Convenings

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Page: Actio Rules life-cycle
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Page: Arango Monitoring
Configuration Arango requires a scrape configuration be added to the prometheus.yml. (https://www.arangodb.com/2020/03/monitoring-arangodb-prometheus-grafana/ https://www.arangodb.com/2020/03/monitoring-arangodb-prometheus-grafana/) - job_name: arangodb s
Page: ArangoDB FullText Function Setup & Sample
Setup Analyzer 1. In Lens, connect to the Shell of the ArangoDB pod 2. Type "arangosh" in the shell and hit Enter - this will connect to ArangoSH 3. To connect to the correct DB, type "db.useDatabase("transactionHistory");" 4. Then import analyzers: var a
Page: Attacks on Pseudonymisation
The primary goal of pseudonymisation is to limit the linkability between a pseudonymised dataset and the holders of the pseudonyms and to thereby protect the identity of the data subjects. This type of protection is typically intended to counter the effor

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Page: Channel Aggregation and Decisioning Processor (CADProc)
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Page: Channel conceptual overview
Overview The Actio Financial Crime Risk Management Solution is designed to provide scalable and extensible financial crime risk monitoring and management functionality as a service to connected client systems. Channels can be implemented to allow for: Res
Page: Channel Router and Setup Processor (CRSP)
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Page: Complete example of a network map
{ "active": true, "cfg": "1.0.0", "messages": [ { "id": "004@1.0.0", "host": "NATS Server", "cfg": "1.0.0", "txTp": "pacs.002.001.12", "channels": [ { "id": "001@1.0.0", "host": "NATS Server", "cfg": "1.0.0", "typologies": [ { "id": "typology-processor@1.
Page: Complete example of a rule processor configuration
A “banded” rule configuration: { "id": "006@1.0.0", "cfg": "1.0.0", "desc": "Outgoing transfer similarity - amounts", "config": { "parameters": { "maxQueryLimit": 3, "tolerance": 0.1 }, "exitConditions": [ { "subRuleRef": ".x00", "outcome": false, "reason
Page: Complete example of a typology processor configuration
Building on the example rule configurations provided here: Complete example of a rule processor configuration Typology configuration for a typology with two rules { "desc": "Double-payment to a merchant.", "id": "typology-processor@1.0.0", "cfg": "001@1.0
Page: Conducting an EKUTA Proof of Concept
TL;DR Introduction A transaction monitoring system is a key component of a Proof of Concept - Objectives Deployment Integration Ingress Egress Operation Detection Effectiveness Data requirements Approach Metrics Calibration Feature validation
Page: Config-driven design
Page: Configuration management
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Page: Convenings
Page: Create New Channel
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Page: Create New Rule Processor
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Page: Create New Transaction
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Page: Create New Typology
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Page: Creating and Maintaining Processors
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Page: Data Preparation
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Page: DNS Monitoring
Configuration For DNS Monitoring we require a target to be configured on the Prometheus Config. - job_name: coredns scrape_interval: 5s metrics_path: /metrics static_configs: - targets: ['kube-dns.kube-system.svc:9153'] The default Metrics port is: 9153,

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Page: Entity Resolution Explained
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Page: Entity Resolution Implementation
Entity resolution Objective: To determine if the debtor (or creditor) in a transaction is the same person that had transacted previously, even if from a different account. Pre-requisites Account information from previous transactions have been independent
Page: Environment Monitoring
Introduction Scaling the FRMS Solution effectively means we will need to observe bottlenecks to scale effectively. Our monitoring Solution consists of Prometheus (https://prometheus.io/ https://prometheus.io/ ) for data collection and Grafana (https://gra

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Page: Feedback
com.atlassian.ecosystem2729962a-bde6-4430-b9d6-d6483b89a1dd/5e7a22e6-909d-46ae-9ab3-35d134dfd821/static/poll-maker27239f3d-07d7-4586-9545-874a91c83575ari:cloud:ecosystem::extension/2729962a-bde6-4430-b9d6-d6483b89a1dd/5e7a22e6-909d-46ae-9ab3-35d134dfd821/

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Page: Glossary
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Page: ISO20022 and Actio
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Page: Jordan - December 2022

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Page: NATS Monitoring
Introduction For our NATS monitoring we’re using the prometheus-nats exporter (https://github.com/nats-io/prometheus-nats-exporter https://github.com/nats-io/prometheus-nats-exporter ) Please note - on our NATS helm chart, this is automatically included w

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Page: Operating Scenarios Background
SCENARIO 1: Pseudonymisation for internal use Data are collected directly from the data subjects and pseudonymised by the data controller, for subsequent internal processing. Actio will not collect data directly from data subjects. SCENARIO 2: Processor i

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Page: PoCs
Page: Processor results propagation
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Page: Product Overview
What is Tazama Tazama is an Open Source solution built to support any Digital Financial Services Provider (DFSP) that requires Transaction Monitoring. Whether that DFSP is a small provider running one or 2 transactions per day or a national payment switch
Page: Pseudonymisation of customer data
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Page: Pseudonymisation Policies
Consider an identifier 𝐼𝑑 which appears several times in two datasets 𝐴 and 𝐵. After pseudonymisation, the identifier 𝐼𝑑 is substituted with respect to one of the following policies: Deterministic Pseudonymisation 𝐼𝑑 is universally replaced by the
Page: Pseudonymisation Techniques
Whichever technique is employed, pseudonymisation must be unambiguously reversible. Single-identifier Pseudonymisation Counter An identifier (the data that identifies a data subject) is substituted by a unique number chosen by a monotonic counter. First,

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Page: Rule Processor Overview
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Home page: Tazama Real-Time Transaction Monitoring
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Page: Test Data
Change log 2022/03/17: Updated post-NiFi test files to include changes made in and Transformations Each ISO 20022 transaction message that is ingested into Actio flows through the following processes/processors which each may introduce some transformation
Page: Transaction Aggregation and Decisioning Processor (TADProc)
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Page: Transaction Monitoring Service API
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Page: Typology Processing
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