Smart regulatory apps for financial institutions
HOW IT WORKS
Search, collect and structure data
Build context and connect the dots
Provide insights and recommendations
Whether it's legacy systems (core banking, CRM, trading) or external sources (web, API, documents), we collect, clean and restructure data to provide consistent datasets
Our smart engine transform and reconnect data to provide context: a unified client 360° view to break the silos barriers when addressing regulatory problems
Leveraging AI models, NLP extractors or rule inference engines, we detect issues and provide real-time risk assessment on client-focused regulations such as AML-CFT, FATCA, AEoI-CRS, MIFID, IDD, ABC
Financial institutions are facing an unprecedented acceleration and overlay in regulatory obligations. Today, it significantly impacts the cost structure of their business model, their operational efficiency and their client relationship.
Our business consultants possess extensive knowledge on numerous regulations such as AML-CFT, FATCA, AEoI-CRS, MIFID, IDD, ABC.
Our R&D and AI lab founded in 2017 is building a platform that automates compliance processes with a full digitization experience.
Our mission: offer modern tech solutions to tackle the challenges brought by these regulations with more relevance and agility.
We provide a comprehensive solution that was designed to solve regulatory compliance problems with more efficiency while minimizing friction with clients.
Our vision: become an AML regtech pure player that leverages the latest technologies to handle fast-evolving regulatory challenges while enabling financial institutions to service efficiently their customers.
Modern solutions leveraging latest AI and machine learning technologies are essential to fight financial crime and money laundering. They leverage efficiently the greatest asset banks possess - their data - and can offer solutions that can evolve as fast as regulation and criminal scheme.
Our platform offers components which:
Were designed using modern technologies (big data architecture, NLP, AI, graph)
Use natively all internal/external data whether they are structured or non structured
Overcome the paradigm based on pre-defined rules and workflow
Detect non-compliant elements and discrepancies not visible by a human operator
Reduce false-positive and generates relevant alerts
Conciliate regulatory requirements and business objectives