-->

How to cleanse your data to reduce credit risk this holiday season

Reading Time: 2 minutes

As Australia comes out of COVID pandemic and lockdown restrictions are reduced, uncertainty around trading activity remains. During the holiday period it is vital to stay on top of your customer data.

Companies need data to gain insights for business development and make informed decision-making. CreditorWatch’s portfolio health check and data cleansing play a vital role in detecting data discrepancies within a database and removing or updating the information. Specifically during the holiday season, it is even more crucial to be on top of data management and checking up on your risky customers to make sure you are being paid on time.

CreditorWatch’s portfolio health check provides a comprehensive review of your business’ database, assisting and empowering you to validate your data, remove incorrect information and identify risky customers and suppliers. Data cleansing is a high quality, accurate and complete audit of your businesses data, enabling you to take control of your risk management and make more informed decisions with clean and authentic data.

Forty per cent of business objectives fail due to inaccurate data, highlighting the detrimental effects it can have on a business which may still be struggling in the rocky economic landscape of a post-lockdown world.

How does the portfolio health check work?

The portfolio health check reviews a businesses’ database, distinguishing the clean data from the dirty data, making it much easier for you to see where the outdated, inaccurate information is hiding. Through this data cleaning, it automatically corrects and consolidates your businesses’ data to ensure your system performs at the optimum level.

The portfolio health check includes:

  • Data validation
  • Data standardisation
  • Eliminating duplicate data
  • Data matching
  • Data enhancement
  • Data reconstructions

 

Data validation 

Data validation ensures your database is authentic and contains correct and updated information for various system inputs. The data validation step includes a check of allowed characters in a field, corresponding data and spelling and grammar.

Data standardisation 

This process includes the action of taking data from different sources, formats and naming conventions and then converting them into a cohesive and common form. Through standardisation, the data is visually presented clearly in an accurate and consistent manner so that business decisions can be made.

Eliminating Duplicate Data 

Through a data wash, any inaccurate or duplicate files are removed, eliminating the potential harm of skewing data results due to inaccurate or out-of-date records and results. This elimination of duplicate data increases the data quality. 

Data Matching 

Data matching is the process of cross-checking the information in your database with external data resources. Through a comparison of information from various validated sources, we can identify, match and merge records that correspond to the same entities and data sources.

Data Enhancement 

Through the adding of supplementary information such as related phone numbers to addresses or enhancing a list of loan applicants with their credit score, we can utilise and emphasise the accuracy and holistic value of the data.

Data Reconstruction 

Data reconstruction is the overall process of transforming dirty data into clean and accessible information to help solve business challenges at an optimum level.

 

Get in touch below for a free portfolio health check consultation with one of our data cleansing experts. 

Cleanse your data now