Credit Bureaus have accumulated over 100 years of data. They have combined millions of scattered attributes into an organized database. To utilize their data, we have to organize your portfolio performance data to take advantage of this information.
Portfolio Performance Data
To leverage modeling techniques, we need to organize your portfolio performance data. Whether it’s a first payment default or a revenue-based model. The key to have an accurate model developed is the organization of your application, loan and payments data.
Third Party Data
Sometimes, attributes from credit bureaus are not enough to figure out your default or conversion issue. One of those cases is fraud-related charge offs. In these instances, we might need to integrate a third-party data set to detect fraud. We can help you to analyze these cases.
A strong portfolio requires strong analytics
We can help you increase conversion rate, reduce default rate and capture fraud-related losses.
There are thousands of credit risk attributes from the credit bureaus. Which one should you use to build a better mousetrap? We can help you siphon through these attributes and build a better model.
Machine Learning Models
Let’s face it. ML and AI are all the rage today. But the underlying science behind these “new’ techniques is the same, regression analysis. We’ve got the fundamentals down and we also have these new models for you to use.
The key ingredient to a well-managed portfolio is not how well you’ve developed a single model. It is how well you can continuously remodel over and over again base on the latest learned datasets. We have a process that we use to constantly improve upon the existing models.
A future proof model has both accuracy and lift. Most importantly continous learning.
A well-designed credit modeling process addresses the way you can continuously improve upon the existing models. Only by continuously learn from newly collected data would you be able to control all aspects of your loan portfolio.
We have software engineers and statistical analysts under one roof. We all work towards a common goal which is deploy high-end statistical models with accuracy and speed.
Speed is Everything
Our decision engine is built in an in-memory database. The reaction time is within milliseconds. We’ve also found the most optimal way to connect to various credit bureaus which will safe you money and time.
Model Accuracy and Implementation Accuracy
Often, we see a well-designed model is implemented incorrectly which will result in millions of dollars lost and potential compliance issues. Our statistical engineers work with our software engineers hand in hand to conduct thorough post implementation quality assurance.
We deploy the best technology not only in modeling services but also with our decision engine services.
A well-designed model is as good as the execution engine. We deploy, maintain the best and the fastest models in the world.
Credit risk comes in a variety of forms. Intent to pay is one of the most elusive targets to model against. Sometimes physicological driven default doesn’t appear within someone’s credit profile. However, sometimes, they leave tale-tale signs in other places that you might be able to use to detect their intentions.
Ability to Pay vs. Intent to Pay
Ability to Pay is where the borrower has the ability (income or cash flow) to repay their debt. This assessment might be made at the time of acquisition but the borrower’s true “Intent to Pay” might not be realized until they default on their loan repayments.
First Party Fraud
First Party Fraud is slightly different than the ability or intent to pay. First-party fraud is defined as the applicant fraudulently stating their identity and income or cash position at the time of application. For the sole purpose of defrauding financial services.
Whether it's credit risk or fraud risk. We can help you to reduce both.
Leverage our decades of experience with portfolio management and credit risk management, we will help you achieve your goals.