What's Predictive Analytics?

Definition of term

Predictive analytics, a field of data mining, is about predicting future data and trends at short notice. The focus here is on an individual customer or a unit from your company for which future behaviour is to be calculated and for which interest is to be shown. If, for example, you want to know what you can do to increase sales of a specific product as quickly as possible or which offer you can present to customers who are willing to migrate so that they remain loyal to you, the WDL can help you with your decision. In order to be able to determine such information, we use the available historical data of your company and concentrate additionally on the history of the product to be viewed or the relevant customers. With the help of appropriate state-of-the-art technologies, we can evaluate the extensive amount of data with regard to the current issue. In addition, we enrich the evaluations with a large amount of external data in order to better explain the behavior of individual customers and the sales figures of certain products. During the analysis external information about holidays, weather, season or the introduction of new competing products or companies to the market can be helpful. The focus of Predictive Analytics is on the short-term decision horizon as well as the set focus. The difference with another data forecasting option, forecasting, which the WDL uses for more long-term data forecasting for your entire organization, is in the focus and timeframe set.

Sector-specific differences

Predictive analytics can be used promisingly for banks. There are huge amounts of data available that offer great potential to provide the bank with new information about your customers and thus support the management of the company. In contrast to many other companies, banks traditionally handle the evaluation of the data available in their IT systems rather cautiously and thus by no means exhaust all possibilities for data analysis. The WDL knows how to deal with this problem: In addition to the requirements of the Basic Data Protection Regulation (DSGVO) and the concretisation by the Federal Data Protection Act (BDSG), which we dealt with at an early stage, we offer our customers trust, protection and security as a central component of our service. All data is transmitted in encrypted form or reduced to the minimum required for our analyses. The WDL can show you how you can use predictive analytics to manage your business and increase customer satisfaction and retention:

  • Determination of the creditworthiness of customers
  • Assistance with the allocation of the (monthly) budget for bank customers
  • Detection and prevention of fraud
  • Cross-selling in the advertising of financial products
  • Prevention of customer churn
  • Formation of customer groups for better address and application
  • Financial management for customers or companies
  • Banking on the smartphone
A data science project with us usually runs in three agile steps, whereby a customer-specific project is first identified in the Proof of Concept (PoC), which is then transferred into an individual graphical user interface. This is followed by the automation of the previously created dashboard and the transfer to automated regular operation, with which you become a data-driven bank.

Westphalia DataLab GmbH

Regina-Protmann-Str. 16
48159 Münster
Phone: +49 (0) 251 20751120
Mail: info@westphalia-datalab.com

© 2019 Westphalia DataLab GmbH
Cookies facilitate the provision of our services. By clicking OK, you agree that we may use cookies. Read more