Fraud Analytics Associate

Overview

Hyundai Capital America (HCA) helps people move forward. Through Hyundai Motor Finance, Genesis Finance, and Kia Finance, we deliver innovative financing, leasing, and insurance solutions to more than 3 million customers and businesses nationwide.

We’re a company driven by growth, innovation, and people. At HCA, you’ll find opportunities to build new skills, expand your career, and make a real impact—while working in a diverse, inclusive, and values‑driven environment. We’re proud to support our communities through volunteerism, philanthropy, and engaged Employee Resource Groups.

If you’re looking for a fast‑paced, collaborative workplace where your ideas matter, join us as we lead the future of financing freedom of movement. Apply today.

The Fraud Analytics Associate supports fraud monitoring, reporting, and analytics activities that help identify and mitigate fraud risk. This role uses established data analytics tools and processes to analyze fraud trends, consumer behavior, underwriting activity, score performance, and potential risk indicators. This role maintains recurring reports and dashboards, performs routine and ad hoc analyses, and summarizes findings for fraud leadership and cross‑functional partners.

In addition, this role may support manual review activities by analyzing applications or accounts for irregularities or potential fraud indicators.

Fraud Analytics, Metrics, and Reporting Support

Support development and maintenance of fraud analytics used to track fraud exposure, fraud trends, and score performance.

Perform data validation and variance analysis to help identify changes or anomalies in fraud trends.

Support development and upkeep of fraud‑specific data tables used for monitoring, reporting, and analysis.

Maintain and refresh fraud monitoring reports and Tableau dashboards, to ensure data accuracy and consistency.

Perform routine quality checks on fraud analytics outputs and escalate data issues or anomalies.

Assist with updates or enhancements to existing fraud analysis tools to improve usability and efficiency.

Conduct ad hoc analyses to support identification of fraud trends or potential risk indicators by dealer, geography, product, or fraud typology.

Assist in analyzing fraud score performance and vendor outputs to support review of fraud trends, rule performance, and potential risk indicators.

Summarize findings clearly and concisely for analytics managers and fraud operations teams.

Support evaluation of fraud prevention tools and data provided by Credit Reporting Agencies and external vendors.

Assist with data analysis and benchmarking of fraud tools, score enhancements, or vendor outputs.

Help prepare supporting analytics, summaries, and exhibits used to evaluate fraud tools, score enhancements, or vendor services.

Work with fraud, credit underwriting, origination risk, and portfolio risk teams to provide analytical support for fraud prevention initiatives.

Assist with data pulls, analysis, and documentation used in cross‑functional fraud reviews and initiatives.

• Support continuous improvement efforts by identifying data gaps, reporting enhancements, and process efficiencies.

Minimum 2–4 years of related experience in fraud analytics, risk analytics, credit risk, reporting, data analysis, or financial services operations support.

Experience using data to support fraud monitoring, trend analysis, reporting, dashboards, or operational risk reviews preferred.

Working knowledge of credit, underwriting, fraud prevention, collections, or financial services processes preferred.

Auto finance Industry a plus

Bachelor’s degree or equivalent work experience required.

Strong analytical skills with the ability to support fraud monitoring, reporting, and trend analysis using established tools and processes.

Working knowledge of SQL, Excel, and relational databases to query, validate, and analyze datasets.

Familiarity with SAS, Tableau, or similar analytics and reporting tools used to support fraud reporting, dashboard maintenance, and data analysis.

Foun…