Our customised analytical solutions help you to have a greater understanding of your individual customers’ needs, behaviours and financial wellbeing. Extensive experience in risk analytics means that we can help with solutions throughout the customer lifecycle.
Data is at the heart of everything. It provides the raw understanding that fuels decisions. But, it is what you do with it and where it takes you that counts. We combine advanced tools and techniques with expertise in credit risk to help you bring data to life and turn it from information into insight throughout the customer lifecycle.
Tools that predict the probability that an applicant will behave in a particular way, helping you to make effective automated decisions.
Helps to retain and grow the right customers for your business
Ways to proactively segment your portfolio and manage your collections strategy enabling you to support your customers.
Application Scorecards are tools that allow organisations to predict the probability that an applicant will behave in a particular way, helping businesses to make effective automated decisions.
The most commonly used application scorecard for credit, predicts the risk of a customer paying or not. This supports you as a business to make automated, accurate and consistent decisions on whether to approve, review or decline applicants.
Application Scorecards are statistical models typically developed using an institution’s historical data for the relevant product, if sufficient such data is available.
If relevant historic data is not available, for example if the scorecard is required for a new product, then Experian can provide representative generic data from their extensive data sources.
After the data has been extracted and verified it is critical to design a modelling data sample that is representative of the target portfolio and allows the resultant scorecard to meet the business objectives. This is achieved through detailed analysis of the available criteria, portfolio stability and behaviour. The model can then be developed using several methodologies, with linear and logistic regression proving to be the most common. Experian has more than 30 years of experience in successfully developing credit risk models for financial institutions.
In addition to your data, captured at the point of application, the most predictive application scorecard developments include credit bureau data which provides a detailed view of credit history. In addition to scorecards, Experian can provide extensive retrospective credit bureau data to support application scorecard developments.
Do you know who your most valuable customers are? Are any of your customers struggling to repay their debts with you or elsewhere? If you want to activate the right customers, whilst mitigating the risks, knowing how and where to focus your efforts by maximising the use of all available data and insight in everyday decisions is key.
We develop statistical models combining your data with our data alongside expert consultancy to predict how a customer will behave in the future. Behavioural scoring is used throughout the life of a customer relationship to inform management strategies for each customer, whether managing and supporting customers with financial difficulties or extending the relationship with customers through enhanced features or new products.
When accepting a new customer’s application for credit, or agreeing to extend credit for existing customers, assessments should be made to indicate the likelihood that the customer will be able to manage financially and will be able to comfortably repay the amount borrowed.
In addition, it is important to recognise that customer circumstances may change over time and lenders will need to understand them on an on-going basis in order to offer appropriate support throughout the relationship.
In today’s climate, the prioritisation of accounts in collections plays an integral part in controlling bad debt, knowing who to prioritise and in treating customers fairly. For example, how frequently and through which channel to contact them can be difficult balance to strike.
Getting it wrong can potentially cause a negative experience for the customer, and for your recoveries.
Collections scorecards can support this process. For example, using scoring within collections may help to identify those customers who require less interaction, or contact, to prompt a payment.
This can allow you to focus on the individuals who may need further contact or support to bring their account up-to-date. The ability to make this distinction is essential, as companies often face the further challenge of balancing limited resources in this area as well as making sure that customers are treated fairly.
Models can be developed to predict a customer’s propensity to pay. They can also identify the likelihood that customers may experience further financial difficulties in the future.
We use our extensive experience of the credit industry to help with the development of collections scorecards.
This could include support and advice in creating an appropriate sample for development, as well as building the required models. Additionally, our knowledge of enhanced strategy modelling can be utilised to help get the most from scorecards and ensure that the score is utilised in such a way it benefits your comprehensive collections strategy.