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Millions of financial transactions take place around the world a day which makes Transaction Monitoring even significant for financial institutions to combat financial crimes.

As to enhance AML system environment and configuration, Our Transaction Monitoring module contains a complete set of detection rule library for regulatory requirement for different industries, e.g. banking, insurance, securities, etc. The rules are flexible to extend for enhancement or customization.

For data management, our compliance intelligence database can store and use for:

  • AML transaction monitoring

  • Fraud monitoring

  • CDD / KYC data

  • Detection or monitoring logic

  • Pattern and behaviour analysis

  • Alert information

  • Investigation operation

  • Historical data

  • Audit trail

Key Benefits:

  • Consolidate all the fraud-AML related activities in one system, which is a revolutionary concept in the industry

  • Customer holistic view of both fraud and AML information for transaction monitoring and investigation

  • Extend to include the AI capability for alert scoring to reduce false-positive alerts, which is one of the HKMA RegTech guidelines for the banking industry

Transaction Monitoring


This is the smart banking era, data analytics and machine learning are broadly used to complement banks' processes. By applying RegTech solutions, such as artificial intelligence and machine learning, suspicious behaviours and patterns can be easily detected and recognized.

Once the alerts generated through existing AML Transaction Monitoring system, daily alerts and related information will be collected. Through our AI platform with alert scoring engine which learns investigator's behaviours and decisions, it helps scoring each alerts and reviewing all available alerts. Each alert score is explainable and daily alerts will be either classified, hibernated, or closed.

Key Benefits:​

  • Reduce false-positive rates

  • Free up resources to focus on investigating high-risk cases

  • Enhance the overall effectiveness and efficiency of the transaction monitoring process

AI for Transaction Monitoring


While conducting the institutional money laundering risk assessment, several factors should be covered by AI according to regulators' guidelines, and which come up to a Customer Risk Score:

  • Customer risk factors - e.g. industry, occupation, legal entity status, etc.

  • Country risk factors - e.g. country of incorporation and country of residence, etc.

  • Product / Service risk factors - e.g. deposit, credit cards, loans, etc.

  • Delivery / Distribution channel risk factors - e.g. postal, internet, e-mail, etc.

  • Other risk factors - e.g. STR counts, audit, company specific, etc.

With our KYC / CDD module, the workflow is configurable to control the operation, such as maker-checker review process. All review results and records associate with the customer profiles which help notify different parties to follow up or for further review planning purpose.

In addition, as the data sources are from different internal and external systems. The solution provides customer holistic view which collects all the customer-related data to comply with regulatory requirements even effectively. The results generated can then be consolidated for additional activities and operations.

Key Benefits:

  • Configurable risk rules

  • Customer holistic view

  • Able to integrate with internal systems (API / batch)

  • Audit trail

Network Analytics.png


HKMA stated that Network Analytics helps exploring how data and information about corporate shareholding and banks' exposures may potentially be brought to life as network diagrams, so that the relationships between different entities become apparent.


Our Network Analytics for AML module deploys advanced analytics and RegTech technology to existing data which provides great transparency to trace and identify customer's network even more effectively and efficiently.

Additionally, our compliance intelligence database allows to extend for additional data and relationship, also the pre-define compliance data mart is able to store:

  • AML Data - e.g. customers, accounts, transactions, TM alerts, customer risk, etc.

  • Fraud Data - e.g. IP address, devices, OS, etc.

  • Graph Information - e.g. nodes, edges, etc.

Key Benefits:

  • Easy to read

  • Handy to explore the relationship and information

  • Flexible to expand on data capture and configure for different data types

  • Pre-defined network analytics database structure

  • Allow to adjust the data properties of the network graph

  • Easy to interface and integrate with existing AML system

  • Able to support alert investigation of transaction monitoring

  • Support pro-active detection mechanism

  • Integrate with customer holistic view

  • Strengthen AML capacity

  • Reduce AML and operational risk which fulfil HKMA's requirement

Name Screening
Network Analytics
Name Screening.png


As per the guidelines from regulators, financial institutions should put effective screening procedures in place to identify whether their customer is a Politically Exposed Person (PEP), terrorist or sanction designation, and such procedures should be reviewed periodically.

By embedding AI and statistical models with carefully curated and tested algorithms, our Name Screening module is able to perform screening accurately.

In order to narrow down the potential matching names, filtering can also be enabled and there are multiple mechanisms and screening modes as required by the regulators to perform effective and accurate screening:

Name Matching Mechanisms:

  • Exact match

  • Fuzzy match

  • Partial match

  • Reverse ordering match

  • Abbreviated forms


Screening Modes:

  • Real time screening

  • Batch screening

  • Regular full screening

Eventually, there will be a score assigned to the screening result for the matched input name. Institutions can adjust the scoring threshold and decide whether to accept or reject the customer based on their risk appetite. The name screening engine can be accessed by different internal systems through API which provides a centralized onboarding service with consistent results to financial institutions.

Key Benefits:

  • Reduce false-positive alerts with advanced machine learning and natural language processing technology

  • Reduce the need for performing name screening manually, instead deploying those resources to more valuable efforts

  • Screen multiple lists by using a single solution
    i. Internal - e.g. white list, black list, bankruptcy list, etc.
    ii. External - e.g. WorldCheck, Factiva, OFAC, etc.

  • Include enterprise functions and features to eliminate unnecessary reviews and duplicative tasks



Further to our Transaction Monitoring module, in order to track where money goes, and more other details, compliance bot is applied.

When data sources like accounts, customers, transactions, etc. are validated and consolidated, single view of customer with risk appetite will be generated, together with entity resolution, entity network and fund flow, alert scoring through AI engine and news analytics. Other than that, compliance bot also helps providing investigation recommendation and reducing false-positives.

Key Benefits:

  • Customer holistic view

  • Reduce false-positives

Compliance Bot


To safeguard financial institutions from the risk of being involved with terrorist financing and money laundering crimes, our high quality of STRs can definitely help.

Our ESTR module workflow is configurable.

  1. Database source synchronizes with AML database automatically

  2. The ESTR solution interfaces the AML alerts information to eSTR system, including customers, accounts and transactions

  3. Compliance team will be able to review, complete and approve the STR contents

  4. STRs can also be generated for filing and send back the result to AML system

Key Benefits:

  • Automation and integration

  • Bank-wise suspicious report management

  • Workflow

  • Standard JFIU output

  • Audit and record keeping

  • Multiple STRs generated for periodic status reviewing and due diligence enhancement purpose:
    i. eSTR status report
    ii. eSTR result report
    iii. eSTR entity list report
    iv. eSTR performance report

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