Most financial institutions are struggling to implement data and analytics in their day-to-day operations. Fintechs have been highly successful in serving SMBs and entrepreneurs to gain customers from banks and credit unions. They can address important client needs including bookkeeping, expense tracking, insurance, invoicing, payment processing and payroll.

1. Fintechs Steal Customers By Beating
Banks At Data Use - Bahaa Abdul Hussein
Most financial institutions are struggling to implement data and analytics in their
day-to-day operations. Fintechs have been highly successful in serving SMBs and
entrepreneurs to gain customers from banks and credit unions. They can address
important client needs including bookkeeping, expense tracking, insurance, invoicing,
payment processing and payroll.
Most Small and Midsize Businesses (SMBs) do not find additional benefits to their
business banking account over their personal accounts. So more SMBs depend on
fintechs than on banks. So, several banks are investing more in data, advanced
analytics and artificial intelligence to gather intelligence from the real-time
transactional data they have available.
Huge Data, Missing Details
Traditional commercial banking providers as per Bahaa Abdul Hussein, do not give
access to enough detail on customer behaviour needed to respond quickly and with
the right insights. Because banks do not have the right data foundation, they cannot
easily adapt third party resources to serve their clients better. With suitable
multi-speed data governance banks can create an expanded data ecosystem
combining different data signals and fully leverage the scope of the available data.
Banks also send messages and offers.
Main Roadblocks
There are several roadblocks for banks on their journey to reach data maturity. A
principal problem is that banks have their data in discrete silos. So accessing full
data from all these different internal resources is time-consuming and inefficient.
Usually data-driven transformation projects at banks are aimed at short term
management of immediate concerns. For better results, lengthier projects with
better planning are needed. Because of these issues in planning the benefits
obtained from these projects are low. So the banks are fatigued from trying to
reinvent themselves digitally over and over again. Most of the benefits are not from
data-driven innovation to create new models of business, but small revenue
generated from cost saving investments.
How Should Banks Proceed?
There are several things banks can focus on to start seeing major benefits of digital
reinvention. They should work on data access, quality and cloud-based foundations

2. to bypass their internal silos. Banks should create cross-functional teams to allow
business, analytics and IT to share insights and engage in the transformation from
the start. Banks can start by implementing AI for decision-making with low-risk
investments and move to higher-risk investments after initial success. With growing
confidence and data analytic capabilities the banks can slowly try to automate
trading of other products. Using ecosystem partnership to drive transformation, AI
and cloud-enabled architectures and data-driven operating models banks can
increase efficiency. Then banks will gradually win back SMBs by better
understanding and serving their needs.
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