Creating Data Products for Credit Union Using Data Platform

Data products of credit union offer us

  • Credit Union offer saving accounts and loans  
  • Junior saving account  
  • Christmas saving account  
  • Prepaid Debit Card  
  • Insurance Products  
  • Cash ISAs   
  • Mortgages

What is a Data Platform?

There are two main categories of Data – Behavioral Data and Transactional Data. Transactional Data is the most basic set of intelligence at any financial institution’s disposal. It consists of loan balances, account balances, and information that revolves around banking. Digital channels increasingly capture this data.  

On the opposite side, Behavioral Data includes anecdotal experiences and touchpoints within an establishment. It is a capture from a bank’s customer relationship management platform or third-party integrations.  

Which data platform can create data products? 

A data product uses data to assist businesses in improving their decisions and processes. Data products that provide a friendly interface can use data science to supply predictive analytics, descriptive data modeling, data processing, machine learning, risk management, and a spread of study methods to the non-data scientist.   

  1. Predictive analytics is advanced analytics that predicts future outcomes using historical data combined with statistical modeling, data processing techniques, and machine learning. Companies employ predictive analytics to seek out patterns during this data to spot risks and opportunities.   
  2. Finance terminals – A Bloomberg terminal may be a computing system that permits investors to access the Bloomberg data service, which provides real-time global financial data, news feed, and messages.  
  3. Analytics- It is a process of discovering, interpreting, and communicating significant patterns in data. Analytics helps us see insights and meaningful data that we’d not detect otherwise. 

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Key Takeaway of Analytics

  • It is the science of analytics data to make conclusions of that information.  
  • The techniques and processes of knowledge analytics are automating into mechanical processes and algorithms that employ over data for human consumption.  
  • It also helps a business optimize its performance.   

Type of Data Analytics

  • Descriptive Analytics – It shows what happened in a given period. Like the number of views go up or down? Are sales stronger this month than last or not?  
  • Diagnostics Analytics – This focuses more on what and why something happened. It involves more diverse data inputs and a touch of hypothesizing.  
  • Predictive Analytics – This move to what’s likely getting to happen within the near term.   
  • Prescriptive Analytics – It focuses on a course of action.   

Why Data Analytics is important?

  • It is essential because it helps businesses to optimize their performance.  
  • It moves to what’s likely getting to happen within the near term.   
  • A company also can use data analytics to form better business decisions and help analyze customer trends and satisfaction, resulting in a new and better product and services.    
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