Scorecards

Along with the decision engine, TurnKey Lender provides its users with the ability to use Scorecard. Scorecard processes available details of a potential lender to assess the risks associated with the loan.

The basics behind both scorecard types appear quite simple:

  1. Assign specific risk scores to specific details of the customer.

  2. Calculate the total risk score

  3. Define the risk level for this risk score

There is nothing more to it if these are custom scorecards, as those rely on the client's own experience and improvement effort.

However, if a built-in scorecard is used, it is the TurnKey Lender who keeps it efficient. To do so, we are using an AI-based algorithm that is trained to improve the scoring efficiency on an ongoing basis. Let's take a closer look at each of the stages. 

Assign Risk Score to Customer Data

Scorecard management is available in the System → Decision engine → Scorecards section. When creating a custom scorecard, you can manually assign scores to specific details.

At the top of the card, there is a specific piece of customer details, e.g. “Resided at Address (months)”. Below are some categories and the risk score associated with the category.

The higher the score, the more reliable is the client.

For example, in the card on the left, the longer the customer has resided at the same address, the lower the risk is.
As for the employment duration, the customer is most reliable if they’ve worked in the place for over five years, and is almost just as reliable if the employment duration is 2 to 3 years, however, the risk is a bit higher in between the third and fifth years at the same place (as this is a recent time for people to change employer). Applicants who have worked less than 5 months at the same place are the least reliable.

 

In the Custom card, if the value is numerical, you can add/remove ranges (“categories”) for each piece of customer information and assign a specific value to each of them. If the value is one of many, the card will include all options available for your company.
Some of the common customer details used in scoring include, for example, number of dependents, education, company size, job title and employment duration, property in possession, credit bureau score, number of previously fully paid loans, etc.

 

 

Total Risk Score and Risk Segments

Now, when a loan application is processed, the system will calculate and add up all the risk scores (defined manually or specified in the built-in card). After that, the system looks at the score, and defines what risk level it corresponds to.

These details are managed in the “Risk segments” tab. There are five risk segments allocated by the risk level from low to highest + default. If the client decides to use a custom scorecard, they must specify score ranges for each risk level. They can also define the probability of dafult, expected distribution, note-down the odds and recommendations, and define what should happen to the loans withing this segment (automatically approved, automatically rejected or sent for further manual review). As it’s been said before, for customer cards, these values lie solely on the client.

AI Magic of the Built-In Cards

For built-in card, TurnKey Lender runs analysis of the scoring success (big data analysis) and the is continuously improving the risk segment allocation and its details, as well as, in case of need, notifying TurnKey Lender team about the need to create additional categories to improve the scoring capabilities.

This is the Risk Segment tab available today:

As you can see, the whole card can give the maximum of 1000 points - for the most reliable clients. Therefore the risk is low for clients with the score above 545.

 

 

When using this built-in card, the clients can modify the recommendations and further actions on the application (auto-approval, auto-reject or manual review). However, probability of default, expected distribution and odds are calculated based on the existing data analysis (cannot be edited by a client if built-in card is used) and are updated as the system conciders previously scored customers.

 

 

 

 

 

 

Further Data Analysis

As the system analyzes results of the scoring, they become available in the Scoring reports. These help you see how well the built-in card is doing its job or assess the quality of your custom scorecard and improve it if necessary.

 

Conclusion

This way, TurnKey Lender clients can undertake to use their own cards and improve them on their own (using Scoring Reports as a reference point) or use our built-in scorecard, that is not visible to the clients (due to copy-righted information safery concerns related to the algorirthms used to improve it) but is updated by TurnKey Lender and is continuously improved using machine-learning AI algorithm.