Fraud Analyst – Banking (Application Fraud)

Juris Technologies; Kuala Lumpur; On-site; MYR 60,000 - 80,000; Full time

Job summary

A leading software solutions company in Kuala Lumpur is seeking a detail-oriented Fraud Analyst to combat application fraud in the lending sector. The successful candidate will develop fraud detection systems and require strong investigative skills and a Bachelor's degree in a related field. Ideal for someone with over 3 years of experience in fraud operations. The position offers a dynamic and innovative environment, perfect for professionals eager to contribute and grow.

Qualifications

• 3+ years’ experience in banking/fintech fraud operations, AML/financial crime.
• Practical knowledge of application fraud typologies.
• Experience designing test cases or scenarios.

Responsibilities

• Develop and maintain a fraud scenario library for lending.
• Design reproducible test artifacts for regression testing.
• Translate fraud scenarios into detection signals.

Skills

Attention to detail

Strong investigative skills

Analytical skills

Communication skills

Education

Bachelor's degree in finance, data analytics, forensic, or related field

Tools

Spreadsheets

Job description

• Join the fastest-growing lending and recovery software solutions company.
• Work with colleagues who understand how to build great software.
• Enjoy breathtaking recognition and rewards.

JurisTech is a leading innovator in the lending and recovery software industry, providing cutting-edge solutions to banks, financial institutions, and the telecommunications sector. Our mission is to revolutionise the way businesses manage credit through advanced technology and creative problem-solving. At JurisTech, we pride ourselves on our vibrant culture of innovation, collaboration, and continuous learning, making us a perfect fit for fresh graduates and professionals who are eager to grow and make an impact.

OVERVIEW

We are seeking a detail-oriented Fraud Analyst focused on application fraud in retail and commercial lending. This role will involve working with and assisting in developing and refining Artificial Intelligence systems to detect and prevent application fraud, making an immediate impact on our automated onboarding and decisioning platforms.

The role is responsible for identifying, designing, and validating fraud detection checks and escalation rules across the loan lifecycle — from loan document pre-screening to credit paper creation and decisioning. The candidate will work with product, data science and engineering teams to translate real-world fraud typologies into automated actionable detection signals and test artifacts.

RESPONSIBILITIES

• Develop and maintain a comprehensive fraud scenario library that covers application fraud typologies relevant to lending (income falsification, forged bank statements, synthetic identities, collusive schemes, identity manipulation, document tampering).
• Design reproducible test artifacts (anonymised sample documents, metadata-manipulated PDFs, synthetic identities) and use them in regression testing for automated fraud detection system.
• Translate scenarios into detection signals and business rules (metadata checks, cross-document consistency checks, statistical heuristics, social/OSINT indicators) and collaborate with engineers and data scientists to operationalise them.
• Support triage and investigation of flagged applications, define escalation criteria, and help calibrate alerts to balance risk vs customer friction.
• Provide subject-matter expertise to compliance, underwriting and product teams on emerging fraud trends and regulatory expectations.
• Produce clear written documentation: scenario playbooks, runbooks for investigations, test plans, and executive summaries for stakeholders.
• Measure and report on KPIs: detection coverage, false positive rate, false negative incidents etc.

JOB REQUIREMENTS

• Bachelor’s degree in finance, data analytics, forensic, information security, or a related field (or equivalent experience).
• 3+ years’ experience working in banking/fintech fraud operations, credit underwriting investigation, AML/financial crime or a related investigative role with exposure to lending application fraud.
• Practical knowledge of common application fraud typologies (income fabrication, forged documents, synthetic identity etc.).
• Experience designing test cases, scenarios or playbooks used by fraud operations or red teams.
• Strong investigative and analytical skills; comfort working directly with documents and metadata to identify tampering and inconsistencies.
• Excellent written and verbal communication skills with the ability to explain technical/operational issues to product, engineering and compliance partners.
• Comfortable working with spreadsheets and producing structured test datasets; ability to work with engineering teams to convert scenarios into automated tests (coding not required).
• Prompt Engineering — design prompts and test-cases to evaluate model behavior.
• GenAI risk awareness — understand common model failure modes (hallucination, overconfidence).
• [Preferred] Certifications such as ACAMS, CFE (Certified Fraud Examiner), or relevant forensic/document-examiner training.
• [Preferred] Experience with document forensic concepts: PDF/XMP/EXIF metadata, scanned vs native documents, digital signatures, hashing and checksum concepts.
• [Preferred] Prior exposure to machine-learning-based detection systems or experience collaborating with data science teams.

Interested applicants can send their resumes and transcripts directly to ***********@juristech.net.

Successful candidates will be required to work at Bangsar South area and may be required to travel as and whenever required.