Analyse the creditworthiness of your clients with Score
Are you interested in the creditworthiness of your customers to adapt your sales processes? Use our credit scoring API to protect yourself against default risks.
Score by Pledg
credit scoring api
Credit is an essential part of the modern economy, but it also carries risks. Companies that make loans need to be able to assess the creditworthiness of their customers. That's why we've developed our credit scoring engine, Score by Pledg, that uses machine learning algorithms to analyze users' banking transactions or context to predict the likelihood of default.
Our credit decisioning engine has proven its relevance to minimize risk while maximizing volume.
Our scoring algorithms can analyze a multitude of data, allowing them to be relevant in any context.
Our credit scoring API returns an answer in less than half a second, without the need for customer intervention.
Why trust our
credit scoring API?
For the needs of its activity, Pledg has developed a credit decisioning engine using the latest machine learning technologies.
Thanks to them, we obtain the lowest overdue rate on the market while guaranteeing acceptance rates above the standards.
Overdue rate and number of transactions as a function of the Score result (from 0 to 1000)
What data can Score process?
One API and two ways for you to benefit from our expertise:
By providing us with a transaction history as returned by an open banking solution of the market, in accordance with the DSP2 regulation.
By transmitting us contextual data about a customer: the content of his basket, his purchase history, his contact details, his technical profile...
With Score, you gain access to a scoring model based on a state-of-the-art data analysis and machine learning technology, capable of processing several hundred data points to quickly and efficiently assess the risk of default.
Our algorithms adapt to all contexts and continuously learn from the data they analyze, in order to make an ever more accurate assessment of a client's borrowing capacity based on banking and contextual data.
Learn more about our API, Score ?
Frequently asked questions
Assessing a customer's creditworthiness or ability to pay and their risk of default is essential for many actors, financial organizations, insurers, merchants, etc. In general, estimating a customer's ability to pay and repay is important to reduce the risk of non-payment and ensure a healthy business relationship between the parties.
Protect your business against
- Payment default
- Financial failure
- Inability to pay
- Failure to meet payment deadlines
- Excessive debt
- Late payment
- Inability to repay
The most common method for estimating a customer's borrowing, payment, and repayment capabilities and risk of default is through the use of credit scoring, an assessment of a borrower's risk of default based on his or her credit history which is used by lenders to determine the likelihood that a borrower will default on a loan.
Another method commonly used to assess a customer's payment and repayment capabilities is financial data analysis, which measures a customer's creditworthiness and debt load. This analysis can include information such as debt-to-income ratio, equity ratio, and total debt-to-income ratio.
Lenders can also rely on sophisticated scoring models that use so-called "alternative" data, such as online payment behavior, banking history, and purchasing habits, to better assess a borrower's ability to pay and risk of default.
It is important to note that estimating a customer's ability to pay and repay is not limited to a single method and that a combination of several methods can be used to provide a more complete and accurate assessment of a customer's ability to pay and repay. Finally, the analysis of a client's ability to pay and repay can be enhanced by using simulation models that test different scenarios, such as changes in interest rates or late payments, to better assess risks and potential impacts on loan repayment.
Our decisioning tools for your :
- Credit risk measurement
- Insolvency risk prediction
- Loan analysis
- Credit rating
- Default risk assessment
- Ability to pay and repay estimation
- Credit score
- Loan decision
To assess the risk of non-payment and secure your payments, our scoring algorithms and machine learning prediction models process banking criteria such as income level, debt level and payment history and/or contextual parameters such as transaction amount, product and industry information and buyer or payment data. This scoring method allows you to better understand the financial situation of your customers and to make relevant and instant decisions regarding the granting of credit or loans, the management of default risks for recurring payments, subscriptions, etc.
Our model is based on an exhaustive analysis of the financial and non-financial data of the buyers, allowing us to take into account a large number of variables in order to evaluate their ability to pay. Our credit scoring solution enables proactive management of payment risks by identifying the most at-risk customers in advance and offering appropriate solutions to reduce this risk. Taking into account contextual parameters, such as industry and buyer information, in our scoring methodology allows for more personalized and relevant credit or lending decisions.
With its huge capacity in terms of data that can be processed and/or are already processed today, our scoring model will help you make your decision, after a simple API call to send us the data you have collected. It will build on what it has learned about our business and will continue to learn and improve on your own market.
The models are therefore regularly updated and adjusted to adapt to market changes, your industry and the context of each call to our API, Score.
Pledg continuously relies on its team of experts in scoring, data analysis and machine learning to ensure the reliability of its scoring models.
We understand the importance of not slowing down sales processes, which is why our solution is designed to easily integrate into your existing workflows, to provide you with a quick and accurate assessment of your customers' ability to pay.