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The Antidote to Big Data Challenges and Risks

The Antidote to Big Data Challenges and Risks

In time, data analytics will become a necessary component to every financial institution’s business strategy.  But today, many executives are searching for the cure to overcome some of the potential challenges that come with a data analytics initiative.  Challenges and uncertainties include how to manage the data, how to mitigate compliance and security risks and how to quantify big data’s true ROI without flawed results. There are obvious obstacles and risks that can overshadow the tremendous benefits. Fortunately, the answers and the cure already exist.

Unlike mega banks that have a large budget to hire a Chief Data Officer and an army of data scientists to build a data analytics program from the ground up, midsize and even community banks are seeking out innovative experts that have spent years researching, developing, testing and refining a data analytics product offering.  Why? Proven, outside partners require a fraction of the time and budget of an in-house product. You receive the benefit of time-tested expertise and they will do all the heavy lifting.  My advice, those toying with the idea to go full speed with a data analytics product should take the time to research an innovator that has years of experience and has already combined the software development and implementation acumen with a powerful data analytics platform.  This should be a proven product that will provide the power to unlock profitable opportunities and accelerate growth.



Security and compliance are paramount for all financial institutions, and should take the highest priority for analytics as well. Seek a partner that adheres to the most stringent data privacy and security requirements, while still offering the speed, convenience and accessibility of a cloud-based solution.  They should provide powerful data encryption and be SSAE 16 certified.

Make sure that the data analytics partner provides a program where all data is transmitted using Secure File Transfer Protocol (“SFTP”), and two security options that are based on the financial institution’s preferences.

The first security option is a process that runs at the financial institution before the data ever leaves the data center. All non-public information (“NPI”) is cleansed or masked using an algorithm unique to each institution.  The second should run the same process at the providers’ data center. Either way, no NPI is stored within the cloud based solution. When lists, including customer information are necessary, the process runs in reverse and the list should be placed on a server within the financial institutions’ data center.

The bottom line, financial institutions should seek a partner that allows them to have the peace-of-mind to analyse business data without ever compromising data security.


It’s true that when it comes to analysing big data, if you do not understand the data, and misinterpret it, then you will risk getting flawed results.  Also, after collecting and cleansing the data, some are left asking “so now what do we do with it?” How do you overcome these challenges?

Seek a partner who offers a solution that provides actionable insight with sophisticated, yet simple-to-understand dashboards. By leveraging these dashboards, users will quickly and easily be able to make data-driven decisions that deliver impactful results. This leaves little room for the misinterpretation of data. Initially, there are dozens of intuitively logical actions the institution should take to drive revenue. Over time, additional actions are statistically derived.  These actions become recurring best practice by comparing action 1 to action 2 versus a control group.  Soon the institution should have a number of quantitatively proven actions that move meters and drive ROI.


Infusing an advanced data analytics initiative into a financial institution can be a daunting task, so alongside a data analytics product, ensure the partner provides a Data Scientist or Data Analyst to give support during and after the roll-out of the product.

A Data Scientist will analyse the data each day, and train staff to uncover new opportunities, reduce expenses, retain customers and create new revenue streams.  This ensures everyone involved in the process understands the data coming in and what the output translates to.  Similar to how data scientists at larger banks have been trained to turn mountains of information into quick insights, seek a partner that can advise  decision makers to take action on immediate opportunities, track success, and improve cross-sell opportunities that enhance the bank’s competitive advantage.


Many financial institutions are embracing the power and potential benefits of implementing a big data and advanced data analytics program.  Soon, bank executives will rely on data analytics to make almost every major decision to drive revenue, control costs, or to mitigate risks.  Take the time now to invest in your financial institution’s future. The antidote comes in the form of a proven provider with time-tested software and implementation expertise, who does the heavy lifting so the financial institution can focus on the bottom line and the future.

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