In the realm of customer engagement for debt collections, the banking and financial services sector has traditionally relied on conventional methods such as letters and phone calls along with a one-fits-all approach. However, this bulk application of strategy with limited engagement modes has often resulted in below-par experience for both lenders and borrowers.
Nevertheless, in today’s era of hyper personalization, customers anticipate being treated as distinct individuals with unique preferences, needs, and circumstances. They expect lenders to offer the same level of tailored services and experience that disruptors in other industries are providing.
The tremendous growth of fintech companies, widespread smartphone accessibility, extensive internet penetration, convenient digital payments, seamless data sharing, long-term initiatives for financial inclusion, and the growing demand for financial services have all played a significant role in transforming the sector. There is an ongoing endeavor to enhance the quality of interactions between lenders and borrowers.
The Reserve Bank of India (RBI) has taken measures to provide adequate regulatory frameworks by introducing guidelines for digital lending and related areas. These guidelines are designed to align with broader objectives, which include ensuring that India leverages the $1.3 trillion fintech opportunity and protecting customer interests.
The effective utilization of AI, Machine Learning, and predictive analytics presents a wide array of possibilities for comprehending data, gaining actionable insights, and resolving various issues in the realm of financial services, including debt collections. Data science provides sophisticated capabilities, detailed procedures, and innovative use cases for extracting patterns and deriving profound, actionable insights from diverse data sources.
Data science has contributed to enhancing the speed, simplicity, and user-friendliness of processes and systems. Its advanced capabilities hold immense potential for the financial services industry as they facilitate the breakdown of silos, equip teams with tools that streamline their work, facilitate decision-making at multiple levels, foster transparency, standardize processes, and enable innovation.
Enhanced borrower understanding through data analytics
Through the analysis of demographic, transactional, and behavioral data, banks and other lending institutions gain a deeper understanding of their customers. This process allows them to identify relevant patterns and extract profound insights, enabling them to approach collections with a more strategic mindset. Examples of this include tracking borrower responses to different types of communication messages, determining the optimal timing and frequency of interactions, employing risk-based segmentation to enhance targeting and ascertaining the propensity to pay. Data analytics further consolidates customer data, providing a comprehensive view that proves valuable when automated bots or agents engage with customers.
Data analytics helps understand the borrower better
By analyzing demographic, transactional and behavioral data, banks and other non-banking finance companies are able to understand their customers better, identify patterns and gain deep insights that help them adopt a strategic approach to collections. Tracking borrower response to various categories of communication messages, determining the appropriate time and frequency to interact, and following risk-based segmentation for improved targeting are all examples of these. Data analytics further compiles customer data into a comprehensive picture, which is useful when automated bots / agents are interacting with customers.
The understanding of borrowers plays a crucial role in achieving valuable outcomes in debt collections more efficiently and cost-effectively.
Taking insights-driven decisions in debt collections
The usage of advanced software solutions in the lending industry, allows harnessing the power of AI capabilities, ML models, and analytics, enables effective segmentation, deep behavioral analysis, predictive modeling, and the implementation of relevant collection strategies. These solutions provide valuable insights derived from accurate data, offering early warnings of potential defaults and delinquencies. Anticipating when an individual is likely to default on payments allows for the development of personalized solutions that greatly benefit lenders.
By leveraging insights obtained from data collection, lenders can also craft precise and efficient responses for borrower interactions. The challenges posed by persistent follow-up calls from lenders are alleviated through the application of data intelligence. Lenders are equipped with the necessary knowledge to cater to their customers, providing them with the right information at the appropriate times.
For instance, a simple illustration of this is the inclusion of single-click payment links in targeted communications that are pre-filled with borrower-specific details. This streamlined approach empowers borrowers to easily resolve pending repayments, simplifying the process and enhancing overall efficiency.
Cultivating personalized customer relationships
In a market where financial services are increasingly becoming commoditized, the differentiation lies in the experiences and relationships formed with customers. By leveraging data-driven insights to create highly tailored experiences based on individual preferences, needs, and requirements, superior customer experiences can be designed.
Data analytics plays a crucial role in developing advanced recommendation engines that provide customers with personalized choices. Through demographic and geographic intelligence derived from data analysis, lenders can craft language- and region-specific responses for borrowers. Even for customers who may not be digitally savvy, the reception of concise and relevant vernacular voice messages or voice bots proves highly encouraging, cost-effective, and optimal for lenders. This approach ensures the establishment of a personalized relationship that enhances customer satisfaction.
Mitigating fraud and errors for enhanced security
Banks and other lending institutions confront critical challenges like credit fraud, data inaccuracies, incorrect entries, and system issues. However, the advent of intelligent systems, advanced data analysis capabilities, seamless API integrations, and automation improvements has simplified the resolution of these challenges. Multiple data sources are now available for authentication, ensuring accuracy and reducing the risk of fraud and errors.
Even in debt collections, technological advancements are integral in minimizing the likelihood of fraud and streamlining operations, particularly in field collections. Through the digitization of the entire process, complete transaction transparency is achieved. Embedded checks at each step, real-time tracking of agents, geo-fencing, and instant digital receipts contribute to a significantly improved customer experience. These measures provide heightened security and efficiency in debt collection operations.
Providing connected and tailored experiences
Borrowers now expect their lenders to have a comprehensive understanding of their lifestyle, digital preferences, and financial needs, acting as trusted financial advisors. They desire technologically savvy lenders who can engage with them in real-time, seamlessly integrated into their daily activities at a time and place of their choice.
This customer shift in preferences has resulted in the emergence of embedded finance, anytime-anywhere access, super-apps, and Buy Now Pay Later (BNPL) services. The rise of FinTech and digital lenders can be attributed to the demand for faster, simpler, and user-friendly service experiences. When applied to debt collections, these advancements have transformed customer engagements, making them more relevant, productive, and effective.
By leveraging technology, lenders can now reach out to borrowers through their preferred communication channels, at the desired frequency and time, in their language of choice, providing specific details regarding their accounts and transactions. Even the payment links embedded in the communication is personalized with specific details of the borrower to facilitate seamless self-service of repayment transactions. This level of personalized focus is highly appreciated by borrowers, as it saves them time, eliminates harassment, and simplifies the resolution process.
Thanks to digital transformation and the extensive use of data analytics, lenders can reimagine debt collection procedures, discover more efficient methods of engaging with borrowers, and ensure compliance with rapidly evolving regulatory requirements. The time has come to fully leverage the potential of digital technology and data in debt collections, and those who embrace these innovations early on will have a competitive advantage.
The article has been written by Anand Agrawal, Co-Founder and CPTO, Credgenics