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AI-Based Credit Risk Tools Can Be Ruined By Noisy Data

The Horizons Tracker

One’s credit score is often hugely important, with it very difficult to secure substantial loans, such as mortgages, without a healthy credit rating. The researchers themselves used AI to analyze vast quantities of consumer data, which allowed them to test various credit-scoring models. Risk assessment.

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How Cashless Payments Affect Our Credit Worthiness

The Horizons Tracker

Assessing credit risk. Traditionally, lenders use a range of criteria to assess our credit risk, but the new wave of fintechs entering the market tend to rely more on alternative data that goes beyond your credit score. Verifiable records.

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What Is Bad Credit and How Can It Affect You?

Strategy Driven

Having a bad credit score is something nearly 68 million Americans have to deal with. Your credit score is a way for lenders to see how much risk is associated with lending you money or approving you for a line of credit. With the help of this program, you can automate the credit report dispute process.

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Use Data to Fix the Small Business Lending Gap

Harvard Business Review

Today, community banks are being consolidated and larger banks are relying more and more on data-driven credit scoring to make small business loans—if they are making them at all. My recent Harvard Business School Working Paper on small business credit explores new technology-driven entrants in the world of small business lending.

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Use Data to Fix the Small Business Lending Gap

Harvard Business Review

Today, community banks are being consolidated and larger banks are relying more and more on data-driven credit scoring to make small business loans—if they are making them at all. However, all these online models depend on developing accurate new predictive models of credit assessment, often using new sources of data.

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A Practical Approach to Reading Signals in Data

Harvard Business Review

With fairly few signals in their models, the FICO score doesn't have the ability to distinguish between credit risk in a generally high risk group. For example, thousands of signals can be used to analyze an individual's credit risk. The way to address this is to add more signals.