// 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

Benefits of an anti-fraud system

Data security:

  • Protection from unauthorized access to confidential information.

  • Prevent leaks and theft of customer data.

Early fraud detection:

  • Automatic detection of suspicious activity in real time.

  • Timely notification and blocking of suspicious transactions.

Efficiency and accuracy:

  • Utilizing machine learning algorithms for high accuracy in detecting fraudulent activity.

  • Reduce false positives by adapting to unique business characteristics.

Saved time and resources:

  • Automated fraud detection and prevention process.

  • Freeing employees from routine checks, allowing them to focus on more important tasks.

Antifraud system license price

License pricing is available upon customer request and depends on a variety of factors including:

System customizations:

  • The size and complexity of antifrod system customizations to meet business needs.

Support Level:

  • Various technical support packages with options including consulting, upgrades and staff training.

Volume of usage:

  • Price may depend on the volume of transactions and data processed by the system.

Customized Requirements:

  • Additional functional requirements or integrations specific to the client’s business processes.

An anti-fraud system that adapts to your business

This system is learnable and able to adapt to any business due to:

Flexible customization:

  • The ability to customize system settings to fit the unique characteristics of your business processes.

Machine Learning:

  • Utilizing machine learning algorithms to continuously improve the system and increase its efficiency.

Adaptation to change:

  • The ability of the system to respond quickly to new fraud techniques and changes in the business environment.

Custom Optimization:

The ability to provide additional training to the system to optimize it for specific business needs.