3 Intro Decision Intelligence Approach Step 1: Fuse Data Step 2: Define How Information is Presented Step 3: Surface Suspicious Transactions Step 4: Prioritize Leads Step 5: Detect Suspicious Activities Step 6: Construct the Narrative Step 7: Map the Network About NEXYTE Investigation Challenges AML Investigation Challenges The traditional approach to combatting money laundering focuses on compliance. Financial institutions generally use rule-based tools to conduct Know Your Customer (KYC) and customer due diligence processes millions of Suspicious Transaction Reports (STRs) and Suspicious Activity Reports (SARs) and tend to produce many false positive alerts. This creates an information overload for the FIUs responsible for uncovering money laundering networks. The percentage of false positive alerts generated by traditional, rule-based AML/CFT tools is shockingly high, accounting for 90-95% of all suspicious transaction alerts 4 . Data Challenges + Massive amounts of data from SAR/STRs + Data siloed between multiple databases + Little time to investigate each lead + Noise generated from false positives Decision Challenges + Which STRs/SARs to focus on + Which companies or individuals to focus on + How to allocate and optimize investigation manpower and resources Decision Intelligence Platforms for AML Investigations Decision Intelligence platforms leverage technologies such as data fusion, machine learning and AI, in addition to collaboration and data visualization tools. These platforms enable organizations to automatically collect, fuse and analyze data from virtually any source, on a massive scale, in order to generate data-driven insights and decisions. This allows AML investigative teams to detect anomalies, identify patterns of suspicious activities, assess risks, and uncover new leads. Best-in-class Decision Intelligence platforms enhances data science with domain expertise, by allowing non-technical-domain experts to contribute their field- specific knowledge to the building of organization-specific analytical models. Fusion Data-driven actions Analytics