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

The Horizons Tracker

It’s increasingly common for financial providers to use AI to produce credit risk scores, but research from Stanford University highlights how bad data can cause such systems to go astray. The post AI-Based Credit Risk Tools Can Be Ruined By Noisy Data first appeared on The Horizons Tracker.

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How Cashless Payments Affect Our Credit Worthiness

The Horizons Tracker

The users of cashless payment systems can benefit from this approach by virtue of lower interest rates as they generally have a lower risk of defaulting. The authors argue that these benefits could drive more people towards cashless payment systems. Assessing credit risk.

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Auditing Algorithms for Bias

Harvard Business Review

Influenced by this community, Accenture Applied Intelligence* has developed a fairness tool to understand and address bias in both the data and the algorithmic models that are at the core of AI systems. The model falsely predicted that the person had low credit risk. How does the tool work?

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How P&G and American Express Are Approaching AI

Harvard Business Review

If firms had previous experience with expert systems, they are familiar with some of the necessary organizational and process changes arising from contemporary cognitive tools. Gupta at American Express reminded us of the Authorizer’s Assistant, which was one of the more successful rule-based expert systems of the late 1980s.

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For Successful Collaboration, Think Outside the Box

Harvard Business Review

He explained that his organization was highly functionalized with separate units for sales, trading, investing, portfolio management, credit, risk, and operations; some of which reported to him and some to the corporate center. She and her customers were basically told to get used to the delays.

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A Dedicated Team of Problem Solvers Can Help Big Companies Act Like Lean Startups

Harvard Business Review

We have a lot of newer businesses that come to us for credit and we need to do due diligence on them. So it’s an incredibly labor intensive process for us to verify whether they are a good credit risk.” ” Haller’s team was able to put together a prototype and present it to the client within 90 days.

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Predictive Medicine Depends on Analytics

Harvard Business Review

Think of the colleges that are increasingly able to identify students at risk of dropping out and intervene before they do. Or lenders’ enhanced abilities to gauge credit risk. Think of it as a 360-degree/24-7 support system. Energy, agriculture, insurance, retail, human resources — no industry is unaffected.