Job description:
Paymentology processes tens of millions of transactions in over 40 countries around the world. As an award-winning global Fintech company, we provide enterprise-level, scalable and highly secure financial processing systems making it easy for people to issue, redeem and reconcile Mastercard and Visa cards all over the world.
Paymentology processes tens of millions of transactions in over 40 countries around the world. As an award-winning global Fintech company, we provide enterprise-level, scalable and highly secure financial processing systems making it easy for people to issue, redeem and reconcile Mastercard and Visa cards all over the world.
We are seeking a Fraud and Risk Analyst in the LatAm region to augment our fraud monitoring operations across our organizations. Joining one of the most exciting issuer-side processors in the payment space, you will get to work in a complex cloud-first organization on a global scale.
What you get to do:
As Fraud and Risk Analyst in Paymentology, you will be joining a globally distributed company and will work with colleagues dotted across the globe.
What you get to do:
As Fraud and Risk Analyst in Paymentology, you will be joining a globally distributed company and will work with colleagues dotted across the globe.
Your colleagues are passionate about our products and customer-experience and you will work closely with them and our clients globally as an ambassador and driver of our fraud and risk initiatives.
- Monitor real time queues and identify high risk transactions within the business portfolio.
- Observe customer transactions to identify fraudulent activity such as BIN attacks, friendly fraud, and similar other risks.
- Analyse and triage detected fraudulent transactions. Recommend and implement mitigation action.
- Resolve queued transactions within the service level agreements to reduce potential revenue losses.
- Interact with customers to validate information and to confirm or cancel authorizations.
- Resolve customer issues within the scope of existing service level agreements.
- Monitor constantly customer and transactional records to identify unauthorized transactions and fraudulent accounts.
- Maintain fraud analysis models to improve efficiency and effectiveness of company systems.
- Determine existing fraud trends by analysing accounts and transaction patterns.
- Identify system improvements to prevent fraudulent activities.
- Recommend anti-fraud processes for changing transaction patterns and trends.
- Recommend new software tools used for fraud detection, prevention and reporting activities.
- Generate suspicious activity reports and risk management reports.
What it takes to succeed:
- Experience with Fraud pattern detection analysis
- An understanding of regional fraud trends relating to transaction monitoring
- Proficiency in using key data analytics and visualisation applications e.g. Metabase, PowerBI, Tableau, and Excel to produce reporting.
- An understanding of card operations, authorization, settlement, clearing, tokenization, issuing, ISO 8583
- Knowledge of Mastercard, Visa and UnionPay Fraud Regulating Policies and Solutions.
- Ability to write and present reports demonstrating strategic thinking
Ideally you will have these experience competencies;
- At least 3 years of working experience in a similar role related to the fraud and risk domain.
- A relevant University degree/technical certification, or relevant experience commensurate to the role (Data Science, Business Intelligence, Forensics, Information Technology etc)
- CFE, CFRM or other relevant professional fraud certifications
What you can look forward to:
At Paymentology we value making a difference to the lives of the people who work for us and who live in the communities where we operate. As values are important to us, you can look forward to working alongside fellow Paymentologists, who share these values. You’ll be part of a team that is passionate about making a difference on a global scale. We focus on building strong, diverse teams built from different backgrounds, experiences &identities.
Data source
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