Advice for debt collectors in pandemic times: watch your language

Banks have braced themselves for the first wave of struggling borrowers in response to the coronavirus pandemic, but a second and potentially larger wave lies ahead when it comes time to collect.

Accordingly McKinseyUp to a third of US jobs are “at risk,” meaning they face potential furlough, layoffs, or become unproductive due to the pandemic.

In the interim loan forbearance and deferral programs have provided a runway for banks to prepare for such a critical moment. But when these utilities end a new era of customer loyalty and collection efforts need to take shape.

During this time, well-managed collections can effectively unleash a “growth lever” while acquisition and cross-selling proceed slowly. Past crises have shown that banks with strong customer relationships that demonstrate empathy and flexibility towards their customers weather the storm better than those that don’t.

It starts with the language used to communicate with customers – language that is both mindful and data-driven.

First, financial institutions need to identify vulnerable customers quickly and intervene early (if they haven’t already).

The rapidity of the impact of the coronavirus on the economy has shocked many customers and tried to get a grip on their new financial situation. Banks that quickly identify at-risk customers and use a multichannel approach to communications will keep those customers engaged and responsive during times of financial distress.

This will allow banks to maintain these relationships well beyond the end of the crisis. The key here is to improve and protect the customer experience to reduce chargeouts and losses at the institution.

The pace of the debt collection crisis and the call center burden on creditors will come fast and furious. Banks and lenders need to move beyond the “we’re here for you” phase and implement systematic, data-driven customer retention capabilities as part of the pre-collection and early collections processes.

Look for simple signals in the data – such as B. Changes in deposit flow and credit activity or geographic location and employed industry – to create predictive segmentation.

Regulatory guidance recently issued in response to the pandemic offers significant scope to offer loan modifications early and reach at-risk customers before they miss a payment. This is a critical window of engagement. Early intervention also gives a creditor more leeway to achieve a preferred ranking in the order of creditors demanding payment.

Second, one of the biggest short-term challenges banks face is adopting a more attentive, context-sensitive, and tone-adapted approach to brand communications—while retaining customer payments and managing losses. Mindful messaging balances empathy with performance.

The language used during this time is crucial and need not be left to guesswork when it can be informed by data and artificial intelligence to balance effective messaging with empathy and sensitivity. Most messages are written by a copywriter using pattern recognition and intuition. But natural language generation, a form of AI, can augment that experience and create deeper human connections than a copywriter could alone.

If every lender uses similar, generic language, the message will never get through to desensitized customers. Prioritizing important information and providing customers with clear, concise next steps helps them know what to do and when to do it.

For example, by using AI-based language insights, phrases like “We strive to give you extra peace of mind” are more effective when communicating with customers in the pre-collection journey. Conversely, banks should not use language that conveys undue urgency or references “news,” which should be left to actual updates about the pandemic.

Third, don’t put yours Call center on the back burner.

Call center agents are at the forefront of the customer experience and are critical to building, maintaining and repairing customer relationships.

Unfortunately, many call centers are seeing triple-digit increases in demand, even as some have made the Herculean effort to move large groups of agents to work remotely.

With many banks now adopting digital banking at a greater pace to meet the influx of customer demands, long hold times result in poor experiences. What call center agents say and how they say it can do a lot to create or destroy customer loyalty and value.

To amplify these efforts, many inbound calls should be routed to self-service channels, resulting in significant cost savings and freeing agents to handle more difficult cases.

The most innovative banks are already arming their call centers with intelligent routing to match specific customers to specific agents and using AI-tested speech to improve the performance of interactive voice prompts and call center scripts.

This increases call routing rates and encourages adoption of self-service channels.

Finally, maintaining customer trust should be every bank’s priority so that when customers return to a stronger financial footing, they know where to turn for their next long-term loan or investment. Also, customers who now feel a greater sense of loyalty may be more willing to keep up with their payments, even if they have to do it in smaller increments over a longer period of time.

As this recovery takes shape, it is critical for banks to develop a clear understanding of consumer insights, new segmentation and a new foundation for acquisition, cross-selling and customer retention at scale.

However, as the current crisis ebbs and flows, banks need to go a step further to ensure their messaging is aligned with changing customer expectations. The cost of such a mistake means significant customer churn, increased payment defaults and (again) declining reputation.

Banks can successfully mitigate the debt collection crisis and call center surge by engaging early, identifying the most vulnerable customers, and shifting to sensitive, attentive messaging through the use of AI and data-driven customer engagement. In a crisis of this magnitude, machines could actually be the ones helping banks become more human.

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