The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

Right-Party-Connect Rates In 2018

September 22, 2017 at 1:19 PM

Collection Cascade

When looking at the collections cascade and it’s diminishing returns, we always emphasis the responsibility factor relating to each metrics. Whom is responsible for these areas, and how do we monitor the accuracy of these metric results?

If we take a closer look at the right-party-connect rates, you'll notice several dispositions that occur regarding this metric:

  • RPC KPI’s for collection agents
  • Manual logging of RPC’s and subsequent impact
  • Quality Assurance monitoring of RPC’s
  1. Right-party-connect is a direct result from available data, analytic insights/models and dialler strategies, but we still see companies including RPC as a KPI for collections agents. This is concerning due to an agent having no influence if the right-party answers a telephone call or not. RPC outcomes are only as good as the data and strategy used. If your company uses RPC as an agent KPI, how sure are you that the logging of RPC’s is accurate? Remember, agents always find a way of manipulating outcomes to suit their needs.
  2. If we look at how we log a RPC in our operating systems, we can all agree that for the most it is still a manual action by an agent. But is this really optimal, and what is the risks associated with these manual actions? Even though we may not assess agent KPI’s on RPC outcomes, we still assess their conversion of a RPC to a promise-to-pay (PTP). We know that agents can very quickly find a way of manipulating outcomes to suit their needs. So how comfortable are we in the accuracy of our agents’ negotiation outcomes, knowing that there is still room for manipulation?
  3. I recently had a conversation with a colleague regarding their comfort around their QA process and the validity of the outcome. What QA penetration % on calls would you feel is sufficient to draw conclusions from? Would you bet your money on the validity of that penetration? % NO... And I agree fully.

We all know that most companies penetrate less than 0.5% of all calls, and with those odds we are very far from being comfortable to draw any concrete conclusions to influence strategy.

What if we could penetrate 100% of all our calls, would that change the face of our RPC outcomes? Would that result in a focus shift?

Looking at where the collections solutions are going in terms of data analytics, machine learning, AI agents and voice analytics – isn’t it important to completely take the RPC metric away from the call centre agent and their ability to manipulate it?

Let’s start talking about voice biometrics and the importance of it within the operational call centre...

Increase your collection and recovery yields

Perry de Jager
Perry de Jager
Perry has been involved in Collections and Recoveries for the past 12 years, spending time in different market segments ranging from law firms to investment companies. At Principa, Perry has worked on extended projects within both South Africa and the Middle East with some of the largest financial organisation, providing on-site consulting within the collections and recoveries space covering strategy, process, people and technology.

Latest Posts

The time is NOW for model validation and adjustment.

One of the major premises used in credit scoring is that “the future is like the past”. It’s usually a rational assumption and gives us a reasonable platform on which to build scorecards whether they be application scorecards, behavioural scores, collection scores or financial models.  That is reasonable until something unprecedented comes along.  You can read about this black swan event in our previous two blogs here and here

10 ways the COVID-19 crisis will affect your credit models (PART 2)

This is the second of a 2-part blog. You can read the first blog here.

10 ways the COVID-19 crisis will affect your credit models (PART 1)

One of the basic principles of credit scoring and modelling is that the “future is like the past”.  Whilst robust credit models may be calibrated on multiple time periods, this assumes that trends in the past represent what is going on today.  COVID-19 is a black swan event – meaning in the modern day it really is unprecedented.  If you have never come across the term black swan, or if you have but no idea the origin, I recommend taking two minutes to read its really interesting etymology.