There’s no doubt about the huge potential and possibilities of Generative Artificial Intelligence (AI) such as ChatGPT in financial services, digital banking and conversational banking in particular. AI is already used in digital banking to improve the customer experience, automate processes, and reduce the risk of fraud. But the hyper-personalization of banking opens up even more incredible prospects for customer experience.
Post by Alex Kreger, financial UX Strategist/Founder of the UXDA
In just two months after its launch, GPT-3-powered ChatGPT has reached 100 million monthly active users, becoming the fastest-growing app in history, according to a UBS report. ChatGPT is a language model that uses natural language processing and Artificial Intelligence (AI) machine learning techniques to understand and generate human-like responses to user queries.
I compare Generative AI appearance with the launch of the internet, in terms of impacting the future of humanity. It enables machines to understand and generate language interactions in a revolutionary way. GPT (Generative Pre-trained Transformer) AI has the power to disrupt the way we engage with technology, much like the internet did.
What is Generative AI in banking and finance industry?
Generative AI in banking and finance use neural networks and machine learning to identify the patterns and structures within existing data to generate human-friendly responses to a user request. Generative AI ability to leverage unsupervised or semi-supervised learning for training allows quickly leverage a large amount of unlabeled data to create foundation models. Such models as GPT-3 and Stable Diffusion used to perform multiple tasks that include text, images, sounds, animation, 3D models, or other types of data. Multimodal Generative AI systems can take more than one type of input, as GPT-4 accepts both text and image inputs.
Notable generative AI systems include ChatGPT (and its variant Bing Chat), a chatbot built by OpenAI using their GPT-3 and GPT-4 foundational large language models, and Bard, a chatbot built by Google using their LaMDA foundation model. Other generative AI models include artificial intelligence art systems such as Stable Diffusion, Midjourney, and DALL-E.
It’s only been two months since the launch, but we can already see how much ChatGPT impacts user experience. The internet is full of examples of crazy prompts, to which ChatGPT provides accurate and competent answers. People are rapidly adopting ChatGPT power to leverage their regular work. It has already become a personal AI assistant and advisor for millions of content creators, programmers, teachers, sales agents, students, etc.
ChatGPT has shown the benefits of using Generative AI in terms of customer experience, and the big names are already declaring the launch of rival AI GPT solutions. And the main question for me, as a financial UX strategist, is how AI technology will impact the banking and financial customer experience.
Customer experience is the key to business success in the digital age. According to a North Highland survey, 87% of business executives perceive CX as a top growth engine. Harris Interactive research, in 2022, showed that almost 4 out of 5 respondents would quit a brand to which they are loyal after three or fewer unsatisfactory customer encounters. According to an Accenture study, 91% of consumers are more likely to buy from brands that identify, recall and provide relevant offers and recommendations.
To secure a primary competitive advantage, the customer experience should be contextual, personalized and tailored. And this is where AI will become the breakthrough technology to ensure it. According to Temenos, 77% of banking executives believe that AI will be the deciding factor between the success or failure of banks. According to the McKinsey Global AI Survey 2021, 56% of respondents report AI usage in at least one function.
We can forecast that Generative AI technology will impact the customer experience in the banking industry in several ways.
First, it can analyze customer data to understand their preferences and needs, and use this information to provide personalized customer service and support to users, addressing their queries and concerns in real time. It could include customized financial advice, targeted product recommendations, proactive fraud detection and the reduction of support wait times to zero. Generative AI can guide customers through onboarding, verifying identity, setting up accounts and providing guidance on available products and services.
Second, Generative AI can automate many routine tasks, such as account balance inquiries and password resets, freeing customer service representatives to focus on more complex issues. It can increase efficiency and reduce costs for banks while providing faster and more accurate customer support, allowing banks to avoid the need for large customer support teams. And all of this would be available 24/7, making it easy for customers to get help whenever needed by answering questions, resolving issues and providing financial education outside of regular business hours.
Third, Generative AI can provide a conversational banking experience, integrating with banking applications to provide a single point of contact for users to make transactions, view account information and receive alerts through the chat or voice interface in multiple languages. It can simplify the user experience and reduce the complexity of banking operations, making it easier for even non-native speakers to use banking and financial services worldwide.
Generative AI in Banking Supercharges the Future
The banking industry has been pressured to adapt new technologies for some time now. The growing pressure from competition with Big Tech companies and the emerging number of Fintechs was largely accelerated by the impact of the pandemic, leaving no choice but to take immediate action.
It’s clear that the explosive growth of the challengers’ customer base depends on the ability to remove obsolete practices and adopt a new, user-centered approach to doing business by adjusting to growing customer needs and digital tendencies.
In fact, when it comes to a competitive threat, 50% of bankers would consider PayPal and ApplePay, while 34% name the Big Tech firms like Google, Facebook and Alibaba, according to The Economist Intelligence Unit.
Sixty-six percent of banking executives say new technologies will continue to drive the global banking sphere for the next five years. They point toward AI, machine learning, blockchain or the Internet of Things (IoT) as having a significant impact on the sector, according to Temenos.
As the number of advanced technological solutions of data processing and personalization through AI are becoming more and more accessible, it is broadening the opportunities financial institutions (FIs) can offer their customers. The question is how well will these be executed?
“The number one bank in the world will be a technology company,” as Brett King, Fintech influencer, author and futurist, predicted. It’s true. The banks of the future need to become digital and create their digital strategies accordingly. It’s unimaginable that a digital company would be slow in adapting to technological advancements.
According to Temenos, 33% of bankers are currently using banking AI platforms for developing digital advisors and voice-assisted engagement channels. The superpowers of AI also uncover the benefits of increased productivity, customer retention, risk assessment, prevention of fraud, improved processes for anti-money laundering (AML) and enhanced know-your-customer (KYC) regulatory checks.
The impact of AI on customer experience (CX) in the banking industry is significant. Generative AI technology has the potential to revolutionize the way banks interact with their customers, providing more personalized, efficient, and secure services. There are multiple potential benefits to using AI in digital banking, including:
Personalized financial advice
AI can be used to provide personalized financial advice and recommendations to customers, based on their individual data and preferences. This can help customers make more informed financial decisions, and potentially improve their financial well-being.
Automated customer service
AI-powered chatbots can provide fast and accurate responses to customer queries, freeing up human customer service representatives to handle more complex issues. Virtual assistants can provide personalized support to customers, answer their questions, and assist them with tasks such as making transactions or managing their accounts.
AI can help identify potential fraud by analyzing large amounts of data and identifying patterns that may indicate suspicious activity, and take appropriate action to prevent losses. This can save time and resources for the bank, and reduce the risk of financial losses.
AI-powered natural language processing technology can be used to automatically analyze and understand large volumes of customer feedback and other unstructured data. This can provide valuable insights for banks, helping them to improve their products and services and make more informed decisions.
AI can be used to analyze historical data and make predictions about future customer behavior, which can be used to optimize products and services.
Generative AI can help banks to identify and manage risks by deeply analyzing big data and providing insights in real time that is not possible for humans and modern systems.
AI will help to enable banking operations using alternative interfaces, such as voice, gestures, neuro, VR and AR in Metaverse. This will allow the implementation of banking solutions into different experiences.
Main Outcomes of Using Generative AI Solutions in Banking
1. Increased Workforce and Cost Efficiency
Many banks clearly know what they aim to achieve from Generative AI, not only in terms of increased customer satisfaction but also in productivity and efficiency.
It’s predicted that, in the upcoming years, Generative AI will completely replace most of the jobs in banking and other industries. Generative AI software would only require some regular maintenance as opposed to vacations, breaks, the risk of human error and the demand for raises. Banks are already seeking ways to optimize the capabilities of Generative AI chatbots and voice assistants so that it would be possible to solve almost any customer inquiry without a living person in sight.
For example, CaixaBank of Spain is using AI to process over 12,000 transactions per second in peak hours and boasts a 900 terabytes data pool to improve the customer experience. The bank’s 100-strong business intelligence unit uses big data, AI and machine learning to communicate with customers more efficiently. As a result, branch staff levels are half the eurozone average and CaixaBank’s costs are the lowest of its domestic peer group.The Economist Intelligence Unit & Temenos study
Even though many traditional professions are being gradually replaced by machines, as long as there will be a need for empathy, there will be jobs for emotionally intelligent people.
It’s essential to note that the essence of a new technology like Generative AI is to ease our lives, so it’s very important that the innovations are easy to understand and use by the majority of non-tech-savvy customers. To ensure that, it’s not enough to have brilliant engineers with a highly developed IQ.
There is a need for highly emotionally intelligent people who serve as translators between customers and the complexity of the opportunities uncovered by new technologies.
This explains why the demand for digital banking CX/UX experts is rapidly increasing. They are the user advocates that ensure a user-centered approach in digital product development.
What differentiates robots from people is the ability to feel emotions and empathy toward one another. This means that, while future technology might uncover superpowers for mankind, it’s up to the actual people behind the machines to determine the success of the outcome.
The other side of the coin is how the skills and capabilities of the professionals who will remain in their places will be enhanced by the power of Generative AI. There’s no doubt that the speed and efficiency of the daily duties of a UX architect or a designer, for example, would skyrocket, as the AI would sort huge amounts of available data to offer a selection of best choices for the UX expert to make a decision.
2. Champions in Personalization Skyrocket Customer Experience
According to Wunderman’s research, 79% of customers in the United States are certain that brands should demonstrate understanding and care toward their customers, and 89% are willing to engage with businesses that not only show care but go above and beyond that.
It’s true that the key to becoming a successful financial company post-COVID is having 100% focus on solving the customers’ problems in the most effective way possible, instead of following a standardized scenario.
It requires true empathy toward the customers─getting to know them, feeling their pain like your own and delivering a solution that will make their lives better and easier. This calls for personalized, contextual banking experiences.
In the digital age, the one-size-fits-all approach no longer works as customers demand and are surrounded by a more personalized experience. As conducted in a study by Wunderman, 63% of consumers state that the best brands are the ones that exceed expectations throughout the customer journey. The best way to exceed expectations and show customers that the financial brand cares about them is by offering a true value and benefit that is tailored to the specific needs the customers face.
Using big data and Generative AI assistants, people will be able to get hyper-personalized insights and recommendations on how to improve their financial health and what products they might want to consider even before they have thought of it themselves.
3. Possibilities of Personalized, Contextual Financial Products
Personalized, contextual financial products powered by Generative AI technology should:
- inform the users about any situation that requires their attention;
- help to improve users’ financial health by monitoring it and providing recommendations;
- make financial forecasts and offer uniquely crafted possibilities according to the user’s specific needs and goals, in a specific context;
- in the near future, it should also enable the users to conduct financial operations using voice processing, gestures, neuroscience, VR and AR.
A financial or banking app that provides a contextualized Generative AI experience should be able to predict the exact moment when a user needs a specific product and provide it by combining big data with behavior-based predictive analytics. The data already available to the incumbents could be used to provide personalized offers based on the user’s purchasing and financial behavior even before the user has requested it.
This would provide not only an amazing experience for the users but also a key factor that so many financial services of today lack─speed.
4. Contextual, Personalized Offers Instead of Annoying Ads
The mobile apps and websites of many FIs are often loaded with redundant promotional information about the FI itself and the benefits of its products and services. But, if this specific information is not relevant to the customer, it just becomes annoying and creates a feeling of pushiness.
Users forget information but remember experiences, and experiences are created from emotions. This means that information should be integrated into a context of usage.
It should become an organic part of the banking user experience. Personalized offers created by Generative AI allow connections with customers on an emotional level, rather than annoying them with tons of useless product description and information overload.
One of the most powerful features that digital banking Generative AI can provide is personalized promotions. This can be ensured by using predictive analytics.
It should combine analysis of the user’s financial activity, their social environment and big data analysis on typical behavioral patterns, geolocation data and contextual analysis.
For example, location-based push notifications about the location of local ATMs may appear when the user crosses the border. Purchasing a flight ticket could be a good chance to offer an insurance policy for travel. Child expenditures or maternity grants detected by the banking Generative AI could become an ideal reason to offer a loan on increasing the living space.
In the future banking marketplace, users don’t have to browse a long list of financial products. Instead, using Open Banking APIs, Light Bank itself will choose the right solution from hundreds of products delivered by third-party providers. Artificial Intelligence prepares a pre-approved personalized offer in just a few seconds by scoring users’ financial profiles.
The future banking user experience should be fully personalized and able to come up with solutions that fit each customer’s specific needs in specific circumstances, right when the customers need it.
To provide customized proposals for each customer, AI could be used for a more accurate customer credit scoring based not only on the user’s bank’s profile and credit history, but also social profiles and offline activity. This would allow the bank to generate a personalized proposal even before the user has requested it. All that the customer has to do is choose the proposal that best fits his/her needs and tap a single button.
5. Generative AI Requires Human-Centеred Culture and Strategy
The Generative AI possibilities are great, but, in the end, its potential boils down to one central aspect─the shift of the company’s culture and mindset.
The huge force powered by the technology of AI can either make our lives better than ever before or result in disaster. This could happen if AI is integrated without a sharp focus on human centricity.
There are already concerns among customers about how AI technologies will use their data and whether it is safe. According to The Economist Intelligence Unit & Temenos study, 34% of customers are concerned about the lack of clarity surrounding data use, while 40% were concerned about the security of their personal financial information.
There’s also uncertainty within the leadership of organizations. According to a report by Board Agenda, 78% of board chairs, directors, CEOs, CFOs and other executives could not confirm that the board and senior management sufficiently understand the implications of AI for the business and industry, including its impact on society or geopolitics.
Many executives emphasize the main business gains of AI, such as cost savings and efficiency, while 76% are concerned that “the use of AI in the firm will introduce significant ethical or cultural changes within the firm that will need to be carefully managed.”
It’s clear that many organizations and their leaders lack clarity on the matter, as well as the knowledge and skills to ensure a successful AI integration that would truly do good. What can be done about it?
Main Use Cases of the Generative AI in Banking
Despite the inspiring prospects that Generative AI technology opens up for improving the customer experience in banking, implementing Generative AI into banking products can pose some challenges. One of the main challenges is safeguarding the security and privacy of customer data. Banks must ensure that the chat interface is secure and that sensitive data is protected from unauthorized access or disclosure.
Another challenge is training Generative AI to understand the language and terminology specific to the banking industry. Banks must provide relevant training data and integrate the model with their existing systems to ensure that it can provide accurate and appropriate responses to user queries.
And the last challenge is customer adoption. Banks need to ensure that customers are aware of the chat interface and its benefits, and are comfortable using it. It requires additional product design and education efforts to provide an easy-to-use chat interface to demonstrate its benefits to customers.
By leveraging its natural language-processing capabilities and understanding of customer data, Generative AI technology can become an excellent solution to provide a more personalized, efficient and convenient user experience in banking and financial services.
There are 10 obvious use cases for Generative AI in banking:
1. Account inquiries
Banking users can employ chatbots to monitor their account balances, transaction history and other account-related information.
2. Money transfers
Users can make fund transfers to other accounts or to pay merchants through chatbot.
3. Loan applications
Generative AI chatbots can assist users in applying for loans and guiding them through the application procedure.
4. Credit score monitoring
Generative AI chatbots can assist users in checking their credit ratings and provide advice on how to improve them.
5. Financial advice
Generative AI can analyze complex financial data and identify patterns and correlations to provide investment or other financial advice and assist users in making informed financial decisions.
6. Fraud prevention
Generative AI can assist banks in preventing fraud by monitoring user transactions and spotting unusual activity.
7. Customer service
Generative AI can provide rapid and effective customer care by answering common questions and fixing simple issues.
8. Account management
Generative AI in banking can assist users in managing their accounts by arranging automatic payments, changing personal information and more.
9. Insurance claims
Users can utilize Generative AI to submit insurance claims and get information about the claims procedure.
10. Financial planning
Generative AI in finance can assist users with financial planning tasks, such as budgeting and setting financial objectives.