7 Minutė; -tės; -čių skaitymo 2020-11-19
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Five ways banks can transform their collections processes

7 Minutė; -tės; -čių skaitymo 2020-11-19
Related topics COVID-19 Banking and capital markets Financial Services Banking transformation Financial Services Asia-Pacific
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  • How a Canadian bank personalized its collections strategy using machine learning (pdf)

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  • How a large consumer bank identified efficiency opportunities within its collections environment (pdf)

    Atsisiųsti 1 MB

Better use of data, technology, and process automation can help banks adapt their debt collection models to curb loan losses in the future.

In brief
  • An inbound repayments model approach relies on predictive and behavioral analytics to create more personalized debt solutions.
  • Process automation and predictive analytics can help banks safeguard against regulatory penalties.
  • Greater digitalization will enable banks to proactively reach out to customers at an earlier stage, helping to improve customers’ financial well-being.

In our first article, we explored how banks have an opportunity to reimagine their debt collection techniques and strategies now, before facing a wave of non-performing loans (NPLs) in the months ahead. The global economy is entering a saw-toothed economic recovery and, as a result, every bank is dealing with the same conundrum: how to provide ongoing support to customers while looking ahead to the rising cost of NPLs.

Banks have already put aside record sums1 for NPL losses, the cost of which could spiral if customers begin to fall behind on their payments. With large swathes of retail customers and small-to-medium-sized enterprises (SMEs) expecting to need financial assistance to avoid collections, banks must act now to devise a set of unique debt treatment strategies and solutions. Most financial institutions, however, lack the necessary resources or technological capabilities to deliver satisfactory outcomes using their existing debt recovery process. To contend with the scale of NPLs coming their way, banks must dedicate greater time and investment in improving these capabilities.

By transforming the collections model – from a labor-intensive outbound approach focused on finding customers who can pay — to a loss-preventative inbound operation in which banks offer pre-approved treatment strategies and personalized communications — financial institutions can incentivize customers to proactively reach out to them. This approach would deliver more personalized, effective customer service, at scale. For example, the inbound offer could be no mortgage repayments for six months or a temporary reduction in the interest rate thereby reducing the payment so that the customer reaches out proactively to accept it or another solution.

There are five areas banks must focus on to reimagine the collections model in practice. 

 

Why uniting collections with compassion creates better outcomes

In this webcast, panelists discuss how lenders and customers can prepare for a surge in loan defaults.

 

1. Transforming the role of collections recoveries

Even before the pandemic, the average collections rate was below 20%, the lowest in 25 years. Moreover, banks’ outbound collections strategies have been costly and inefficient, with the success rate of these campaigns standing at roughly 5%.

Transforming the collections model from a labor-intensive outbound approach to a loss-preventative inbound operation can drive greater operational efficiency and improve workforce capabilities. Crucially, if banks can implement an inbound model now, they will be better prepared for periods of uncertainty in the future.

If banks can implement an inbound model now, they will be better prepared for periods of uncertainty in the future.

This would also fundamentally change the nature of the payment collections role – from a frontline debt collector or administrator to a financial advisor. In keeping their workforce engaged – and training them to display greater empathy and compassion to customers – banks can communicate with customers in difficulty in a better way, which will be critical to the success of an inbound campaign.

Moreover, an inbound repayment model also offers bank employees a greater sense of purpose – that what they are doing is the right thing for customers during this challenging time. This sense of purpose will be particularly important in attracting new talent and giving greater job satisfaction to those working in this area.

2. Process automation is key

Banks will come under intense regulatory scrutiny to ensure the fair and consistent treatment of customers in the months ahead. Process automation and predictive analytics can help banks to remove human bias or arbitrary judgments from their decision-making processes. This is one way to help banks avoid regulatory fines. However, integrated testing programs that review the end-to-end collections process, and subsequent customer outcomes, are also vital.

Generally, investment in the automation and streamlining of back-end processes is a must. If banks fail to do this, they will face accounting reconciliation and amortization challenges, which will ultimately impact their balance sheets. Generally, banks have a short window of 30 to 60 days to process loan modifications – should they miss this, they will face a significant accounting challenge at scale.

Self-service capabilities, for example, can help customers learn about their options before ever talking to their bank, and are likely to be relatively straightforward (e.g., payment rescheduling). However, this does not remove the need for specialist expertise in more complex situations, such as cross-product holdings for retail and larger SMEs.

3. Inbound digital channels

Banks have a duty of care to help customers in need. If they can apply a digital layer across this experience, it will help them deal with more customers, quickly and effectively. To successfully devise an inbound debt management strategy, banks need to show a higher level of understanding of their customers’ needs and situation, across every channel. By making greater use of their digital channels, banks can provide customers with notifications about debt modification options; for example, giving customers greater awareness and understanding of what a modification program involves and what they are signing up for.

An inbound campaign also relies on banks making better use of virtual agents and chatbots to answer some basic payment questions. As a result, when customers call their bank, the discussion will be more streamlined and efficient.

Greater digitalization will enable banks to proactively reach out to customers at an earlier stage, helping to improve customers’ financial well-being and driving stronger long-term value.

Banks that apply a digital layer across their debt treatment strategies will be able to deal with more customers, quickly and effectively.

4. Data: the power of knowing your customer

Banks that make better use of data to understand each customer’s situation can apply this knowledge to a set of pre-approved, personalized debt solutions. The closer banks get to Q1 2021, the more certainty they will need about which customers are going to default or who will need their loans modified. To prepare for this as best they can, banks will need to expand their data sources – from legal and employment sources to credit and financial records – along with predictive and behavioral analytics, to better ascertain the customer situation.

Banks already have a substantial amount of customer data at their disposal, but they must begin to use and apply it in a more effective way. This will benefit an inbound collections model by not only building a more satisfactory, personalized customer experience but also boosting the likelihood of recovery returns. Banks have the ability to really drive their level of data intelligence now, to personalize the solutions they are offering in the months and years to come.

5. The next-generation customer engagement model

An inbound model has the potential to create a powerful effect on the banking sector’s next-generation customer engagement model. Investing in a proactive approach that treats customers uniquely and fairly holds promise for greater customer retention and increased customer satisfaction.

The closer banks get to a period in which defaults are likely, the more they will know about which customers are going to need additional support. An inbound model emphasizes the need for each institution to demonstrate a higher level of understanding of their customers’ needs and particular situation.

In practice, this means approaching customers in a compassionate, personalized way, seeking to understand their personal circumstances and how financial lenders can help. Banks must apply predictive analytics to assess likely customer behavior and profile their customer base accordingly. As a result, this will grant banks greater insight into real-time customer behavior in the marketplace – which will give them the confidence to pre-approve treatment strategies where appropriate.

Banks have a duty of care to help their customers – and an inbound collections model will help them manage customers in a more compassionate way. If banks fail to prepare now for the wave of defaults that are likely to hit in the months ahead, they risk regulatory penalties, a significant increase in costs, and reputational risk.

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Rodyti išnašas

  • How a Canadian bank personalized its collections strategy using machine learning.

    pdf (982 KB)

Rodyti išnašas

  • How a large consumer bank identified efficiency opportunities within its collections environment.

    pdf (1 MB)

Santrauka

To transform the collections model from an outbound to an inbound approach, banks must dedicate greater time and investment on improving their technological capabilities to incentivize customers to reach out to them proactively.

Apie šį straipsnį

Related topics COVID-19 Banking and capital markets Financial Services Banking transformation Financial Services Asia-Pacific
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