Banking Virtual Assistants: Today’s Order-Takers, Tomorrow’s Decision-Makers
An interesting prediction by Gartner about banking virtual assistants is that by YE24, 15% of customer interactions will be performed by virtual financial assistants that will act on behalf of their users.
One of the pioneer sectors that created concrete use cases for AI-based virtual assistants is finance. Although financial virtual assistants are in their early phase, they promise a high potential to transform the sector in many aspects. Today, we can see banking virtual assistants that provide responses to the daily customer queries or perform basic transactions. There are some examples that are able to provide simple suggestions to the customers but the assistants are mostly order-takers. Gartner predicts that banking virtual assistants will be more active about managing the customers financial lives and CIOs should consider this both with a customer and organizational perspective. Our blog summarizes Gartner’s report “Anticipating the Reality of Virtual Financial Assistants: What Banking and Investment CIOs Need to Know” that explains the new role of the banking virtual assistants, how will they be able to perform this role and what CIOs should focus on in this new environment.
Banking virtual assistants as machines that “decides”
Although people are skeptical about autonomous machines that act on their own and drive, manage our financial lives, organize our meetings, they are very likely to be part of our lives in the near future. Gartner predicts that by 2025, more than 12% of new vehicles will have Level 3 or higher autonomous driving hardware capability – Level 3 means being fully capable of taking control of the car. In the 2018, in Gartner Personal Technology Survey 45% of the consumer respondents indicated that they had used a voice assistant in the past month.
Some banks have already integrated their systems to these voice assistants and provide their service through these new channels of interaction. But the new use cases are mostly FAQ-type or rarely perform basic daily transactions. In the second phase of this new environment, it is predicted that we will have banking virtual assistants that make decisions autonomously using the information they gain through various channels. The assistants may come from hardware or software provided by a third party like Google Home, Amazon Echo, Alexa, etc., or they may be algorithms provided by the banks themselves and can be available through several platforms such as voice assistants, banks’ websites or mobile apps or messaging platforms like WhatsApp or Facebook Messenger.
How can a machine know what is best for me?
Banking virtual assistants have a huge potential as they have the power to gain the data about the customer’s personal financial habits, behavior, financial contexts and preferences. If this data is analyzed by the bank or a third party, then the assistant can predict current and future financial needs and act on the user’s behalf. Gartner estimates that banking virtual assistants will perform 15% of consumer financial transactions by 2024.
The crucial prerequisites
It is obvious that the banking virtual assistants need much more maturity to have this role. The prerequisite capabilities for a virtual assistant to act on the customer’s behalf are summarized by Gartner as follows:
- The source of data must be trustable and the customer must think that the assistants make the best decision. Also the privacy of the data should be preserved.
- The assistants must be capable of analyzing the data by using the required technologies in the best way such as natural language processing, data analytics and machine learning.
- There must be a deep personalization and capability of adaptation to the changing circumstances of the customer and the environment.
The customers must feel that they are gaining more value by delegating these decisions than they are risking. If they think that the risk is low and the assistants will make better decisions for them, then they are more open to receive this service. Although we are not close to this point yet, the customers are getting more familiar with this concept as they use the banking chatbot and voice assistants more.
In order to build the trust, the banking virtual assistants must ensure that they are working for the customer. Second, they must be transparent in terms of the decision making algorithms. Third, they should admit and inform the customer honestly, when they are not capable of making the best decision for the customer for the specific moment.
Today virtual assistants are reactive – they give information when asked or do what they are told. But in the near future they will be acting on the customer’s behalf by using 2 kinds of data – factual and contextual. Factual data are about the customer’s facts such as the interest rate of the loan, the date of the salary, the amount paid monthly, oil buying frequency, etc. These data can be collected by tracking the consumer’s activities. As ecosystem banking or open banking matures, the data gained through different sources will be enlarged. In addition to factual data, contextual data is very useful to understand the circumstances of the customer. Financial goals, lifestyle, family information are some basic examples of the contextual data.
Using factual and contextual data for personalization
The banking virtual assistants of the future will have a 360-degree perspective about the customer with a combination of factual and contextual data. This will enable them to be accurate about the predictions, offerings and actions. The most important enabler of this capability is that virtual assistants are used for other purposes and gain a huge amount of data. Open banking and ecosystem banking will allow the banks to make the benefit of it more.
But, this creates an opportunity for the banks to sell more and make more revenue. Of course, this new situation means a big responsibility for the banks as they will have to care the long term goals of the customers when selling each and every product and service. The algorithms should be designed in such a way that they prioritize the benefit of the customer not the bank to gain the trust. So this will be a big game-changer within the overall financial environment.
As it is a game-changer, it has many aspects to be considered by the CIOs or other decision making roles. Business models, organizational culture, customer experience designs, data policies, risk management and security policies, HR policies, operations, workflows, marketing activities will all be affected and needs consideration.
Within the greater view, the authority will have to change the perspective in terms of the regulation and the overall industry dynamics. For example, one interesting question can be who will be regulated: the device, the algorithm, the bank? It is no doubt that this development will disrupt the financial sector sharply. We may see more frequent changes in customer accounts for example and it will disrupt the existing business models.
What should decision makers focus on?
Although virtual assistants are at an early phase in the financial sector, they have a great potential to disrupt the existing sector dynamics in many aspects. The CIOs should take into consideration the fact that banking virtual assistants will have more role to decide on behalf of the customer and act autonomously.
Within this framework, Gartner suggests the CIOs to focus on three important points:
First, CIOs should know and asses the potential scenarios, use cases, implementations by creating test environments.
Second, they should focus on the security, risk managements, privacy, compliance related aspects of the issue.
Third, they should see that the organizational change is a crucial consequence of this new environment. Organizations will need to adopt not only in terms of culture but also involving new skills in the fields like data analytics, machine learning and virtual customer experience. They should be prepared for the high demand and scarcity in these talents.
All in all, banking virtual assistants’ evolution towards autonomous financial decision makers is part of a greater digital transformation not only within the organizations but the daily lives of the customers. These two will mutually affect each other to reinforce the transformational change of the future.
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