For every business objective there is an answer: How to choose your scorecard?
With more than 5 years of experience and over 200 scorecards behind, our team of analytical professionals is fully focused on Scorecards development to provide you with the best predictive models for your business needs. The primary beneficiaries of Creditinfo’s scoring model developments are Credit Bureaus and Financial Institutions including banks and non-banking lenders. Debt collection agencies, telecommunication companies and other utilities providers, on-line and in-store retailers are also amongst Creditinfo’s scorecard customers. Outsource your scorecard development with us to rely on our professional experience to make better business decisions.
Written by Alexandra Aproiants
What are the things you would like to predict?
For every business objective there is an answer. Fraud Scorecard will help you to protect your business from external fraud by identifying typical profiles of those customers who, already at the time of application, do not intend to pay back their loans. At the same time, the Default Scorecard will evaluate a customer’s stability and detect high risk of their potential defaults in the future.
Collection Scorecard will help to improve the results of your debt collection efforts by finding adequate treatments for your debtors and reducing unproductive activities.
Obviously risk is not the only factor in business profitability and scoring does not seek to manage and predict only risk. Our Marketing Scorecards allow you to maximize your marketing campaign performance and boost your profitability by targeting the right customers with “just-in-time” product offers.
With the help of our Loyalty Scorecard you will get to know when your customers’ loyalty is at risk. It helps you to better address your customers’ needs and ensure their retention.
Anticipate rather than react!
What type of customers do you target?
Since loans can be categorized as personal or a business loans, scorecards applied to individuals and businesses should also differ. While Individual Scorecards are built based on solely personal data, Business Scorecards use available information about the company.
Experience shows that while evaluating business loans lenders should also consider information about the business’ owner(s), shareholders, board members and related companies. This is the principle that is used when combining all available information about the business and connected individuals’ histories into the Business Blended Scorecard.
The same principle can also be used while assessing personal loans. Personal Blended Scorecard is a combination of people’s personal data with available information on related persons. This, for example, is the most optimal way of assessing of loans with several co-applicants and/or guarantors.
What data can be used for the prediction?
To make a business decision it is usually wiser to use detailed data analysis rather than intuition alone. In creating its scoring models, Creditinfo often uses data from the loan application to create a so-called Application Scorecard, and customers’ historical credit behaviours for the Behaviour Scorecard creation. The combination of both application and historical data, when available, is also a recommended approach.
But when there is little to no credit history data available, then any data is an advantage. It is statistically proven that there is a strong correlation between customers’ creditworthiness and their social behaviour. Social Scorecards are based on social networks data and can help in assessing customers when classic scoring fails because of a lack of credit data.
When there is no data at all for a statistical scorecard, there is still a solution available. Using our knowledge and experience in multiple regions we provide our Expert (knowledge-based) Scorecard.
Head of Scoring Development in Creditinfo Solutions