// DELIVERY, IMPLEMENTATION AND SUPPORT OF THE DIGITAL SOLUTIONS

Solving fraud issues and improving reliability of the financial institutions

Protection

Versus unscrupulous employees, customers, contractors and others.
Control

The operations online and offline.

Compliance

AML, CFT, KYC, anticorruption, automated compliance.
Up-to-Date

Analysis of the latest threats, development of new rules/scenarios.

The problem that we solve

+
billion tenge
Just a single resonant incident: “Hackers stole from the accounts of Kazakhstan’s banks” (profit.kz)
5%

of revenue lost by the companies due to fraudulent activities (ACFE, GFS)

Every third resident
Every third resident

has experienced the fraudsters who allegedly acted on behalf of a bank (KURSIVE, 2020)

%

Rise in fraud cases as of June 2022, according to the government services

Prevention

Analyze correlation of user behavior data on their devices during work through the various channels.

Cross-Channel
Verification

Cross-Channel<br>Verification

Response

Learn the machine to respond to millions of operations.

Machine
Learning

Machine<br> Learning

Analytics

Investigate a clients' behavior, their basic actions and abnormal deviations. Build a behavioral profile of the client.

Behavioral
Analysis

Behavioral <br>Analysis

Create your own risk assessment model and quickly adapt it to changing threats. Build the models to identify specific fraudulent scenarios. Implement a rule builder for any level of complexity.

Up-to-Date
Rule Builder

Up-to-Date <br>Rule Builder

Develop the rules based on the specifics of a particular unit’s work. Respond against abuse of office and the vulnerabilities in the systems.

Closing the Internal
Fraud Risk

Closing the Internal<br>Fraud Risk

Visualize the product results and analyze the effectiveness of report for the fraud monitoring team.

Reporting

Reporting

Data required for analysis

Scheme of the Antifraud cross-channel monitoring system

// SYM BUSINESS PLAN

Protection of Clients’ Funds from Fraudulent Activities

01
Analysis

Collect and analyze identified and potential events to consider the possibility of risk reduction. Implement automated control in the Antifraud system for high-risk products.

02
Automation

Implement the scenarios and rules to detect suspicious activity. Check the effectiveness of the configured rules by analyzing the processed incidents, then optimize the rules in the Antifraud system.

03
Outcome

Data enrichment for the Antifraud system from the information systems. Machine learning launch. The organization continuously monitors, detects events, responds, and optimizes controls.

SCHEDULE