Designed to help financial institutions detect and eliminate financial crime, the SaaS solution aims to deepen client risk assessments by leveraging intelligent entity behaviour modelling. Furthermore, it helps deliver increasingly accurate detection of criminal transactions in real-time, thus increasing compliance team efficiency and reducing costs.
Sentinels aims to help banks, wallets, payment service providers and other financial institutions stay ahead of anti-money laundering (AML) threats in a market that is known for rising transaction volumes, spiralling compliance costs, and constantly tightening regulations. As detailed in the announcement, users leveraging the company’s solutions have reduced their time spent on case management by up to 55% and their ‘red herring’ false positive transaction alerts by 25%, which are known to divert the time and energy of compliance officers, while simultaneously increasing the chances for genuine illegal activities to slip through undetected.
The company has transitioned to a scalable, high-performance AWS cloud-based delivery model where customers can connect into the SaaS platform by leveraging secure, standardised APIs. Due to this, Sentinels is enabled to maintain a high pace of product innovation and development and to rollout continuous improvements without having client operations disrupted. Furthermore, the dynamically scalable computing capacity enabled by AWS gives users the option to create and run powerful, data-heavy business rules in real-time, with accuracy that is consistent, which allows them to detect and react to potential suspicious and criminal activity in an instant manner.
Sentinels’ representatives advised that one of the main challenges that compliance teams face is their limited capacity to identify, monitor, and manage key sources of risk. The company’s SaaS platform aims to extend this capacity and enable them to create and test tailor-made business rules without causing interruptions to the platform’s real-time detection engine. Additionally, it opens the door to AI and machine learning algorithms, which are thought to further reduce risk by analysing patterns and suggesting improvements.
As it provides immediate analysis of transaction processing flows, Sentinels’ real-time detection capability is believed to help customers tackle more areas of financial risk, enabling them to proactively block suspicious transactions before further risks are created. Furthermore, the scalability of the SaaS architecture enables clients to increase their transaction volumes with no impediment from the technologies they use to monitor, manage, and mitigate risk.
Maria Adele Di Comite, Research Director at IDC Financial Insights Corporate and Retail Banking commented on the state of the market and advised that banks are in a ‘privileged position’ to contribute to the combatting of financial crime. As such, regulators require support from the banking community and impose huge fines on organisations that are not compliant with requirements to combat financial crime. Banks should both contribute towards the detection and combatting of financial crime and meet customers’ expectations for a seamless customer experience. Thus, to detect possible criminal transactions in an efficient manner, there’s a need to deploy quick and smooth detection tools and processes.
As advised by the IDC official in Sentinels press release, the above mentioned is the underlying reason that led 33% of Europe-based banks to plan additional investments in AI and ML in 2022, having implemented effective automated screening processes, minimised customer experience friction, and enhanced operational efficiency by reducing false positives. Furthermore, throughout 2023, the relevance of AI and ML alongside data and analytics investments is expected to grow to address the constantly increasing concerns regarding security, risk, and compliance.
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