QuantaVerse boosts its Financial Crime Investigation Report

Thursday 10 September 2020 11:12 CET | News

QuantaVerse has boosted its Financial Crime Investigation Report (FCIR) so AML cases can be adjudicated more efficiently.

Among other critical information, the QuantaVerse FCIR presents investigators an at-a-glance analysis of transactional relationships, negative news, and money laundering typologies along with risk scores calculated by the QuantaVerse machine learning engine and narratives needed to clear a case or document a suspicious activity report (SAR) submission.

The QuantaVerse FCIR, which meets requirements for properly documenting, explaining, and detailing AML investigations, presents the findings  of the QuantaVerse Financial Crime Platform. The QuantaVerse platform has proven to automate approximately 80% of investigation work. By automating the searching, collating, and analysing of vast amounts of data and then summarising those findings in the FCIR, QuantaVerse allows investigators to apply their skills, experience, and time to adjudicating more cases.

Risk scores presented in the FCIR are derived by the QuantaVerse decision engine, a non-recurrent neural network that interprets observables (such as line of business, adverse media, jurisdiction, entity type, etc.) and makes accurate determinations on risks.

Narratives explaining what risks were found in the case are now joined by a new narrative section that explains what risks were able to be cleared. Each set of narratives include the rationale for those determinations which can be used when explaining why a case was cleared or to document a SAR. For investigators tasked with reviewing flagged TMS alerts, the FCIR narratives have helped reduce the average time spent investigating a case by as many as 40 minutes.

QuantaVerse offers customers two types of FCIRs. Its alert-based FCIRs examine cases that have been triggered by TMS alerts while entity-based FCIRs analyze and document the risk associated with each customer (and their counterparties) on a regular basis as prescribed by each financial institution.

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Keywords: QuantaVerse, financial crime, financial institutions, machine learning
Categories: Fraud & Financial Crime
Countries: World
This article is part of category

Fraud & Financial Crime

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