Payment Fraud Data Analyst

September 30, 2024

Hewlett Packard

Heredia

Business environment:
HP Inc. is a fortune 100 company, the market leader in commercial personal systems and printing, driving innovation that empowers people to create, interact, and inspire like never before.
HP Payment Fraud is a global resource shared by all parts of our business to help them become better managed and control payment risk. We are a valued advisor and business partner while influencing and ensuring fiduciary control and delivering payment risk management excellence within HP Legal’s Brand Security division.
Position Summary:
The HP Payment Fraud Data Analyst will assist with HP Fraud Prevention directives to include the risk model, analytics, internal systems, external solutions, and reporting. HP Payment Fraud is a global resource shared by all parts of our business to help them become better managed and control payment risk.
Main Responsibilities:
Data Analysis and Reporting

Performs data analysis and applies developed data mining techniques to identify suspicious behavior trends, outliers, anomalies and other issues that represent fraud risk, recommends solutions to deter fraud attacks and communicates those trends to designated leads
Performs ad-hoc investigative and statistical analytics to facilitate risk investigations and assists external stakeholders in their investigation of risk events
Perform link analysis of known patterns of fraud and anomalies where known patterns are violated to uncover new fraud patterns
Develops operational metrics and benchmarking analysis and comparisons through reporting and trending for designated regional or country fraud prevention, and also daily, weekly and monthly reports, maintains key performance indicators towards global consistency to align to business expectations and business drivers

Risk and fraud detection models

Adjusts and maintains fraud detection models to prevent losses on real time on-line customer transactions
Applies developed skills and knowledge in designated regional or country fraud detection models to provide the greatest efficiency and effectiveness balancing PFCC and partner KPI’s
Optimizes the fraud risk model by removing rules with low loss rate but keeping the structure to ensure that fraud attempts can be quickly identified; improves decline rate in out sort rules and loss rate in approve rules
Assist in validation of the risk model frequently and in-depth when encountering a fraud attack
Run reports to validate the model periodically
Ensure fraud detection methods offered comply with financial industry security regulations and consumer privacy laws as they relate to the Company's operations
Maintains user access to fraud prevention systems for designated regional or country fraud prevention
Recommends system enhancement requests, evaluates new tools, applications and services

Monitoring operations and industry trends

Provides successful coordination with other Company departments
Awareness of store policy & procedure changes that might impact the model and adjust accordingly
Awareness of industry trends in any fraud prevention related areas, including new fraud patterns, services, detection tools or any new technology
Analyse system declined suspected fraud orders, fraud chargebacks and customer reported fraud tracker data regularly and propose adjustments to the risk model

Requirements

Passionate about working with numbers and data
Very Fluent English (oral and written) – 90% plus required
Degree in statistics, mathematics industrial engineering or related area of study, or equivalent experience preferred
Relevant experience in data analytics, and/or statistics, and/or risk modelling, and/or fraud detection, and/or development of technical solutions for fraud prevention preferred
Strong proficiency in MS Excel, MS Access, MS Power Point required
Python expertise desired
Good understanding of statistics and a proven background identifying, understanding, solving, and communicating complex problems
Relative understanding of risk mitigation principles & practices preferred
Good business writing and verbal communication skills
Must have good interpersonal skills with the ability to work with peers and personnel at all both higher and lower job levels
Ability to work flexible hours including occasional overtime as required
Proven ability to deal with ambiguity
Demonstrates ability to perform independently and show initiative
Proven ability to manage and deliver on multiple tasks and projects that overlap
Proven ability to manage and deliver multiple tasks and projects in a fast, paced and changing environment
Self-starter, innovative, creative thinking, real-world achievement, passion with data are highly coveted attributes for successful candidate