You are currently viewing Collections Technology in the aftermath of a pandemic (Part 1)

Collections Technology in the aftermath of a pandemic (Part 1)

We all know the importance of technology within the call centre … or do we?

The world has been experiencing its fifth documented pandemic since 1918.  According to the WHO, a pandemic is defined as the “worldwide spread of a new disease”, and the novel coronavirus, SARS-CoV-2, was officially defined as a pandemic on March 11, 2020.

In almost a year of living with the pandemic, we have experienced:

  • Introduction of WFH (work-from-home) within a previously predominant contact centre-based environment;
  • Large volumes of customers being directly affected by the state of emergency which forced industries to come to a standstill or companies operating with minimum capacity, resulting in employee salary reductions and retrenchments like we have never seen in our lifetime;
  • We’ve seen an increase in account defaults, especially late in 2020 when relief schemes started coming to an end.

But have we learnt the importance of technology and what’s available to ensure resilience in future?

In this 2-part series, we will be looking at the Collections cascade or funnel and what types of technology can positively influence performance.

When we look at the collections funnel, we all know that the volumes entered or starting volumes diminishes as you go through the levels or activities. What we want to do, is utilise data and technology to decrease this diminishing relationship between the levels or activities. We in essence want to increase the conversion rates.

So, let’s start at the beginning.


The first technology, and most probably the most important within collections operations, will be:

    a.  The Collections Management Solution, or Collections Software

We highlight this aspect of technology, not because it is the most important, but because we have learnt through this pandemic that all solutions are not equal. This pandemic has taught us not to be content with what we need today, but to plan for what tomorrow could bring.

So, what do we need when we think of a solution for today?

  • Cloud based with universal access;
  • Easy to use (reduce system training dependencies);
  • Data driven solution – capable of utilising internal, external and system generated data and triggers within business owned strategy design, testing and deployment;
  • Raw data extraction capability for 3rd party BI solutions and Decisioning or Scoring Solutions;
  • Have integrated self-service capability, or have available API’s to integrate seamlessly into 3rd party self-service or chatbot solutions;
  • Must be able to integrate into 3rd party communication platforms, credit bureau’s and any 3rd party application.

In short, a collections system must cater for bespoke data driven strategies and processes, within a secure and easy to use environment, capable of integrating into any 3rd party software or solution to cater for customer preferred engagement channels.

There’s one element which we’re going to focus on throughout this entire process, and that is the utilisation of data. In order to use data, we must be able to collect, store and analyse clean data.

The second technology solution is focused on utilising data:

    b.  Decisioning or Scoring Solutions

With data being the cornerstone of collections, data analytics and modelling are the vehicles which drives data driven strategies within your collections solution.

Decisioning or Scoring Solutions provides organisations and business users with the capability to use internal and external data within a controlled environment, to capture and apply business rules, use multiple scores within matrices, build scorecards and models, create decision trees based on available data and scores, and design decision flows within processes.

Decisioning and Scoring solutions can also feed and absorb outcomes from,

    c.  AI or Machine Learning Environment

Credit lenders use data analytics to assess potential clients and determine affordability. However, many credit lenders and debt collection companies fail to apply the same practice when dealing with defaulting clients. Collections operations have historically revolved around quantity, as opposed to quality.

What if we could increase operational effectiveness AND financial returns? What if we utilise our data within collections and recoveries to drive our strategy and efficiency?

Geoffrey Moore, the author of “Crossing the Chasm” and “Inside the Tornado” said “Without big data analytics, companies are blind and deaf, wandering out onto the Web like a deer on a freeway.”

Within the collections environment, analytical models can be created to determine: Right time and number to connect, best platform to engage, probability of payment, individual debtor instalment value, net present value settlement calculations, EDC outsourcing scorecards, legal process efficiency, probability and yield forecasting.

AI & Machine Learning environments, create the capability for companies to deploy an automated test-and-learn environment, where these analytical models evolve over time to increase model predictability, where in the past we use to do realignment of models periodically in a manual or resource intensive manner.

When using these technology items, we know that we will work our accounts in the most efficient way, and that these technology items remains vital throughout the next phases.

Let’s look at technology relating to our efforts in connecting with our customers or debtors:


When we assess collections operations in South Africa and outside of South Africa, we find that a common mistake is to design a rigid communication or queue prioritisation strategy.

We sometimes forget that all strategies must be driven by available data insights. Therefore, we will start again by looking at data utilisation.

    a.  Predictive and Prescriptive Analytics

 We have previously discussed the need for analytical models, but what models do we use to increase our connect rates?

Multiple models are available, and we can also use multiple models to create a single contact score.

We typically look at building models which predicts and prescribes: Right time to connect, Right number to connect, Best Communication Platform to engage etc.

Through analysing data, we can design our data driven contact strategy which informs us of WHEN to connect and also HOW (what platform) to connect.

Let’s look at the platforms:

We make a distinction between direct communication platforms, where we as the company initiate communication, and indirect platforms, where the customer initiates communication with us.

    b.  Direct Communication platforms

Probably the most used and known platforms are Diallers, SMS Providers, Emails and AVM’s.

But let’s look a bit deeper in dialler requirements:

        i.       Dialler Modes

Dialling modes can make or break your communication strategy, and all too often we see how the use of predictive dialling without the necessary knowledge in setting up the correct algorithms, can do more harm than good.

How many of us has experienced getting telephone calls, only to be greeted by silence on the other end? Would you be happy as a CEO of a company, knowing that about your customers experiences? Certainly not.

When looking at diallers, we need to make sure that we can use multiple different dialling modes, aligned to our dialler batches, which will provide a good customer experience, but also an acceptable efficiency level.

        ii.     Interactive Voice Response (IVR)

When we look at incoming call volumes, we need to make sure that the calls are routed to the correct area and agents. Interactive Voice Response capability can route inbound calls based on your agent’s skill sets, campaigns or any other criteria you specify. Therefore, reducing the need to transfer calls repeatedly, and wasting precious time.

        iii.     Advantages of Cloud Based Platforms

There are many advantages to using cloud based dialling platforms, but maybe the most important are:

  •    Reduced maintenance costs;
  •    Easy to setup with a fast go-live timeline;
  •    Adaptable and Scalable;
  •    High Security;
  •    Fast and uninterrupted updates.

Let’s look at indirect communication:

    c.  Indirect Communication Platforms

There are several indirect platforms on which customers can engage directly with us, from Social media to Chatbots, but most importantly we need to create a single platform of self-service which can be accessed through all indirect channels.

Self-service bots are not new to customers, but the adoption of self-service bots within the collection environment has been extremely slow, notwithstanding the customer demand and clear benefits it offers.

Millennials and Gen Z’s are forming a big part of credit portfolios, or will be forming a big part within the near future. If we look at how they engage, we will see that “texting” forms the major part of their engagement preference. That, together with the fact that collection engagements create a feeling of embarrassment, makes an impersonal platform fit for purpose.

It is however important to choose the correct bot and technology partner, in order to safeguard customer experience and reputational risk. We’ve seen too many companies “experiment” with live chatbots and lose customer engagement through the platform.

Let’s not forget about the Omnichannel:

    d.  Omnichannel

Within collections and recoveries, customer engagement forms the cornerstone of success. Most companies however still deploy a traditional communication strategy which is random and ineffective.

A Dasceq study on how intelligent omnichannel collections can improve customer experience has found that: “60% of people prefer brands that interact across multiple platforms. By 2022, people physically going to the bank is expected to drop by 36% with mobile transactions eventually composing 88% of all banking transactions.

Omnichannel is more than just “multichannel”, an omnichannel solution includes the ability to process new and updated information instantly, which in turn can automatically trigger the account to be moved in terms of the workflow or process flow, as well as triggering the subsequent strategic actions.

An Omnichannel creates consistent and strategic engagement across multiple communication platforms and devices, resulting in increased customer engagement and subsequent collections results.

Technology can assist us in making contact, but technology cannot make the right person / right party pick up the phone.

In part 2, we will look at what tools are available that can help us when engaging with the right party, as well as tools available for the negotiation process.

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