In 2016, financial institutions (FIs) filed 2 million SARs (suspicious activity reports) with FinCEN. During 2008—2018, ~90% of US government enforcement actions involved $27B in penalties.
Out of ~ 21B ACH transactions worth $46.8T in 2017, ~$1.4B were fraudulent. Financial institutions use business rules to out-sort fraudulent transactions with high false-positive rate due to constant changes in fraudster schemes.
Conflict of Interest occurs in investment banks & law firms because
Library of 25+ proprietary supervised & unsupervised algorithms, pre-trained & tested for our products
30+ probabilistic spatial & temporal graph algorithms to determine links & connected entities
Prebuilt financial ontologies & business rules that each product will improve over time
60+ algorithms for cleansing, harmonizing & validating data from internal & external sources in 30+ formats, e.g., JPEG, video, PDFs
40+ scrapers & connectors for ingesting web & paid data subscriptions, e.g., news, social media, traffic, geo-location, sanction lists
In-built reinforcement learning algorithms that improves our products’ performance over time “with & without a human loop”
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ workflows
Highly scalable with parallel & distributed computing with options to deploy on-premise or consume as SaaS
Incorporates clients’ strategies & business rules to improve compliance & accuracy
91% – 98% accuracy that improves over time & with high quality ontology
60% – 85% improvement in time & cost over the current manual process
Incorporates 500+ signal-features & reduce noisy-features to reduce false positives & produce alerts in real-time