Open Banking Software: Data & Transaction Monitoring Solutions

Open Banking: Data and Monitoring Solutions

CRIF Open Banking is a suite of solutions to evaluate customers and manage processes using PSD2 data.

CRIF open banking solution enables access to payment accounts to accelerate creditworthiness evaluations, for consumers and businesses, categorizing customer account transactions, profiling spending behaviours and revealing related development opportunities.

Thanks to CRIF ML and AI technology, financial institutions can leverage their customers’ transaction data (current account, credit etc..) with accurate categorization for specific profiling , KYC/KYB and indicators for effective risk avoidance plans and loss reduction.

The Open Banking main features are:

Open banking
Access to Account
KPI calculation
Score calculation
Account transaction categorization
Cash flow Indicators
Customer portfolio risk monitoring
Customer portfolio profiling
Marketing intelligence insights

Covered industries

Banking

Insurance

Telco & Media

Energy & Utilities

Manufacturing

Solution details

Enhancing creditworthiness assessments

NEOS is the open banking solution that enables access to payment accounts in order to accelerate consumer and business creditworthiness assessments, categorizing customer account transactions, profiling spending behavior, and identifying related development opportunities.
Firstly, the solution allows PSD2 consent acquisition and a secure and smooth connection to bank accounts through an intuitive user interface.
Then, the categorization engine, based on an advanced machine learning algorithm, enables account transactions to be read and aggregated into specific categories.
Finally, advanced analytics produce an innovative credit score and a set of advanced KPIs developed from spending/saving behavior patterns that allow commercial relationships to be developed.

Early warnings to prevent credit default

CATCH is a solution that provides insights into the customer base by leveraging account transaction data. It is powered by a proprietary categorization algorithm based on machine learning and artificial intelligence that turns unstructured data into structured insights. By analyzing a customer portfolio, CATCH identifies potential credit default warnings that can be dynamically updated to monitor portfolio evolution.