In a context where startups like Wise, TradeIn, and Revolut are showing an average annual growth exceeding 100% over the last three years, far outpacing traditional banks, the importance of customer service becomes crucial to ensure a user experience superior to that of the competition.
It’s undeniable that maintaining a high level of customer service is easier to manage for a start-up with 100 employees than for a large bank with multiple affiliates.
Faced with this challenge, how can traditional banks improve their customer service in the era of artificial intelligence in 2024?
1. Artificial Intelligence assistance, without falling into the trap of 100% AI
Without a doubt, customer service is the first sector of the company to feel the impact of the arrival of AI. Although this process is not recent, the first chatbots date back some ten years. However, their integration into customer services has grown exponentially since the end of 2022 with ChatGPT 3.
One question that quickly arises is: do we still need human customer service in the era of artificial intelligence?
The Swedish fintech boasts the success of its OpenAI-powered customer service chatbot, which handled no less than 2.3 billion conversations in the last month.
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The Swedish company has laid off 700 employees by 2022, curiously as many as the chatbot is apparently capable of replacing.
In the world of banking in France, the answer is categorically YES.
Several factors confirm that, in a sector as crucial as banking, customer service plays an essential role that will not be replaced over the next few years:
- French customers are not ready.
The company Odoxa indicates that 73% of French people would not trust these AI-powered chatbots. In addition, 70% of users consider “their exchanges with chatbots to be unsatisfactory”. - The technology, being fully autonomous, still needs to progress. A very concrete example of this can be found on the other side of the Atlantic with Air Canada: “The Canadian airline was forced to pay for a pricing error made by its customer relations chatbot.”
The aim is to use AI to improve agent performance by (1) automating manual tasks such as qualification, response writing and note-taking, and (2) enhancing response quality through the integration of internal search engines.
2. Capitalize on all customer data to offer a personalized experience
In the banking sector, digitalization has been the master word over the past 10 years. Millions of dollars have been invested in various tools such as CDP, CRM, ticketing tools, call management and the digitization of business repositories to improve customer experience management.
Capitalizing on all customer data is crucial to creating a high-performance customer service and remaining competitive in terms of customer experience.
Concretely, whether responding to a customer or managing a complaint, it is crucial for the agent to have a complete overview, including at least :
- Customer’s history with the company
It’s important to know how long the customer has been loyal to the company (20 years or 6 months), their value to the company and their most recent exchanges. - Level of satisfaction (feedback)
Based on the latest CES, CSAT, or NPS scores to provide a real-time assessment of the satisfaction level. - Personalization vectors
In compliance with the GDPR, this information such as age category, financial means, location and language enables a fully personalized experience.
3. Increase the “surface area” of customer service
As agents become more productive thanks to technology, it is now possible to offer a larger customer service surface area, while keeping existing operational costs. This is a mix of AI and integrations, taking customer service into a new era.
Increase the number of contact points
In recent years, omnichannel have been widely discussed, but now it’s about going further by involving the various stakeholders present on each channel. Here are some examples:
- Centralization of customer reviews: Google, Trustpilot, Stores, etc.
- Aggregation of messages from social networks: Instagram, WhatsApp, Facebook, etc.
- Unification of channels: email, telephone, online ticketing, etc.
Once centralized, agents can be present across all contact points throughout the customer journey.
Improving accessibility
AI represents a real revolution in terms of availability, because with the right set-up, AI agents can be present and available 24/7 in over 30 different languages. It should be noted that, as mentioned in point #1, these agents have their limitations and are only effective for responding to Level 1 requests.
4. Digitization of all processes
Fintechs or startups have a major competitive advantage over traditional banks by offering digitally optimized journeys. This results in a significantly superior experience compared to other players.
It is therefore essential to digitize all processes, not only to reduce repetitive tasks in customer service, but also to globally enhance the quality of the banking customer experience.
Here are some key moments in the customer journey that require digitization and optimization for web channels:
- Access to bank statements.
- Account access path (forgotten passwords/logins).
- Check deposit process.
- Accessing tickets with customer service.
- Onboarding for the first access to the customer space.
- Account cancellation.
- Opening new accounts.
- BtoB actions (such as opening access to a collaborator or sharing accounting flows, among others).
A few counter-examples, which persist among certain French players, considerably damage the customer experience in many aspects:
- The need to have a paper card with codes to secure transfers is essential.
- Sending a registered letter to close a bank account.
- Requiring an appointment in person to open an account can be restrictive.
- Not updating the mobile application for more than 12 months when the rating in the App Store is below 2/5.
5. Efficient feedback and weak signal detection system
Managing customer feedback is essential for improving customer service. It’s not new, and several systems have evolved:
- Measuring satisfaction, with annual surveys/barometers.
- Voice of the customer, including real-time measurements and reporting for teams.
- And now, with AI, we’re entering the era of Customer Intelligence.
By combining AI, the right data, and the right processes, it is now possible to go far beyond traditional customer feedback management systems with customer intelligence:
- Real-time and in-depth processing of all verbatims (surveys, reviews, complaints) thanks to automatic Natural Language Processing (NLP) and Machine Learning (ML) linguistic models.
- Automation of report creation and initial analysis (comments on graphs, rendering, etc.) to provide all operational teams with the ability to generate customized reports on problems encountered, positive points and a summary of customer feedback.
- Detecting weak signals and anomalies: by combining customer experience data (feedbacks) with business data (CRM, references, etc.), it is now possible to efficiently and cost-effectively detect correlations and weak signals, and assess the financial impact of dissatisfaction.
6. Reassessing agent performance – NPS 3.0
Recent years have seen the rise of numerous indicators designed to evaluate and align teams with corporate objectives. However, when it comes to the customer experience associated with customer service, it is crucial to assess the impact that certain indicators have on customers.
A primary example is the increasing popularity of the Net Promoter Score (NPS). Despite its many limitations, it’s important to understand its influence on company growth as well as the general well-being of employees, including agents. For more information, you can read our article dedicated to this topic here.
In practice, one of the most common practices to avoid is implementing incentive plans based primarily on NPS scores at agent level. The major issue is that often agents focus solely on the NPS score itself, which is natural, rather than on its actual impact on the customer. They perceive every evolution of the score as a dramatic change.
In addition, there are perverse effects, such as encouraging customers to answer 9 or 10 and nothing else. Solutions exist and are easy to deploy technically, but more complicated to implement in human terms:
- Having an in-depth analysis of NPS (according to different customer segments) and with a monthly frequency rather than daily.
- Changing incentive plans to be based on team NPS rather than individual NPS.
7. Improve investment in agent training
Training employees in the company’s new products and services is no longer appropriate in our current world, where an AI can provide comprehensive answers on all our products in a few seconds. So, the way we approach training plays a crucial role in the transformation and long-term success of banks, provided it is leveraged optimally.
Regarding customer service, the training topics expected to become increasingly important in the coming years are as follows:
- Understanding AI: It’s essential to grasp both the functionality (with its advantages and limitations) and the technical aspects to exploit its full potential.
- The importance of personalization: A successful customer experience relies on an effective combination of data, empathy and a deep understanding of the issue.
- The impact of customer service on business transformation: Emphasizing the crucial importance of customer service through concrete examples, highlighting the central and strategic role of agents who are at the heart of interactions with the bank, capturing the major sources of dissatisfaction, needs and ideas.
In conclusion, faced with the rapid evolution of fintechs, traditional banks must leverage artificial intelligence to strengthen their customer service while preserving the human touch, to guarantee a personalized and competitive experience.
