LendingRobot’s Fully Automated Mode

What is Fully Automated mode?

 

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Fully Automated mode is easy to use.  Pick a risk tolerance, click save, and LendingRobot begins investing. But what exactly does it do?

We designed our Fully Automated mode with four features to simplify and provide better returns: loan cherry picking, smart risk tolerance, optimal cash deployment, and adaptive note selection.

Loan Cherry Picking

Not all notes within a grade are equal. Some low interest rate “A” and “B” notes will default, while higher interest rate “E” and “F” notes may mature.

The LendingRobot model tries to identify the loans with the highest potential return. Our analysis shows that whatever their risk level, loans tend to default at the same point in the loan’s life. See our hazard rate analysis.

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Our intelligent algorithm is based on a statistical model for predicting probability of default. While Lending Club and Prosper do a good job in assessing risk, it is still possible to identify statistical outliers, who are “penalized” with a higher interest rate more than the actual risk would require. Fully Automated mode discovers these notes and submits order requests within 500 milliseconds of a loan’s release. See details about our methodology.

Smart Risk Tolerance

Peer Lending is shown to be uncorrelated with stock market performance, making it a good addition to overall portfolio return. But all investments carry risk of loss of principal, and past performance is no guarantee of future results.

An investor’s risk tolerance depends on many factors, including length of investment and total investment size.  In Fully Automated mode, moving the slider from conservative to aggressive applies more stringent requirements based on a loan’s grade. At a 6% expected return, a C, D, or E grade loan would need to pass through a tougher risk tolerance in order to be included. A 9.9% expected has no additional risk tolerance; it buys purely notes with the highest expected returns.

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Optimal Cash Deployment

Portfolio diversification is important to mitigate risk. Returns will converge toward the total market average as the number of invested loans increases. If you want to show off at a cocktail party, you can even explain its due to the Central Limit Theorem, and that the returns follow a normal distribution. As we increase the number of loans, the risk goes down precipitously. LendingRobot has calculated that the total returns is positive in (almost) when portfolios contain at least 146 loans:

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But cash drag, or the effect of undeployed cash, can weigh down overall portfolio return.

Fully Automated mode carefully weighs the effects of cash drag, the expected return of the available note supply, and portfolio diversification then calculates an optimal cash deployment schedule and appropriate the per-note dollar investment amount accordingly.

Adaptive Note Selection

LendingRobot has invested heavily into data science, and each passing month presents additional insight into how notes perform. We use this information to continue our investigation into superior statistical models.   Clients utilizing Fully Automated mode benefit by having their loan selection automatically updated whenever a new model is released.

You can read more about our prediction algorithm or reference our performance chart.

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