Loan approval has become much easier in the recent past. But debt collection is still a daunting task which affects the productivity of lenders and slow down their operations. With increasing consumer debt, the traditional debt collection methods are no longer viable with modern customer expectation. As a lender, preparing for debt collection issues and effectively responding to delinquent customer-debtors is a must to ensure continued business growth and success.
Major challenges in debt collection:
- Lack of customer data
- Increased burden of regulations
- Failure to track and reconcile accounts
- Inability to execute new recovery strategies
Traditional debt collection is driven by focus on delinquent accounts and handled by a part of the business detached from customers. Lenders need to shift their own methods to match customer preferences- which are clearly for digital channels. Advanced analytics and machine learning can help financial organizations to have a deeper understanding of their at-risk customers. AI can help in segmenting better by considering a span of other parameters like customer behaviour along with their credit history.
Alleviating risk and elevating customer experience
Essentially firms require a technology like AI that can sit on top of their existing collection systems, act on the vast amount of data accumulated over the years, consider other parameters like behavioural and sentiment analysis to derive an effective collection strategy.
With AI based segmentation approach, firms can enhance customer experience with personalized collection and communication strategies. ML algorithms can devour high volumes of unstructured data and provide actionable insights. The built-in AI helps these applications to identify the right segment accounts that are not only based on financial ability of the customers, but also their behavioural patterns from calls, text messages and social media platforms. Thus, it helps to predict customer delinquency, assist recovery agents to call the right customer, set the right tone and gain an upper hand in negotiations.
Quick steps to make debt collection win-win
- Customer segmentation
- Auto generation of customer statements
- Omni channel orchestration
- Customer activity monitoring
- Digitized collection strategy
With the impact of digital transformation in the finance sector, it became increasingly evident that AI and ML will define the future of consumer lending. Additionally, customers of this digital epoch seek easy and convenient solutions, which further compels consumer lending companies to adopt an ML-based, data-driven loss mitigation model that is capable of analysing large volumes of structured and unstructured data. Leveraging the power of AI, organizations can drive a customer risk segmentation achieved from data driven intelligence applications that find the right balance between mitigating loan losses and enhancing customer experience and make meaning out of it. Online banking and virtual collections agents could increase payments and reduce costs for call centers, while improving customer satisfaction.
This is a win-win for the entire financial ecosystem with happier borrowers and wider business opportunities for lenders
