Experian has developed solutions for AI and Machine Learning models that provide a concise explanation of the outcome, allowing businesses to access a range of advanced methodologies within a explainable and transparent framework. Experian’s AI and ML model validation framework is scalable and adapted to each client’s internal requirements.
We can help our clients validate an expert model and a neural network within the same framework. Innovation in data and analytics tools, alongside the application of artificial intelligence and machine learning, means you can implement the most predictive models and insight to inform your business strategies.
Avoid unnecessary time and expenses
Our machine learning and analytics services help businesses avoid unnecessary costs so you can stay focused on developing predictive solutions and strategies that will drive business ROI.
Build, deploy and customize models quickly
Our team can help you build and deploy statistical tools (attributes, models and decision strategies) seamlessly with leading-edge methodologies on platforms that achieve sub-second decisioning.
Custom solutions based on business needs
AI analytics and automation enable your organization to customize scores and attributes to optimize the predictiveness of your models while expediting decisions on low-risk applications or current accounts.
Use the latest AI/ML models and techniques
Your organization can benefit from the most advanced, leading-edge machine learning solutions, harnessing the power of gradient boosted or neural network methodologies to more traditional, tried-and-true methods (such as decision trees, linear regression). Use predictive analytics and modeling to make better decisions for your business.
Explainable, compliant and ethical
Our automated processes and interpretable models keep decisions transparent and fair, even with the most modern machine learning techniques.
Feel confident in your automation with high-quality data inputs
Transform data into deep customer insights. Our machine learning and analytics solutions allow you to seamlessly connect to hundreds of data sources to remove duplicates, correct errors and standardize formats. With improved data quality comes a more comprehensive view of your customers, business operations and more.
The Experian Approach: Boosting Explainability
Now that the regulators are setting the path to using ML models in the calculation of capital, a crucial step in the process is the ability to explain the model outcomes. When consulted about the use of ML models, our clients mention the explainability issue as one of the major concerns. Experian has developed an advanced approach to improve explainability of ML models, so that outcomes of these models can easily be explained and understood by stakeholders or customers.
Explanations are in the form of variable importance ranking which can then easily be translated into reason codes. This is achieved by different advanced techniques which derive importance score for each feature based on partial dependencies and SHAP values. SHAP quantifies the contribution that each feature brings to the prediction made by the model. From that, a confidence level is taken to understand the real importance of individual features.
Experian has also developed a standardised framework for developing and deploying ML models with the required level of explainability. This allows the process to be 50% faster than the normal modelling processes. Experian's Explainability plug-in is compatible with tree-based ML models.