Marketplace lending using AI: Acredius as the ChatGPT of credit risk scoring

Although ChatGPT is well-known for using Artificial intelligence to answer your most difficult questions, the power of this technology extends far beyond that. AI and machine learning (ML) can also be harnessed to revolutionise many industries, and the financial sector is no exception. 

With the increasing availability of data and the advancements in AI and ML technologies, lenders have a powerful tool to assess credit risk. This empowers them to make informed lending decisions. Acredius, a leader in AI-powered lending, has been using AI to create value for its customers since 2017. In this blog post, we will compare and contrast the ChatGPT model with the Acredius AI credit risk scoring model and highlight how data and AI change credit risk assessment.

What is ChatGPT?

OpenAI developed ChatGPT as a large language model. It trains on a massive corpus of public data, including websites, blogs, and other online sources, generating answers to written text queries. The model employs natural language processing (NLP) techniques to analyze the text and offer relevant answers.

What is the Acredius AI Credit Risk Scoring Model?

Acredius AI credit risk scoring model is a proprietary AI-powered solution that assesses the credit risk of borrowers. The model is trained on diverse data sources, including public loan tapes, Acredius loan tape, and research papers data. This training enables it to predict the probability of default and interest rate. The model uses different regression and classification algorithms to make predictions.

Data, the Key to Accurate AI Models

The quality and diversity of data influencing AI models’ accuracy heavily rely on their training. ChatGPT, for instance, undergoes training on publicly available data, which might not portray real-world scenarios accurately. Furthermore, infrequent updates to the data create a one-year gap to the accurate date.

On the other hand, the Acredius AI credit risk scoring model employs a more diverse and representative data set. This comprehensive set encompasses loan tapes, research papers, and other pertinent data sources. Consequently, this training approach yields an accurate and robust model capable of making more precise predictions. Furthermore, frequent updates to these datasets facilitate the adaptation of the model to the market’s most recent and representative trends.

What Sets the Features Apart?

While ChatGPT and Acredius AI credit risk scoring models have similarities, several key differences exist in their analysis features. ChatGPT focuses on language, length, and other text-based features. In contrast, the Acredius AI credit risk scoring model incorporates diverse features beyond financial information. This includes data on the applicant’s geographic location, industry, social media profiles, and other alternative sources. This allows the Acredius model to make a more comprehensive credit risk assessment and provide more accurate predictions.

Bringing AI to the Real World

ChatGPT is available online, with freemium and premium options for users. On the other hand, the Acredius marketplace deploys the AI credit risk scoring model in the real world through its instant offers for borrowers, which are available online. This allows borrowers to receive credit risk assessments in real-time and make informed decisions about their financial future.

In conclusion, AI and ML can potentially revolutionise credit risk assessment. Additionally, by comparing the ChatGPT model with the Acredius AI credit risk scoring model, we can observe how data quality, diversity, and comprehensive features can significantly impact the accuracy of AI models.

Innovating for a Greener Future

Acredius commits to using AI and ML for the greater good. Our company has recently developed a green scoring solution in partnership with EHL, which assesses the environmental impact of loans and helps to promote sustainable lending practices. This innovative solution highlights Acredius’s commitment to using AI for positive change and its leadership in AI-powered lending.