Saying that the world is in “a tough economic environment” is an understatement at best. Financial institutions worldwide have worked relentlessly over the past few years to remain competitive and efficient amid volatile situations.
Consider the far-reaching aftermath of the COVID-19 pandemic compounded by ongoing events like wars, economic recessions, central bank rate hikes, stringent regulations and climate change.
Few areas of banking were left untouched – and the collections function is no different.
The COVID-19 pandemic brought such extreme economic instability that most governments implemented moratoriums on defaults. At the same time, many institutions had to quickly adopt new digital services to continue serving customers – regardless of how prepared they were for that shift.
Since then, most forbearance programs that assisted customers through the pandemic have expired, causing a steep rise in default rates. According to the EBA Risk Assessment of the European Banking System, for example, there has been a significant increase in Stage 2 allocation of EU banks. Simply writing off those losses on a large scale is not a viable strategy.
What does it take to get a collections strategy right?
To succeed, financial institutions need to develop a collections strategy that reduces risk and increases collections without exceeding the operating budget. The strategy must account for factors like compliance laws, brand reputation, exposure, risk level, collections effectiveness, customer contact information viability and internal resource constraints.
Getting it right requires knowing the customer better (through a well-rounded view) and understanding each situation thoroughly enough to develop an optimal strategy. This goes hand in hand with having a flexible foundation that takes full advantage of promising opportunities arising from digital banking and leading-edge technologies like artificial intelligence (AI).
Identifying the challenges
Before establishing or revising your collections strategy, consider the challenges often affecting financial institutions. Then determine which of these are most likely to affect you – and account for them in your strategy. Common challenges often arise around:
- Accessing external customer information and maintaining up-to-date information.
- Making customer data ready to use in modeling and decisioning.
Customer profiling and segmentation
- Balancing the need for customer satisfaction with pressures to reduce costs.
- Accurately predicting delinquency rates and embedding those predictions into the collections strategy (this entails understanding each stage of collections).
- Managing different types of debt and creating customized collections strategies based on credit product nature, customer profile and risk segmentation.
- Reaching customers based on their chosen contact method – and knowing how to facilitate customer cooperation.
- Quickly testing and revising the collections strategy based on the effects of seasonality and economic cycle changes.
- Being able to use appropriate tools to build end-to-end collection strategies. Your tools should provide the capability to:
- Build and deploy models for risk analysis and segmentation.
- Incorporate rules and conditions.
- Use optimization algorithms to determine optimal contact channels.
- Test the strategy before deployment.
- Analyze the business impact via what-if analysis.
- Deploy the new strategy without needing to recode.
Tips for segmenting customers
- Understand payment behavior for different groups (risk, region, age, education) and for different contact methods.
- Know the difference between truly “bad-intentioned” customers versus those who occasionally forget or are going through temporary financial difficulties.
- Differentiate customers based on their industry, job type or current conditions (such as a disaster-driven dilemma).
Real-world tips for improvement
Banks whose collections strategies are tailored to their portfolio’s composition and risk profile generally have a smoother collections process and higher customer engagement. This approach typically leads to higher collections amounts, lower rates of non-performing loans (NPLs) and lower concentrations in high day-past-due (DPD) buckets.
There’s plenty to learn from top-performing banks that share common tactics. These banks:
- Find and maintain verified, up-to-date contact information from reliable external sources, such as credit bureaus or other alternative data sources (like government data).
- Monitor early warning signals and quickly take preventive actions based on detailed policies designed to prevent further withdrawals or reduce exposures.
- Follow up on delinquencies at an early stage to reduce the number of customers that transition to higher delinquencies.
- Maintain the flexibility to modify or create new strategies as they monitor and assess performance.
- Use external information (from credit bureaus, open banking, legal resources, etc.) to understand customer behavior and segment based on historical observations.
- Differentiate and optimize actions based on the stage of collections – keeping in mind that there might only be one chance to get it right.
- Accurately determine the optimal budget and number of resources to allocate to collections.
- Know the constraints they face due to specific regulations.
Understanding the stages of collections
- Early stages should focus on getting the contact channel right and dedicating appropriate resources and intensity to the task. Delinquencies collected between 1 and 29 days past due result in higher returns.
- Later stages require negotiation and an understanding of the best offer. This may require discounts, rescheduling, product or payment plan changes, and working with specialized debt collection agencies.
- Recovery stages may entail selling the portfolio – particularly if the underlying portfolio requires legal or other strong methodologies.
Getting the technology right
To put your collections strategy into action, you’ll need the right technology foundation. The technology you choose should support:
- Automation for processes and scheduling, rules, model deployment and continuous monitoring. You can also use automation to segment customers across delinquency buckets and risk segments.
- Flexibility for changing rules, updating models or adding new constraints as evolving conditions call for strategy changes.
- A champion/challenger approach for creating strategies.
- Performance monitoring, which enables you to analyze the effects of the optimized strategy on collections, compare to expected results and then analyze customer segmentations.
- Scenario analysis for analyzing how changes made to constraints like budget and resources have affected expected collections.
- Integration with other technologies that speed up operations and generate positive outcomes.
Learn how SAS can help you make explainable, transparent collections decisions