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Lazo ILIJOSKI ASEBA AML Anti-Money Laundering Solution.

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Presentation on theme: "Lazo ILIJOSKI ASEBA AML Anti-Money Laundering Solution."— Presentation transcript:

1 Lazo ILIJOSKI ASEBA AML Anti-Money Laundering Solution

2 Agenda Necessity of AML solution & Trends in AML Major functional features System Architecture Overview of system modules Business process for analysis of clients and their transactions Case studies The benefits of the ASEBA AML system Why ASEBA AML?

3 Necessity of AML solution & Trends in AML Global trends State regulations Reputation risk 3 Solution Reputational risk State regulations International standards

4 ASEBA AML - ASEBA AML - Major functional features Integrated End-To-End solution for Money Laundering Detection and Prevention Independent solution from the core banking system Risk profiling of clients and transactions Initial setup with more then 90 indicators for risk detection No limit of rules & indicators for risk determination Creation of new indicators and scenarios without vendor assistance Graphical interpretation of comparison of analytical data Sanctions list management Delivering accurate, prioritized alerts directly to desktop application in real time Generating specific reports imposed by local regulatory authorities and reports based on defined suspicious activity criteria Integration with external systems by using web service layer Integrated document management tool Audit Trail KYC Effect 4

5 Modules of the AML System Data Transfer Module Sanction Lists Management Tool Black list, white lists, custom sanction lists, on-line identification and control of transactions Module for on-line authorization and identification Risk Scoring Engine: Clients & Transactions risk profiling module; Management of Peer Groups; Sub-module for creating custom indicators; Sub-module for custom scenarios; Sub-module for analyzing transactions relationships; Ticketing System Report & File Generator Document Management Module - Exchange-Archive-Search Module for generated files and reports 5

6 Logical Architecture 6

7 System Architecture 7

8 Enterprise Architecture 8

9 Control against blacklists Executor details Behalf of transaction Performing Transactions Controlling mandatory fields and data validation Gathering single transactions even they have passed through several steps within their life-cycle Data Transfer Transactions Grouping Re-creating groups of previously transferred transactions Analysis of relations of transactions Risk Scoring of Clients and Transactions Re-scoring of regrouped transactions Automatically creating tickets (cases) for entities with high risk Risk Scoring Review of scoring results Result comparison Manually creating tickets for suspicious entities Analysis Mark as suspicious/non-suspicious Submission of report to FIU (OPMLFT) Storing into risk lists of clients Final action 9 Business process for analysis of clients and their transactions Business process for analysis of clients and their transactions

10 Data Transfer Module Categories of data that is transferred from Core banking system to AML System Clients Individuals legal Accounts Transactions Related persons Every type with weight factor Reverse relationship Level of relation Collaterals Quality of data most important for analyses Mail notifications 10

11 Scoring Engine Designed to calculate risk factor for transactions and clients Possibility for performing scoring by various risk schemas Flexible for adding new indicators and rules or adjusting existing ones; Creating new indicators by using a wizard; Determination of risk factor based on more than 90 different rules and indicators Possibility for mass risk-rating of all clients Possibility for risk-rating of single client on demand Interactive view and comparison of results of performed scorings Ability to detect a broad range of money laundering scenarios Decreasing number of detected false-risk cases by tuning weight factor for each of the indicators Ability to perform testing and calibration of the schema by Training Application Ability to integrate with external systems through web service layer 11

12 FUNCTIONALITIES Daily scoring More than 40 rules & indicators Easy parameterization Automatically creation of tickets Influence of risk factor to clients Risk factor of transaction 12 Risk factor of transaction Amount Payment basis Part of a group Statistical deviation Dormant or new account Client in a sanction list Country risk... INDICATORS

13 Analysis of transactions relationships and creating groups of related transactions 13

14 Review of scoring results of transactions1/2 14

15 15 Review of scoring results of transactions2/2

16 FUNCTIONALITIES Risk profiling of clients Scoring on predefined period More than 40 rules & indicators Easy parameterization Deviation of client Graphical view of customers Automatically creation of tickets Risk factor of clients 16 Risk factor of clients Origin Cash transaction Freq. specific transaction s Risk factor of transaction Risk Of products Activity of entity Related persons Sanction Lists... INDICATORS

17 17 Design of scoring schemas (Smart Modeler)

18 Review of scoring results1/3 18

19 Review of scoring results2/3 19

20 Review of scoring results3/3 20

21 Graphical review of scoring results1/3 21

22 Graphical review of scoring results2/3 22

23 Graphical review of scoring results3/3 23

24 Ticketing System Built-in functionalities for opening, assigning and reviewing different types of tickets Assigning many and various actions that should be taken until ticket is not closed Possibility for creating new custom actions by system administrators Automatically creating tickets for entities which score is higher than the threshold set by the Bank Attaching of related documents to the ticket and browsing through their content Generating report with conclusion about the performed analysis Tracking case history Mail notifications for new ticket assignment and reminding for due date 24

25 25

26 Tickets Review 26

27 Customer Lists Management System1/2 Management of blacklists, internal and white sanction lists Import of EU, UN & OFAC lists No extra costs for defining and loading new types of blacklists No limit of number of lists Searching under various criteria: Parts of name, Similar aliases, Similar names or address, Different character sets, Transpositions, Common language differences, Common errors in writings. 27

28 Customer Lists Management System2/2 Customer screening – under several methods based on Fuzzy Logic: Trigram Like Levenshtein SoundEX Metaphone Chapman Length Deviation… Show results above minimum matching percent specification Proposed actions based on searching results Possibility for cross-checks of all customers against blacklists Possibility for defining different type of alerts for different sanction lists 28 Transaction screening if there is no possibility for tight integration of external system to AML system All functionalities can be used by external legacy systems by sending HTTP Requests or invoking web services

29 Module for on-line authorization and identification On-line control of transactions Online identification of client against sanction online lists Monitoring of SWIFT messages against blacklists: Scanning of all international payments against blacklists, PEP and other sanctions lists Proposing action according to percent matching Risk of transaction 29

30 On-line identification and control of transactions 30

31 31 Report & File Generator Full coverage of all legal requirements defined for reporting in several countries CTR report- cash transactions above limit, related cash transactions above limit Loans in period Borrows in period Additional data for client STR report Automatically archiving in document management system Flexible definition of new file/report requirements - Report and file generator Allows generation of various custom reports by technical personnel of the Bank Allows for presentation of reports in different formats: XML files Tabular overview Excel reports HTML reports

32 Document Management Tool Key features: Automatic sending of files Archiving of sent and received files – electronic archive Ability to sign documents before sending them Simple and quick access to exchanged documents Logging of individual activities Fast and reliable search engine of data Integrated with ticketing system Relations between documents 32

33 Preview of archived files 33

34 Module for creating custom indicators and scenarios Designing, creating and testing custom indicators by using a wizard No need assistance from technical person Possibility to use two types of operators: Comparative (=, >, >=,, LIKE); Aggregate (Sum (absol. values), Sum (+/-), MAX, MIN, Count). Retrospective analysis of custom indicators Tightly integrated to designing tool for scoring schemas (Smart Modeler) Enhanced monitoring based on custom scenarios No limit on number for adding new scenarios 34

35 Editor for creating custom indicators 35

36 Technology Framework Windows Server family 2003/2008 OS SQL Server 2005/2008 SQL Server Integration Services Internet Information Services.Net Framework 3.5 SP1 36

37 Case Studies Ohridska Banka AD Ohrid (Societe Generale Group) Core Banking System: PUB 2000; Database: SQL Server 2005 AML System database: SQL Server 2005; OS: Win Srv 2k8 TTK Banka AD Skopje Core Banking System: PUB 2000; Database: SQL Server 2008 AML System database : SQL Server 2008; OS: Win Srv 2k8; Virtual Environment Stopanska Banka AD Bitola Core Banking System: PUB 2000; Database: SQL Server 2005 AML System database : SQL Server 2008; OS: Win Srv 2k8 Centralna Kooperativna Banka AD Skopje Core Banking System: BIIS (DataMax); Database: Oracle 10g AML System database : SQL Server 2005; OS: Win Srv 2k3 Univerzal Banka AD Beograd Core Banking System: PUB 2000; Database: SQL Server 2005 AML System database : SQL Server 2008; OS: Win Srv 2k8 ; Virtual Environment Investiciono-Komercijalna Banka DD Zenica Core Banking System: PUB 2000; Database: SQL Server 2005 AML System database: SQL Server 2005; OS: Win Srv 2k3 There are two more ongoing implementations 37

38 The benefits of the ASEBA AML system Effectively assisting banks to comply with AML regulations in different countries and international standards Possibility for upgrade and implementation of changes in business rules without vendors assistance Risk profiling of customers in any time Prediction of customers behavior and achieving KYC (Know Your Customer) effect by using comprehensive user interface Historical data for customers risk deviation Keeping records for risk cases and those that are reported to Finance Intelligence Unit and appropriate treatment of the most risky customers On-line monitoring of transactions and preventing illicit activities Customer screening against sanction lists Protection of cooperation with entities that are on blacklists 38

39 Why ASEBA AML? Fully compliant with legislative requirements Generation of report according to OPMLFT specifications Proper transaction data interpretation Turnkey solution Minimized necessity of technical personnel for configuring AML system; Solution is easy expandable and can be easily integrated to external systems; Future customization of the system without vendor assistance: Creation of new and calibration of existing scoring schemas; Creation of new scoring rules and indicators (even without help from IT staff); Creation and customization of scenarios; Creation of new customer lists; Creation of new rules for transactions grouping. Integrated environment Compatible authorization management Possibility for single sign-on system Integration with external Audit system 39

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