Fraud Monitoring

RecruiterPal; Indonesia; Vor Ort; IDR 60.000.000 - 120.000.000; Vollzeit

Zusammenfassung

ALTO Network seeks a Fraud Analyst to protect payment ecosystems in Indonesia. You will monitor transactions in real time, analyze data, and detect patterns that indicate fraud, using dedicated fraud detection tools and dashboards.

Ideal candidates hold a CFA, a bachelor’s degree in a related field, at least 1 year of fraud analytics experience, and are comfortable with 24/7 rotating shifts; you will support investigations and regulatory reporting as needed.

Qualifikationen

• Bachelor's degree in a related field.
• Minimum 1 year of experience as a fraud analyst.
• Certified Fraud Analyst (CFA).
• Willing to work shifting (24/7).

Aufgaben

• Ensure real-time detection (24/7) and prevention of suspicious transaction activities or fraud to protect payment systems, customers, and the company's reputation.
• Assist in monitoring transactions, analyzing data, and identifying patterns or anomalies that may indicate fraudulent activity.
• Use fraud detection tools and techniques to flag suspicious transactions or behavior.
• Conduct basic data analysis to review transactional data, customer profiles, and financial records for potential fraud indicators
• Support fraud investigations by gathering evidence, conducting research, and assisting in interviews with suspects or witnesses
• Detecting Transaction Anomalies in Real-Time (24/7)
• Follow investigative procedures and protocols under the guidance of senior analysts.
• Preventing Financial & Operational Losses
• Assist in ensuring compliance with anti-fraud regulations, industry standards, and internal policies.
• Help in preparing regulatory reports and documentation as needed

Kenntnisse

Analytical thinking

Communication

Teamwork

Problem-Solving

Time management

Adaptability

Ausbildung

Bachelor's degree in Criminology, Data Analysis, Computer Science, IT, Cybersecurity, Finance or related field

Tools

Fraud Detection System

Excel

Dashboard Monitoring

Splunk

Big data technologies

Data analytics

Machine learning

Jobbeschreibung

COMPANY DESCRIPTION

ALTO Network is a leading payment infrastructure provider as well as the pioneer in payment solution by always bringing the most innovative and impactful technology to connect merchants or financial institutions with their customers to grow their businesses nationwide and beyond.

RESPONSIBILITIES

• Ensure real-time detection (24/7) and prevention of suspicious transaction activities or fraud to protect payment systems, customers, and the company's reputation.
• Assist in monitoring transactions, analyzing data, and identifying patterns or anomalies that may indicate fraudulent activity.
• Use fraud detection tools and techniques to flag suspicious transactions or behavior.
• Conduct basic data analysis to review transactional data, customer profiles, and financial records for potential fraud indicators
• Support fraud investigations by gathering evidence, conducting research, and assisting in interviews with suspects or witnesses
• Detecting Transaction Anomalies in Real-Time (24/7)
• Follow investigative procedures and protocols under the guidance of senior analysts.
• Preventing Financial & Operational Losses
• Assist in ensuring compliance with anti-fraud regulations, industry standards, and internal policies.
• Help in preparing regulatory reports and documentation as needed

QUALIFICATIONS

• A bachelor's degree in Criminology, Data Analyst, Computer Science, Information Technology, Cybersecurity, Accounting, Finance, or a related field is often required
• At least 1 years of experience in fraud Analyst
• Certified Fraud Analyst (CFA)
• Willing to work Shifting (24/7)

Knowledge

• AML and KYC Regulations
• Fraud reporting requirement
• Transaction data analysis
• Ticketing/log system for recording alerts and incidents.
• Data visualization
• Familiar with Fraud Detection System and Dashboard Monitoring

Technical

• Data tools : such as Fraud Detection System, Excel, Dashboard Monitoring or similar tools.
• Splunk
• Data analytics
• Machine learning
• Big data technologies

Non Technical

• Problem-Solving
• Adaptability
• Time Management Skills
• Analytical thinking
• Communication
• Teamwork