From a consumer’s perspective speed is the name of the game when it comes to transactions and planning. 43% of consumers have said that speed is the main reason for using a Fintech lender, with flexibility coming in second at 29%. If, as the saying goes “speed’s just a question of money”, the challenge for Fintech companies has been how to create a rapidly responsive system that is concomitantly cost effective.
One answer is to create automated systems that can perform transactions and respond to queries based on fixed algorithms. PwC has already stated in its report on how Fintech is affecting financial services that one of the major trends has been the emergence of self-service tools that do not require human interaction. However, there are many issues with this type of technology and here we take a look at how this trend could affect consumers.
Personalisation v Automation
The line between these concepts in Fintech is often blurred as early proponents have often promoted automated software as product personalisation. Despite this, carrying out true personalisation is far trickier than the products described by Fintech startups as “personalised” make it seem.
Generally, the software that is peddled as personalised offers a service to manage personal funds. In some instances Fintech can serve up offers and discounts relating to an individual’s financial record; however, there are many others that are actually automated services that don’t offer anything the consumer couldn’t find out for themselves (albeit at the expense of their time).
The danger is that by marketing these services as “personalised”, Fintech companies are implying that the customer is at the forefront of the product’s consideration. Notwithstanding, if the service is automated then Fintech companies run the risk of alienating the customers earned on the promise of a personal experience.
Recently insurance firm Admiral announced that it had developed software, called firstcarquote, that would crawl its customers’ Facebook pages in order to mine data that would affect car insurance prices. The software would perform a sentiment analysis on comments made by the customer and look for key indicators of “safe” behaviour such as list making and detailed planning.
Whilst Admiral was quick to point out that this was only intended to offer discounts rather than increase premiums, the invasion of privacy was deemed too great and Facebook pulled the plug just hours before the launch. The digital campaigning organisation Open Rights Group praised the decision as it said that these “intrusive practices” would promote self-censorship and could discriminate against certain groups.
It is no coincidence that an increase in data mining has coincided with the rise of automated services in the Fintech sector. Data mining can improve CX but it shouldn’t be the only resource used to develop new technologies. Fintech automation treads the same dangerous line as many personalised products have between invasive and beneficial, and to do so without clarity would be an arrogation of personal information.
Positive Examples of Fintech Automation
There are some forms of Fintech that do benefit the user without an overt disregard for the consumer’s experience. Near Field Communication (NFC) is used to connect devices in close proximity and this technology can be used to make payments using either a card or a mobile.
Ovum’s report on the future of eCommerce suggests that NFC is set to become widely adopted among retailers with a forecasted 1.09 billion users globally by 2019. Where NFC differs from other forms of Fintech automation is that it doesn’t require any input from the customer and any data that could be gathered would exist in other channels.
From the perspective of adopting businesses, Fintech automation has the potential to save huge amounts of time and money. Leverate CEO Kobi Gur said that Fintech automation will help:
“…to improve [a company’s] acquisition, conversion and retention funnels.”
One could argue the anti-automation sentiment comes from those wary of the threats to jobs, although it wouldn’t be fair to single out the Fintech industry in regard to this particular matter.
Fintech automation is an exciting way for companies to perform business and offer services to customers. Despite this, the same companies must consider that consumers are increasingly expectant of immediate service and won’t be impressed should an automated service go awry.
Furthermore, automation requires currency and this often comes in the form of data. It has only recently been pointed out that big data isn’t the same as good data and Fintech companies must keep services tailored to specific purposes and avoid mining needless data from customers. In certain cases it appears that efficiency is prioritised over efficacy, and this balance needs to be ameliorated in favour of the customer.
Do you feel that Fintech automation has gone too far? How could Fintech companies improve the adoption of this technology? Get in touch with us on social media and tell us your opinions.