Challenger Banks North America Thought Leadership

Optherium Labs: How Neobanks Overcome Lack Of Human Contact 

Neobanks have been criticised before for their lack of human contact: the inability to see someone to discuss your finances has often been one of its biggest flaws. So what can be done to overcome this?

Serge Beck is the CEO and founder of Optherium Labs, a global fintech company developing blockchain solutions to reform defective functions within financial and security infrastructure. He is driven by his belief that people deserve sounder, more secure financial services in our tech-driven world. He is committed to eradicating problems detrimental to end-user experience through the creation of synergised, decentralised products.

Consumer demand for personalisation being at an all time high. Therefore, organisations are doing everything they can to keep them happy. Challenges arise for digitally native banks that don’t have physical representation on highstreets. This is especially true when consumers want to see someone in person to discuss their finances.

Beck spoke to The Fintech Times to discuss the benefits of neobanks and how they are able to overcome the biggest hurdle that is often associated with them. 

Serge Beck, CEO and founder of Optherium Labs
Serge Beck, CEO and founder of Optherium Labs

Regardless of whether or not you have already realised it, most successful services nowadays learn and make recommendations to their customer base. A great example is the Netflix algorithm, one of the pillars of success for the company.

Many companies like Netflix have transitioned from having onsite personnel to using artificial intelligence (AI) and machine learning. But machine learning and artificial intelligence can be of better use than simply recommending what movies to watch. In the neobanking industry, there are many examples, which will be explored in this article.

You will rarely need customer support

Regarding innovative neobanks with the help of third-party software-as-a-service (SaaS) and banking-as-a-service (BaaS) solutions, machine learning algorithms study each user and modify the user interface to optimise their experience.

For example, if you are using a specific feature more than others, the user interface would change itself to allow you to access that feature almost instantly.

Another great example is timing. If you open a feature around the same time each day, the algorithm would mark that and facilitate the process for you. Although these are some of the simplest examples there are, they can give you a good idea of what your connection with the algorithm could be.

It tailors the experience to you, and the more you use your neobank app, the better it gets for you.

AI recommendations and security

Artificial intelligence can study you and make personalised financial recommendations if you need such. For example, monthly spending and budgeting can be analysed in more than one way. A good example is Revolut’s monthly spending analysis that users can see and access each month.

The algorithm shows you data for each month. It can tell you precisely what has changed in your spending. Additionally, it can suggest why it has increased or decreased for a certain period of time.

Of course, it can also be used for security purposes. After the AI has thoroughly studied the user’s behavior, it could alert the neobank’s relevant department if there is a purchase that looks out of place or like it was someone else instead of the user making the transaction.

Moreover, it could sometimes ask for extra authentication if extra-security features are enabled. Biometrics is another side of the coin. With the help of artificial intelligence, you can now log into your digital banking platforms with your face or fingerprint. Transactions can also contain a 2FA, and a biometric approval, which is very hard to replicate and would most likely stop most attackers.

Neobanks are in one place

In a traditional brick and mortar bank, you need to go to the office for certain operations. Then you need to access one app for other things while also downloading another to locate the nearest ATM. And if you need customer support, you need to search their website to look for a number to call.

Neobanks avoid such confusion by having one mobile application that contains it all. You can contact support, locate an ATM, send and receive finances, and analyse your budgets. You can even get financial consulting inside some of these applications.

Traditional support is the last step of the experience

If everything else works perfectly and is as intuitive as possible, clients would rarely need to communicate directly with customer support.

But that doesn’t necessarily mean the support agents should not provide the best possible experience to the clients. Many fintech companies, including neobanks, strive to offer the best possible support, though statistics have shown that a much smaller portion of their clients actually need it.

Another reason why neobanks need fewer customer support representatives is that their clientele is more tech-savvy than the clientele of traditional banks. If someone knows how a neobank operates, then they can usually navigate mobile apps quickly. This in turns enables them to resolve a big percentage of their problems on their own.

The work of neobanks’ support specialists is easier

The day-to-day work of neobank support specialists is easier. Supporting a high-tech bank over a traditional brick and mortar is a lot smoother due to the all-in-one built CRM services. These allow the support representative to transition through emails and conversations seamlessly with one customer.

The form of omnichannel support also greatly enhances the experience on the client’s side. Not to mention, it also reduces the costs for the bank. It lowers the needed number of support agents per shift.

Technology provides excellent support services

Although neobanks need fewer customer support representatives to join their team each day, most big neobanks strive for excellent support services.

Technical support is very unlikely to be needed by the customers. AI and machine learning take care of the user interface of the applications. It makes suggestions and rearranges visuals to eliminate navigational problems.


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