Adopting AI for Credit and Lending Decisions: 4 Common Data Mistakes

Are you interested in adopting AI and machine learning to grow your lending? If so, the journey to realizing AI and machine learning for your credit and lending decisions essentially begins with data. Handling and preparing a massive amount of data for AI and machine learning can be uncharted territory for many. If you’re looking […]

The Role of Time Series in Loan Data Analysis

In the first two blogs of our four part blog series we covered structured and unstructured data in underwriting and the importance of ontologies, or agreements of what the data mean. This brings us to the next topic, time, and its impact when analyzing loan data. Time series modeling is a very popular and powerful way to […]

The Importance of Data Ontology in Big Data Loan Underwriting

This is the second blog of our four part blog series with topics pertaining to structured and unstructured data in big data loan underwriting. In our first blog of the series, we provided an overview of structured and unstructured data, its impact in data driven underwriting, and how to integrate unstructured data into machine learning […]

Structured and Unstructured Data in Data Driven Underwriting

Gartner estimates that 80% of enterprise data is comprised of unstructured data. Yet until tech advances afforded by machine learning, structured data has been the go-to for data analytics and models. The advances in computation power have afforded organizations the ability to analyze and incorporate unstructured data into their business decisions. One could even say, unstructured […]

Automated Loan Underwriting: Trust Science Scoring Explained

Want better predictions on bad loans, higher originations, and accelerated lending cycles to impact your bottom line? Automated loan underwriting can help you achieve these goals. In this post, I’ll walk you through our Trust Science credit scoring mechanism using a sample customer loan performance with anonymized test data. The example will not only demonstrate […]