How we think about risk

Don’t rely on credit bureau data.

Integrate data with business judgment.

Risky customers can still be profitable.

Algorithms are flawed when a scoring model for consumer credit cards looks at the card's utilization ratio as one of the predictors of default. The algorithm believes that customers with a low debt line utilization (e.g., using just 10% of their credit limit) are safer than customers with a high utilization. For safe customers, the algorithm increases the limit, creating a circular reference.

About half of American Millennials consider Credit Score an important factor when considering whether to seriously date.

Psychologists often use a 5-dimensional framework called OCEAN

to measure personality. The "C" stands for conscientiousness – an indicator of a person's risk-taking behaviour. Signals for conscientious behaviour include purchasing insurance.

Credit officers are statistically more likely to approve loan applications earlier and later in the day due to midday decision fatigue.

No amount of data or computing power alone can find the perfect risk model.

Four humans, one bot

Clemens, Numi, Nathaniel, Daniel and Drayton make up the Sivo Risk team.

Risk that aligns with your growth objectives

Pre-built credit products:

Our risk engine includes credit products that are designed to get you started and include lending parameters, decisioning outcomes and reporting schemas to increase leverage.

Macroeconomic analysis:

Complimentary with your Sivo Debt line, our risk engine monitors the economic world around you so you can focus on your business while Sivo keep's an eye on the horizon.

Your Sivo risk team:

When you're ready to increase leverage, your Sivo Credit Risk Analyst and Numi (your AI Risk Bot) will meet with you periodically to review progress and suggest improvements.

Forward looking, always innovating

It used to be that the most reliable way to predict future risk was to review the past. We changed that.