The Three Big Impact Debt Collection Tools To Implement In 2018
Posted by Perry de Jager
February 21, 2018
Any tool that can optimise your collections strategy and improve efficiencies in your operation, is sure to make an impact on your collected yields. In our years helping collections operations to optimise and improve their collection strategies, we’ve found that data-driven debt collection tools offer the optimal solution to optimise and improve your recovery yields and increase your business revenue.
With that in mind, and with the sheer volume of data at your disposal in 2018, here are the debt collection tools that will have the biggest impact and that you should look to implement this year:
Call centre coaching bots
Machine learning and advanced data analytic techniques are often used in combination with behavioural sciences to develop coaching bots. Coaching bots for call centre agents guide and support agents through calls in real-time, offers them easy access to information and motivates and inspires high performance. Bots can deliver real-time performance metrics and recommended actions or treatment during calls to help agents realise the best possible outcome for every call.
Agents can build on existing relationships by viewing customer or account data visually during a call, such as how long they have been a customer/account, last call outcome and analytical insights e.g. customer behaviour; individual preferred instalment; rehabilitation eligibility; discount offers etc. Improved efficiency and customer experience will result in an increased staff satisfaction and financial outcome.
Yield forecasting tools
How do you currently manage month-end expectation? Do you compare last month, same time or last year, same time or a combination of the two? Do you take seasonal anomalies into consideration?
While using data is a good start, basic analysis is often unreliable and insufficient. It creates inter-month inaccuracies resulting in an inaccurate month-end expectation. It does not provide recommended pro-active remedial action to implement and when to implement in order to achieve desired result.
Standard comparisons will not give you the answers you need to create a strategy that will see results accurately. For collection operations, a critical success factor is the ability to predict month-end outcomes accurately and an early stage of the billing cycle.
Using predictive analytics and machine learning methods, it is possible to forecast yields accurately, and predict which remedial actions will have a short or long term impact if you are not tracking to your targets. Use these insights to inform your business and collections strategy.
The fact that the call centre environment is drastically changing and incorporating technology will lead to the end of the days of call centre agents performing mundane tasks like providing balances, statements, giving banking details: to be delivered by self-service AI bots. AI bots use a combination of data analytics, machine learning and deep learning algorithms to not only perform tasks but also to learn from every interaction to improve subsequent communications and new generation customer experience.
With the inclusion of AI solutions into operations, call centre agents focus will be as intended, to perform specialist duties like resolving default account queries, negotiating for optimal repayment arrangements, and educating debtors to become credit wise. Your collections strategy going forward should be looking to include both call centre agents and AI technology in symbiosis, as this will ensure your collection yields are higher than ever.
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.