In recent years, lenders in both retail lending & corporate lending have become global networks that have linked apps on smartphones, workstations used to generate applications and sophisticated programs to manage digital loan origination system, collections and compliance.
Systems that once merely updated balances are now used to determine financial credit product marketing, in particular, whom to send offers, when to increase credit limits, when to send collection alerts etc through effective credit assessment.
But despite this, there has been a noted increase in delinquency rates, especially in micro or nano loans for both retail lending & corporate lending.
How can lenders improve collection rates and reduce NPAs, even in tough economic conditions?
1. Employing delinquency scorecards-
Lenders can leverage data by applying artificial intelligence, machine learning algorithms, robotic underwriting on customer information. This intelligence can be used to generate accurate delinquency scorecards that will provide a high probability customer behavioural prediction in relation to an individual’s current credit score in the system for lending process like loan origination system, card origination etc. Drag and drop process designers can create data driven delinquency workflows with basic or advanced internal or external data points.
2. Creating personalized recovery strategies-
Smart analysis of credit repayment history can enable lenders to create customized recovery strategies tailored to individual borrowers. Delinquent customers can be blacklisted across credit rating systems and they can lose access to future lines of credit. This can be a powerful motivator to be prompt in their repayments.
3. Developing a risk adjusted approach-
Any lending product can be digital. Seamless disbursal of lending products through effective digital lending journeys require a thorough and accurate variations of product structure, credit methodology and more importantly risk management through risk modelling system & risk rating platform. A robust digital loan origination system will continuously access customer transaction data, his digital footprint ie. monthly income, cash flows, expenses etc. Risk adjusted approach gives a thorough credit assessment of customer affordability and drastically lower nonperforming assets.
For example, Tala is an online lender in Kenya offering mobile-based nano loans via an Android application. Data driven algorithms scrapes approximately 10,000 data points from the phone (including SMS, call records, locational data, etc.) to analyze and score customers.
4. Blend tech and touch-
In the age of digital, it is all too easy to lose focus on technology. However, strong collections will need a blend of human touch and technology. Appropriate ‘right touch’ human intervention at the right time will be an enabler in collections and repayments. This will boost responsible retail lending & corporate lending by integrating both digital and human elements.
5. Financial literacy-
Though often overlooked, embedding financial literacy programmes will go a long away in boosting collections. It will help the borrowers understand the credit product features, their responsibilities and the real consequences of non repayment. Key moments in digital lending journeys can be supplemented with educational content, especially during the initial engagement and complaint resolution for smooth credit assessment.
High rates of missed or delayed payments can be significantly reduced through collections on digital channels. This strengthens the financial inclusion movement and credit environment in general.
ORIGINATIONNEXT, provides a unique risk platform with effective risk modelling system & risk rating platform combining the power of decisioning engine through robotic underwriting, analytics & configurable process designers for boosting digital collections, maintaining compliance & enhancing customer experience for seamless digital lending journeys.