Credit scoring is the process enabling lending businesses to determine how likely a lender will default its loan. This process is utilizing different data sources and less or more is designed around the business logic of the lending organization. In some markets like USA and UK, there are credit scoring bureaus assigning credit score derived from credit files and history of a particular person. In other markets, the credit scoring is up to the lending institutions, not matter banks or nonbank financial institutions like leasing companies, consumer finance companies, telecommunication companies, etc. Such businesses hold the credit risk and they need a solution like credit scoring. In this blog post, we explain why credit scoring as a service is the most viable option for lending businesses of different size and markets. Let us share with you the three main options in front of a company dealing with such kind of financial risk.
How AI & predictive analytics fuel credit scoring-as-a-service
Just think of it! Without credit and lending businesses, we would not be able to buy a house or appliances when we need them. Business would not be able to grow, expand and innovate at the desired pace. Credit is the fuel of any country` economy and this is not a secret. But what is fueling credit and lending businesses? How do they decide if you are eligible for a particular loan or not?
Fully automated data mining. Possible or not?
Now-a-days huge amount of rough data is available. At the same time many businesses need of fast (real-time) decisions in order to survive and grow in the dynamic competitive environment.
To manage in time with such large dimensional problems automated (without human intervention) analytical solutions are needed. In many cases, like the two examples below, the data mining task and a subsequent decision making should be run as an automated workflow.