ROI-positive data from external vendors is just a few clicks away
Tint Augment® uses AI-powered technology to significantly reduce time and cost required to discover and to evaluate thousands of variables from third-party vendors in context.
Dataset upload
You upload dataset in .csv format (only step required from you)
Data augmentation
Tint.ai augments your dataset with data from a curated list of partners and measure value using machine learning techniques
Smart evaluation for your problem
Tint.ai reports the ROI of each variable based on your specific use case
Superpowers for you, hassle-free
ROI
Improve the accuracy of your decisions while balancing data costs
Holistic evaluation
Capture interaction effects between features in context.
Magical easy of use
Discover and evaluate new relevant data sources effortlessly.
Secure
Bank grade security in all data exchanges.
Private
Your dataset is kept in a sandbox environment and is not shared with other parties. All data is deleted after test is over.
Privacy and GDPR ready
The processes are fully compliant with GDPR requirements.
Measure the impact of external data on your problems
Online marketplaces
Improve accuracy of onboarding models
Machine learning models unlock real-time onboarding decisions and enable growth with low risk. Tint.ai identifies external variables about users that enrich the training set and improve predictive performance. For example, do users that have a prepaid phone have higher risk? Would the predictive power increase when this information is crossed with the age of the email used?
Insurtech
Underwrite smarter risks
More data about a user improves underwriting and increases profitability. By using Tint.ai, insurers quickly identify external data that helps them refine their models and grow with profitable revenue. For example, do weather and traffic information impact the risk of a car accident? How to go beyond zipcode? Or does employment information affect the probability of a claim?
Fintech
Reach customers beyond credit scores
Financial institutions rely on imperfect data like credit score, which exclude millions of customers, to make lending decisions. By using Tint.ai, lenders can identify signals that complement, or even replace, credit scores. For example, can employment and education information help predict the risk of users with thin file? Are there other signals that can provide better ROI than credit scores?