Predicting and preventing loan defaults with proactive credit risk management
Solve your customers’ debt problems ahead of time
Detect changes in clients’ income
Monitor behaviour of clients and their households
How can you move from reacting when customers default, to proactively anticipating loan defaults and solving the problem in advance?
Do you already have a vast number of loan clients, with many of them potentially in danger of being unable to repay? Do you react to their situation only after they miss their repayment date?
Wouldn’t it be better if you could predict these missed payments? If you could “see into the future” and know in advance which clients are likely to default?
Imagine being able to check the credit quality of each individual customer on an ongoing basis. It may seem like a challenge, but it can be done – and almost in real time – by loan default prediction.
Our big data solution monitors customer behaviour and gives you a customised early-warning system. This loan default prediction means that customers with financial difficulties will be flagged up sooner rather than later. So you can address issues before they arise – and before a customer defaults.
This is proactive credit risk management. It enables you to intervene at the earliest opportunity so that you have more options for remedying the situation and avoiding losses.
Our approach will help you predict future defaults
How do you predict loan defaults?
Enhance your scoring by using predictive models and move from reactive to proactive credit risk management.
How do you recognise that a debtor has lost or changed their job?
Apply our salary detection tool to be notified of each individual client’s job and salary changes.
How do you detect that a client has significantly changed his or her spending habits?
Monitor your client’s transactions in real time for suspicious behaviour like overspending or increased withdrawals.
How do you identify the behaviour of a debtor and their whole household?
Take advantage of our social network identification so you’ll know who belongs to a household and be able to monitor their financial behaviour as a whole.
How do you detect a client in the debt spiral?
In-depth cash-flow analysis of transactions can reveal clients who cover repayments with other loans.
Be aware of your clients’ increased spending and cash withdrawals as soon as this occurs. Our real-time monitoring system uses behavioural models to identify unusual overspending. When the system detects spending deviations, you’ll receive prompt alerts.
Our salary detection tool processes transactional data and notifies you of your clients’ work-life events. Identify clients’ regular sources of income, wages or bonuses. Detect their pay cuts and raises. Find out about job changes plus employer profiles and their wage policies. See income stability for proactive risk scoring.
Where clients are married, it’s simple to use that information and see that both parties share a family budget. But our unique social scoring engine can detect other clients who belong to the same household – family members, fiancés, people in long-term relationships or friends and flatmates. This means you can assess the credit risk of household members together.
We use complex machine-learning models to process clients’ historical data and transactions in combination with their social scoring. This allows us to determine typical features and patterns of behaviour that lead to a future inability to make debt repayments. Our solution will assess the probability of future default for each client.
How it works
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