Polski
Deutsch
with generating texts and giving us quick responses. Right now, artificial intelligence can tell what your credit score is. How does it work, and is it possible that AI can define it better than bank employees? Below you will find all the pros and cons of AI based credit scoring.
Table of Contents
- Credit Scoring AI and GenAI in the Banking Industry – What Does It Look Like?
- How Does AI Credit Scoring Work?
- AI Credit Scoring Models
- AI Credit Scoring Is Great, but…
The revolution of AI is not only connected
Credit Scoring AI and GenAI in the Banking Industry – What Does It Look Like?
As the SAS company mentioned in “Your journey to a GenAI future: A strategic path to success in banking”, right now 60% of banks are using GenAI. The AI fintech market jumped to $11.59 billion in 2023, marking a 26.8% growth rate compared to 2022. Analysts predict that the banking sector will save $1 trillion by 2030 because of AI. As Juniper Research reported, AI and credit scoring services will reach $44 billion by 2028 (https://www.sas.com/content/dam/sasdam/documents/20250124/your-journey-to-a-genai-future-a-strategic-path-to-success-in-banking.pdf).
These numbers are growing rapidly as banks are starting to see the real benefits of combining credit scoring powered by AI with next-generation AI models.
GenAI helps banks not only speed up the decision-making process but also reduce bias and personalize the customer experience. A great example is synthetic data, already used or considered by over 60% of banks (https://www.sas.com/content/dam/sasdam/documents/20250124/your-journey-to-a-genai-future-a-strategic-path-to-success-in-banking.pdf).
How Does AI Credit Scoring Work?
In the banking industry, AI is often implemented to support risk evaluation and calculate credit score processes. But that doesn’t mean artificial intelligence can do it on its own. The tool needs a lot of data and, of course, employees who will feed and rule it with tons of information.
It relies on traditional sources like credit history, outstanding debts, and payment records; alternative sources such as mobile payments, telecom data, rental history, and utility payments; and behavioral indicators like cash flow trends, checking account information, and transaction patterns.
Usually, the process of AI credit scoring is based on data preparation and cleaning. Then, the system identifies relevant variables through feature selection. Next, the dataset is split into training and validation sets. Thanks to this, the trained system recognizes patterns. Finally, its effectiveness is evaluated and adjustments are made.
How does it help? First of all, it makes the process faster and gives multidimensional insights about your potential clients. Filling out credit applications manually can be time-consuming, and credit scoring AI software can speed up the process by analyzing the data instantly and giving a clear decision based on predefined criteria. The system combines the data from multiple sources, and that’s why it is able to prepare a more comprehensive calculation.
AI Credit Scoring Models
Credit scoring using AI can check if a person’s financial situation meets the criteria for getting a loan. But that’s not all. Ai credit scoring software can also assess credit risk. The system implements solutions that reduce the risk of borrower insolvency by flagging potentially defaulting borrowers. Different functions, such as automatic borrower rating or scheduling subsequent risk assessments, can help minimize the risk.
AI Credit Scoring Is Great, but…
As was said before, AI for credit scoring can help make better decisions in a faster way. But taking a loan is a serious matter, and AI is not perfect and probably won’t be for at least a couple of years, so don’t take it for granted. AI has its limitations, and banks need to safeguard customers’ sensitive personal information.
Ask your bank employee to double-check the data. A big threat appears when the data is subjective. Then, a credit scoring model can suggest biased solutions. So it’s very important to make sure at the beginning of the process that all the information you put into the AI system is correct.
Sources:
https://www.netguru.com/blog/ai-credit-scoring
https://www.sas.com/content/dam/SAS/documents/marketing-whitepapers-ebooks/ebooks/en/your-journey-to-the-genai-future-114042.pdf
