Case Studies

Commercial Debt Recovery Case Study: Improving Energy Collections Performance

Commercial debt recovery requires more than persistence alone. It depends on using the right workflow, the right channel, the right contact timing, and the right treatment strategy for each debt cohort. In this case study, Recoveriescorp partnered with a major energy retailer to improve recovery performance across inactive final-stage accounts, including residential customers and small to medium enterprises.

The result was stronger recovery rates, increased portfolio share, and a consistently low complaints ratio. This example shows how a more tailored commercial debt recovery strategy can improve collections performance without compromising quality.

The Challenge

The client wanted to improve collections outcomes while maintaining a positive customer experience. Two debt cohorts were referred into the program: accounts under $2,000 and accounts above $2,000. These were inactive final-stage accounts with a blend of residential customers and SMEs.

The challenge was not simply to recover more debt. It was to improve performance in a competitive panel environment while protecting service quality and preserving positive customer outcomes. That required a more considered commercial debt recovery approach rather than a one-size-fits-all collections model.

Different debt sizes required different treatment

Lower-balance and higher-balance accounts often respond differently to recovery activity. An effective recovery model needs to match communication style, operator effort, and channel selection to the likely value and complexity of the debt.

Residential and SME accounts behaved differently

The portfolio included both residential and SME accounts. That meant timing, workflow design, and channel choice all needed to be adjusted to improve engagement and maximise commercial debt recovery outcomes.

Performance needed to improve without increasing complaints

Collections performance can sometimes be lifted at the expense of customer experience. In this case, the objective was to achieve better recovery rates while maintaining low complaints and protecting the overall quality of the recovery process.

The Commercial Debt Recovery Strategy

Recoveriescorp used workflows and modelling informed by large-scale energy-sector insights to strengthen performance from the outset. The strategy focused on matching treatment pathways to account type, channel preference, and likely recovery behaviour.

Best time of day to contact customers

Energy data and prior portfolio insights were used to determine the best time of day to contact both residential and SME customers. Better contact timing helped increase engagement rates and supported stronger recovery performance.

This is a strong example of how a smarter collections strategy can improve commercial debt recovery by aligning activity with customer behaviour rather than relying on fixed contact routines.

Channel preference modelling

Previous learnings on channel preference were used to improve how residential and SME customers were contacted. This helped ensure customers were engaged through methods more likely to generate a response and move accounts toward resolution.

Hybrid delivery model

The program used a hybrid collection model combining Australian and Fijian teams. This ensured the right people, with the right skills, were managing the right accounts regardless of delivery location.

For organisations reviewing commercial debt collection models, this demonstrates how hybrid delivery can support better efficiency and stronger account handling without weakening control or quality.

Digital-heavy approach for lower-balance accounts

For accounts under $2,000, the strategy used a digital-heavy treatment model. This cohort achieved an average recovery rate of 36%.

This shows the role of digital collections in lower-balance debt cohorts where speed, scale, and lower-friction engagement can improve recovery outcomes.

Operator-focused approach for higher-balance accounts

For accounts above $2,000, the strategy used a more operator-led approach. This cohort achieved an average recovery rate of 8%.

Higher-balance accounts often require more direct human engagement, stronger negotiation capability, and more tailored handling. This is where a structured commercial debt recovery model can create stronger value.

Benchmarking Performance Against the Incumbent

Recoveriescorp outperformed the incumbent provider from the first month of the program and maintained a positive month-on-month variance across the full reported period :contentReference[oaicite:0]{index=0}

Month-on-month outperformance

The benchmarking table in the PDF shows positive variance against the incumbent across every month reported, including:

• +8.22% in October
• +3.14% in November
• +7.81% in December
• +4.79% in January
• +1.23% in February
• +6.39% in March
• +1.33% in April

These results show that the uplift was not a one-off spike. It was sustained through a more effective commercial debt recovery model :contentReference[oaicite:1]{index=1}

Increased portfolio share

As performance improved, portfolio allocation shifted from a 50/50 split with the panel member to 60/40, with confirmation that Recoveriescorp would move to a 70/30 split next. This is a strong signal that improved recovery performance translated into greater client trust and expanded responsibility.

Why This Commercial Debt Recovery Approach Worked

The program performed well because it did not treat all accounts the same. It used better data, stronger treatment design, more relevant contact methods, and a delivery structure aligned to account complexity and likely customer behaviour.

Better data led to better treatment design

Sector insights and prior energy portfolio learnings helped improve contact timing, channel strategy, and workflow logic. This made recovery activity more targeted and more commercially effective.

Digital and operator-led channels were used selectively

Lower-balance accounts benefited from digital-heavy treatment, while higher-balance accounts received more operator-led handling. This helped align cost, effort, and likely recovery value more effectively.

Customer outcomes remained strong

The case study reports a complaints ratio of just 0.0058%, with none of those complaints relating to Recoveriescorp’s services :contentReference[oaicite:2]{index=2} This matters because strong commercial debt recovery should not come at the cost of unnecessary complaints or poor customer outcomes.

What Organisations Can Learn From This Case Study

This case study shows that commercial debt recovery performance can improve materially when workflow design, segmentation, and channel selection are based on real portfolio behaviour rather than generic collections assumptions.

Commercial debt recovery should be segmented

Different account sizes, customer types, and channel preferences require different treatments. Better segmentation helps recovery teams allocate effort more effectively and improve outcomes across the full portfolio.

Lower-friction channels can improve recovery

Digital pathways can work well for lower-balance accounts, especially where customer effort needs to be reduced. For many portfolios, this can strengthen both conversion and cost efficiency.

Performance and customer experience can improve together

The case study demonstrates that stronger recovery rates and low complaints are not mutually exclusive. A well-designed commercial debt recovery strategy can improve both at the same time.

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Talk to Recoveriescorp About Commercial Debt Recovery

Recoveriescorp helps organisations improve commercial debt recovery through tailored workflows, smarter segmentation, better channel selection, and low-friction customer engagement strategies.

For businesses looking to improve recovery performance, outperform incumbent providers, or build a stronger commercial debt collection strategy, a more targeted model can deliver measurable gains.

Contact Recoveriescorp to discuss how a better commercial debt recovery strategy can improve collections performance, reduce complaints, and strengthen long-term portfolio outcomes.