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WEM Applied: client pre-screening

Many processes in the customer service sector require some type of pre-screening, often a form and sometimes a whole stack, is handed to you upon walking into a doctor’s office or social services appointment.

WEM has been used numerous times to create customer friendly pre-screening applications to automate that process and allows people to complete those forms on their own time, prior to coming in for their appointment, this results in: better customer experience, higher quality answers, ability to prepare for the professional prior to the appointment.

Applications like this have been created using WEM for pre-operative, eye surgeon visits, debt relief aid and pre-employment screenings just to name a few.

In this blog we’ll focus on the Mesis© debt relief aid solution. In the Netherlands where this application is deployed debt relief aid is considered a social service and provided by the government or affiliated organizations.

The Mesis© debt relief pre-screening features a couple of great features including:

  • Multi agency capable, multiple debt-aid organization are able to use the same application with separate data environments
  • Customer (the person seeking debt relief) login with ability to complete the screening as created for them
  • Smart forms with questions about life situations and their responses to these situation
  • Automatic algorithmic scoring based on customer’s answers, creating a comprehensive customer profile
  • Automatic feedback to debt relief professional

As a result of this application the intake meeting with the debt relief professional has been replaced by an automatic intake, allowing the team to design a remediation process tailored to this customer’s needs before the first meeting.

The result is a better experience with decreased wait time for the customer and a much higher turn-around time for the agency allowing them to help more customers.

As part of an extensive review of the effectiveness of the debt-relief process the quality of automated pre-screening application far exceeded the expected results.