The Financial Crime Due Diligence (EDD) process, along with other processes handled by the Financial Crime Operations team, are typically human-intensive manual tasks. An analyst performing the due diligence conducts assessment of the gathered content around the suspect, and prepares a due diligence document.
The process involves task allocation and monitoring, by fetching search reports from multiple websites. These include LexisNexis, World Check, XDC, KYC360, Google, and many more, depending on the bank’s process to analyze the content and eventually draft the EDD report. Steps involve manual activities of getting the content from these websites, reading through the documents, extracting relevant sections/content about the suspect around the Financial Crime categories, and creating the EDD report. This is a largely manual activity, making it less scalable, and subject to scoring, based on the analyst performing the activity.
With a powerful combination of NLP & Machine Learning techniques, LTI helps you intelligently automate the EDD process and consolidate knowledge via learning for consistent scoring. The solution for Intelligent Automation of Financial Crime EDD helps banks deliver by automating data extraction and reporting across a range of internal and external data sources, with a combination of NLP and ML techniques. The solution deploys AI Bots to automate the task of fetching reports from the search sites. The AI Bot extracts relevant content by looking for adverse/negative news content, or sanction issues by agencies around the world, judgments and property interests, etc. It then compiles an EDD report, specifying the risk classification, along with the supporting documentary evidence.
Leverage pre-built dictionaries & vocabularies of the bank for sanction screening.
Ready components for extracting content, which can be customized.
Customizable and can be integrated into the existing landscape of an Enterprise.
Automated maker process, while retaining the human-checker process.
Reduction in Turnaround Time from ~4hrs to ~30min per customer case.
35-45% improvement in analyst time. The team of analysts can manage higher workload.
Consistency in the risk assessment process on account of relying on the system determined scores.
Insight into process KPIs enable better management.