In recent years, FinTech has become a buzz word which refers to technology developed by companies
outside of the banking industry to provide financial services or transactions. By definition, FinTech refers
to any technology created to provide such services without differentiating the source.
With this in mind, one can gather that the origins of FinTech occurred within the banking industry when
technology like the ATM and online banking were developed and introduced to the general public. So,
despite this general belief about FinTech, the term in fact refers to technology developed both inside
and outside of traditional banking. The question becomes: how do banks currently compete with
outside providers like Avant (online lending), Acorns (investments) or the Cash App (funds transfers),
just to name a few, to ensure they limit their losses with regards to market share? The situation can be
further aggravated given the impression that technology offered outside of traditional banking channels
provides greater convenience and cost savings in contrast to what banks currently have available.
Developing technology and/or partnering with an external provider to compete with, or at least
mitigate, services and convenience created outside of the industry is a strategy that could be
considered. As a result, successfully determining steps to take in the development or addition of
technologies is of utmost importance. Analyzing trends outside of the industry such as identifying the
most popular services provided by FinTech and how they have grown in recent years is a method to
assist in this effort. Additionally, studying the market by identifying which segment is adopting
technology with greater propensity can help.
The reality is that if you want to retain your existing customer base, and grow from there, you need to
take an internal look and determine what their preferences are when it comes to employing technology
to do their banking. In this sense, banks have at their disposal a major advantage over FinTech providers
outside of the industry: vast amounts of data generated by their client base with regards to how they
prefer to manage their finances. With that being said, having the ability to gather and interpret this data
is difficult and knowing what to do with this information is even more challenging.
So a great place to start has to do with how data is gathered and managed within your organization.
Let’s consider the different levels of readiness when it comes to collecting and interpreting information.
1. First, let’s consider how organizations typically manage data:
a. Is the information gathered in silos, different departments or units, in manual fashion?
b. How is the data being shared?
c. Are decisions being made with only the data that is available or is your organization
identifying any informational gaps that exist in order to get a better picture?
2. Next, take a close look at how data is analyzed in making decisions:
a. Is there a centralized analytics division with subject matter experts who are reviewing
the information as it is being gathered at all levels of the organization?
b. Are all key decisions based on thorough analysis of data?
3. Finally, let us discuss how this information is helping banks create innovation:
a. Is your staff made up of data analysts and specialists who can generate accurate and
effective predictive models?
b. How is this analysis used to increase sales and improve customer service?
c. Is data mining being employed as a strategic asset and creating a competitive
Determining which of the previous components of the data mining process your institution exhibits is
critical to taking effective steps in designing and employing technology to service your current client
base. This will have an impact on how effective these tools can be in maintaining or even increasing your
Also consider that new technology is not only deployed to customers, it is also for internal applications.
While the main force driving the creation of client facing FinTech is convenience for the end user,
internal or employee facing technology is mainly driven by cost savings or revenue generation for the
institution. Artificial intelligence (AI) is an important form of technology that has been developed and
deployed internally in the last few years.
This technology has evolved rapidly as of late and is being utilized to analyze user data in order to
identify real-time products and services that can be beneficial to banking customers. The ability to
distinguish the financial needs of your client base thru the employment of AI has become extremely
effective. But identifying your clients’ preferences is only one half of the equation, the second
component is effective delivery. Random emails, text messages, or web advertising is not the most
effective way to reach your target, even after identifying their most pressing financial needs. Part of the
reason could have to do with timing and with financial literacy on the part of the general public, perhaps
there is information overload in this age of digital communications. Whatever the reason may be, it is
challenging to capture the general public’s attention thru many of these impersonal methods. The most
effective way to offer a client a product or service that will benefit them is via front line employees at
the branches. This can be a difficult endeavor since it requires a high skillset which not every employee
This is where some banking institutions are doing a great job by providing bankers with the tools to
identify needs and deliver them effectively while interacting with clients at the branches. In some cases
bankers are tasked with setting up appointments with existing clients to engage in meaningful
conversations and offer financial products. Some banks are also automizing basic transactions at the
branch and reallocating branch personnel to engage existing customers in meaningful conversations.
The bottom line is that leveraging technology to innovate how your institution currently serves your
client base will continue to play a critical role in the success of your business model. However, it is the
ability to adapt to the rapid changes in technology and banking in general that could make the
difference between growth vs attrition.