Fintech Today
  • About
  • Banking
  • Insurance
  • Resources
    • COVID-19
Subscribe
No Result
View All Result
  • Digital Transformation
  • Customer Experience
  • Cybersecurity & Risk
  • Regulation & Compliance
  • Claims Management
Fintech Today
  • Digital Transformation
  • Customer Experience
  • Cybersecurity & Risk
  • Regulation & Compliance
  • Claims Management
No Result
View All Result
Fintech Today
No Result
View All Result
Home Banking

Seven Pillars to Master Data Management Success

by Mark Katz
September 19, 2017
in Banking
Reading Time: 5 mins read
A A
data management
Share on FacebookShare on Twitter

“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran

The term Big Data is probably a misnomer by now, given the breadth of global data proliferation.  Moore’s law used to be the oft cited benchmark around processors.  That was then.  While impressive, overall data growth has become the more pertinent benchmark in today’s world—perhaps Massively Big Data should be the new term.

Data growth worldwide doubles in size every two years.  According to EMC, by 2020 digital data growth will reach 44 zettabytes, or 44 trillion gigabytes. Certainly impressive, and something that must keep storage engineers and data scientists up at night.

But as Daniel Moran pointed out in the quote at the beginning of this article, it boils down to this: there is a plenty of data, but very little information.   Data Scientists are trying to make sense of the data sprawl, correlating data that is unstructured and disparate, with the hopes of hitting on algorithms that produce breakthroughs, or at least reveal unforeseen visual patterns that benefit both the internal enterprise and customers.  Not easy, but the payoff can be substantial.

Data monetization has become one of the holy grails, and with the growth of AI, Machine Learning, and the positive disruption of transactional platforms such as blockchain, technology departments need to ensure that the data is actually clean. Without that crucial piece, the only disruption will be to the company’s reputation, and overall strategy. Trying to scrub data by virtue of gleaning the output from these tools and platforms is not the right way to cleanse the data. It is a mistake to think that “the market” will correct your data. If the issues are severe enough, trust erodes, and reputations do indeed suffer. So how can a firm move forward with these technologies, and find different ways to leverage their data assets?

Implementing a robust Master Data Management process is foundational to ensuring that firms can be agile in their approach to these forward tech adoptions, since the very core of MDM is that there is a single version of “data truth.” Organizing for MDM can admittedly be a challenge.  However, in the long run, can mitigate risk, and lead to better organizational cohesiveness.

Some firms have been doing a version of MDM even before the moniker MDM came into play, since data was always at the very core of their business. Capital Markets, Banking, Insurance have inherent data standards for moving money and securities so they can be a bit ahead of the curve. For instance, SWIFT is one standard that comes to mind, and agreement on Securities identifier standards (CUSIP, ISIN, SEDOL, etc.) is another.  But with the various data tools on the market, and unstructured and off system data now being exposed in transparent ledgers (Blockchain), the MDM practice needs to evolve to become a standard in most firms. Without it, it would certainly be a challenge to leverage the firm’s data assets.

As stated earlier, MDM does take time to implement. A key part of the implementation is getting companywide buy-in and adoption, since tech does not own the data; the business lines are the data stewards as they understand how to best leverage it to solve business problems and gain opportunities. With that, the business should be involved each step of the way, since ultimately, most executives would want their company to at least be able to:

  1. Share data and analysis intra-company, with the ability to link and add disparate and even unstructured data that is trusted.
  2. Have a holistic view of all business entities, analyzing data as required, segmenting and combining data assets.
  3. Provide customer intelligence internally and externally, with tools and data that allow decision support.

As a collaborative partner with the business lines, the CIO and or CDO should take the time to explain the components of an MDM implementation, especially since it can result in operational changes due to new governance policies.

So where does a firm start when there are so many moving pieces? Gartner has defined seven foundational pillars for MDM success that ensconces critical attributes:

  1. Vision – Does the business have a defined vision? What can be done?
  2. Strategy – Tactical or integrated?
  3. Metrics – ROI and intra company measurements specific for each project
  4. Governance – Shared governance based on policies, initially IT led, but needs to evolve cross enterprise. Single version of the truth!
  5. Process – Data Life cycle, plain and simple. Mapping the full life-cycle of the data, its use cases, data rules, validations, are all required.
  6. Technology – Start out with Extraction Transform and Load as you map out the data, and engage the business in helping to cleanse the data. Ultimately you want to arrive at the correct and agreed upon Master Data Design.  Also, the selection of the right MDM tool for your enterprise is crucial.

For MDM to thrive in the enterprise, these high-level steps should be at least considered as a framework. Again, an implementation of MDM is not without its challenges, but with data expansion, and the lack of enough true information coming from a lot of data, is it prudent to ignore?

Tags: AIbig datamachine learningMark KatzMaster Data ManagementMDM

RELATED POSTS

Pandemic Relief Fraud
Banking

Artificial Intelligence Helps Combat Fraud, Waste, and Abuse and Protects $5 Trillion in Pandemic Relief Funding

June 9, 2022
Contributed Articles

AI in Financial Services: Where Does Ethics Fit In?

April 28, 2022
Customer Service
Banking

AI Makes its Move in FSI to Improve Customer Service

April 29, 2021

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

TRENDING NOW

  • Who’s Driving Digital Transformation for Banks and Financial Institutions?

    Who’s Driving Digital Transformation for Banks and Financial Institutions?

    499 shares
    Share 200 Tweet 125
  • With a Virtual CISO, Financial Services Institutions Can Upgrade Their Security Posture

    496 shares
    Share 198 Tweet 124
  • Email Phishing and Spam Protection Help Financial Services Institutions Build Trust and Credibility with Customers

    506 shares
    Share 202 Tweet 127
  • Arizona’s Motor Vehicles Department (MVD) Makes Payment Offerings More Accessible

    645 shares
    Share 258 Tweet 161
  • Selling Life Insurance Policies Via Vending Machines is the Ultimate Form of Customer Convenience

    554 shares
    Share 222 Tweet 139

CONNECT WITH US

Advertisement Banner Ad Advertisement Banner Ad Advertisement Banner Ad
Advertisement Banner Advertisement Banner Advertisement Banner

BECOME AN INSIDER

Get Financial Technology Today news and updates in your inbox.

Strategic Communications Group is a digital media company that helps business-to-business marketers drive customer demand through content marketing, content syndication, and lead identification.

Related Communities

Future Healthcare Today
Government Technology Insider
Modern Marketing Today
Retail Technology Insider
Today’s Modern Educator

Quick Links

  • Home
  • About
  • Contact Us

Become a Sponsor

Financial Technology Today offers content and advertising sponsorships to leading technology solution and service providers. Interested in becoming a sponsor? Contact us!

© 2023 Strategic Communications Group, Inc.
Privacy Policy      |      Terms of Service

No Result
View All Result
  • Home
  • About
  • Banking
  • Insurance
  • Categories
    • Digital Transformation
    • Customer Experience
    • Cybersecurity & Risk
    • Regulation & Compliance
    • Claims Management
  • Contact Us