landscape, Cyder can help. We encourage you to book a one-on-one demo today with Cyder’s data experts.
July 10th 2024 | Author: Cyder
