Deep learning based AutoEncoders for Fraud Detection.
Continuous Model Improvement to counterfeit fraudsters
Power Business with automated business intelligence report
Our data engineering involves mining data from mainframe in case of financial services operating on legacy systems along with line items from purchases, invoices, complaints, etc.,
We enforce strict privacy and regulatory guidelines with trust and safety as our core principle in mining financial data.
Merchant Health is continuously analyzed for any irregular signals by ingesting financial data and credit bureau data and applying Natural Language Processing (NLP) to identify the cash flow pattern.
Our Fintech solution aims at Increasing customer lifetime value by underwriting more applicants while reducing frauds and complying with regulations and audits.
Over the course of time, fraudulent activities have gotten smarter to overcome the archaic obstacles and have also resulted occasionally in huge losses to companies in terms of monetary worth, brand value and user experience.
Our Fraud Detection Model identifies the users who tend to commit fraud while staying in the threshold limits of these rules and do not get detected otherwise.
Our unified dashboard offers real-time insights along with any risk and fraud mitigation found in loan underwriting or credit card processing.
We support user friendly visualization tools with customizable option.
We are here to truly “democratize AI”. Machine learning companies today have been focused on helping with building AI models, but in order to truly democratize AI and make it truly accessible to everyone, companies need to be ready to also ‘manage’ AI, not just build it. The AI talent gap is real, and we will help address it by reducing the dependence of expert engineers in managing AI systems.