Moneying
Moneying is a platform that applies Artificial Intelligence techniques for the analysis of financial transactions and textual communications from customers.
The combination of Machine Learning and Deep Learning techniques allows you to optimize compliance activities in the context of anti-money laundering and risk management controls.
The use of Text Analytics techniques allows the automatic processing of written communications from customers, automating the management of claims, complaints and interactions with investigating bodies.
Advantages
The application of Artificial Intelligence techniques for compliance analysis (RegTech) and for the detection of fraud or risk scenarios represents a decisive competitive advantage for banks and fintechs, which operate in a complex regulatory where the monitoring of financial crimes and compliance management are expensive and inefficient operations.
Furthermore, Big Data Analyitics tools allow financial institutions to offer greater transparency, increasing customer satisfaction and stakeholder trust, while AI can also support Customer Relationship Management thanks to Natural Language Processing techniques, Classification of texts. and Query Answering.
Main features
Moneying enables Big Data processing in the financial sector by simplifying compliance processes.
Scalability
Moneying is a highly scalable platform that integrates technologies for Big Data analysis and can be deployed both on premises and as-a-service via cloud.
Big Data Analytics
Moneying provides over 50 algorithms for data processing and customer profiling. The algorithms can be combined in various ways, defining flexible and highly customizable processing pipelines.
Security
Moneying has a user authentication and profiling system that allows restricted access to data analysis and information, thus ensuring high security standards in customers’ operational contexts.
Web interface
The analysis of suspicious cases takes place via a powerful and easy-to-use web interface. Users can extract customized reports and have information dashboards available relating to the activities carried out.
Moneying
Capabilities
Moneying applies Machine Learning and Reasoning techniques to analyze financial transactions for AML and Risk Management purposes.
Through pattern recognition and profiling techniques it is possible to identify fraudulent or illegal behaviors, thus enabling the evaluation of the customer’s risk profile (KYC).
Furthermore, Moneying uses Natural Language Processing algorithms in combination with machine learning and deep learning models to analyze the texts of the tickets proposed by the users and support the resolution of the same.
KYC
Moneying enables customer profiling on the basis of a «Risk Profile», evauated on the basis of objective and subjective characteristics of the customers. All customer information are integrated in order to make available a “customer file” that contains all the specific information of B2C and B2B customers.
Risk Management
The platform allows the execution of analysis for risk assessment; users can customize the data analysis processes aimed at calculating appropriate Key Risk Indicators.
Anti Money-Laundering
Moneying offers features for the processing of Big Data related to financial transactions, in order to identify money laundering scenarios. The platform offers a module for generating reports of suspicious transactions.
B2C and B2B monitoring
Moneying provides a module to manage the sanctioning of B2C or B2B customers who violate contractual agreements in the use of payment instruments.
Claims and complaints management
The platform offers an application module to manage claims, complaints, appeals. The system automatically reads written communications from customers, classifies documents and feeds an application module for the management of practices by the Complaints Office.
Management of relations with investigating bodies
Moneying allows you to optimize interactions with investigating bodies, speeding up the production of responses for requests from judicial authorities, police forces and courts.
