Selling loans is the top priority for every bank.
But, the work doesn’t stop there.
Non-Performing Loans (a.k.a a sum of borrowed money whose scheduled payments haven’t been made by the debtor for at least 90-180 days <Source>) is the biggest threat to banks globally, with the value of NPLs to small and medium non-financial corporations in European banks amounted to a whopping 117 billion Euros in the 2021 financial year alone.
With the rise of Non-Performing Loans (NPLs) worldwide, banks need to reduce their exposure to risk by streamlining their collection processes.
The first step towards that is to investigate the underlying causes of the problem:
- Lack of regulations leading to weak credit management mechanisms and absence of credit-score institutions
- Weak and outdated risk management frameworks
- Competitive pressure to reduce costs and increase efficiencies that affect the due diligence process for loan provisions
- Lack of data to personalize collection approaches according to the needs of each individual customer group/demographic
- Limited visibility into the activities of sales agents, thus hindering timely management intervention
Most banks also don’t try to understand the profiles of at-risk customers who directly affect NPLs, which worsens the issue.
According to a report from EY, debt recovery processes in most banks are flimsy because they do not have the necessary tech capabilities to navigate the massive scale of NPLs that are coming their way.
Here’s what they had to say about how banks should reformulate and restructure their outlook toward collections:
“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.”
Moreover, according to a report by McKinsey, “by enhancing risk models and making more consistent decisions, banks can reduce the risk of nonperforming loans (NPLs) by 10 to 25 percent”
To create efficient customer payment behaviours, agent collection behaviours, personalized approaches (which can directly lower the risk of NPLs), banks need tech and data that can:
- Provide visibility into the most relevant on-the-ground metrics to quickly set up, evaluate, and iterate plans
- Enable proactive, personalized outreach that is based on insights into customer payment behavior and agent activity patterns
- Prompt next-best actions based on data-driven intelligent suggestions that agents can take to reach desirable outcomes. These next best actions and nudges can also coach sales managers for better insight and control
Optimize processes through system-triggered actions for pre-due date and post-due date scenarios (through follow-up)
By creating efficient pathways to customer personalization, banks can reduce their exposure to NPLs and target at-risk customers more proactively in their collections process.
In order to do this, banks need to strengthen their risk-management system, gather data that they can use to gain more visibility into on-the-ground metrics, use tech to understand next-best practices and optimize their decision-making processes.
A smooth collections process is just as important to a bank’s growth and stability as efficient lending!
