Fraud Claims Analyst

Allianz Ireland
  • Job Purpose/ Role

    The Claims Fraud Analyst role is a specialist Data Analyst position within the Claims Analytics and Insights team, responsible for sourcing, analysing and interpreting data on potential claims fraud, and in communicating this effectively to the Claims Fraud team for investigation. ~crlf~~crlf~Supporting the all-island fraud strategy, the Claims Fraud Analyst will be experienced in managing and manipulating data to identify and report on trends that are linked to potential fraud.

  • Key Responsibilities

    Analysis and Interpretation of Data~crlf~• Gather, analyse and interpret relevant claims data to identify instances of potentially fraudulent activity~crlf~• Utilise specialist data visualisation and analytics software to facilitate the analysis of claims customer activity and potential fraud ~crlf~• Analyse claims data across variables such as distribution channel and line of business to understand potential relationships~crlf~• Support the claims fraud team to identify and analyse trends such as claims fraud flags ~crlf~• Development of new referral indicators ~crlf~• Keep up-to-date on available internal and external data sources and technologies to track, analyse and identify potential fraud~crlf~• Collaborate with colleagues across the organisation to conduct trend analysis, and identify opportunities for improvements to fraud identification and management ~crlf~• Review referral indicators, business rules, network and prediction scores ~crlf~~crlf~Claims Fraud MI~crlf~• Track and report claims management information, both scheduled and ad-hoc including; cost of claims, claims volume and fraud savings ~crlf~• Manage data sets to ensure accessibility, accuracy and relevance~crlf~• Integrate relevant data to identify previously unknown or considered relationships between data sets ~crlf~• Recommend best actions to the business based on the output~crlf~• Continually refine analysis to maximise on business objectives, provide input to the fraud strategy ~crlf~~crlf~Interaction and Communication ~crlf~• Support the Claims fraud team with data-driven insights to support the development and evolution of our claims fraud strategy~crlf~• Share knowledge and best practice in data analysis and potential fraud identification with colleagues~crlf~• Support implementation and management of our all-island fraud strategy, ~crlf~• Work closely with relevant business areas including; operations, sales, underwriting and IT~crlf~• Develop propensity models to identify and understand potential link to customer behaviour and potential claims fraud ~crlf~• Represent the claims fraud team at relevant internal committees and projects and external forums as required

  • Key Requirements/ Skills

    Essential Criteria~crlf~• 3+ Years in a data analytics related role~crlf~• Bachelor’s degree - Data Analytics, Mathematics, Engineering, Statistics, Economics, etc.~crlf~~crlf~Desirable Criteria~crlf~• Knowledge of i2 fraud software~crlf~• Experience in using analytical platforms and related programming languages (e.g. SAS, SQL, , Python, R, etc.)~crlf~• Experience of data infrastructures, involvement in strategic data projects and delivering enhancements to analytics processes (Automation, Real time Analytics, Machine Learning, Data Visualisation)~crlf~• Experience in working within a regulated environment

  • About Allianz

    Allianz is the home for those who dare – a supportive place where you can take the initiative to grow and to actively strengthen our global leadership position. By truly caring about people – both its 88 million private and corporate customers and more than 140,000 employees – Allianz fosters a culture where its employees are empowered to collaborate, perform, embrace trends and challenge the industry. Our main ambition is to be our customers’ trusted partner, instilling them with the confidence to grow. If you dare, join us at Allianz Group.~crlf~~crlf~Allianz is an equal opportunity employer. Everybody is welcome, regardless of other characteristics such as gender, age, origin, nationality, race or ethnicity, religion, disability, or sexual orientation.

Job Purpose/ Role

The Claims Fraud Analyst role is a specialist Data Analyst position within the Claims Analytics and Insights team, responsible for sourcing, analysing and interpreting data on potential claims fraud, and in communicating this effectively to the Claims Fraud team for investigation. ~crlf~~crlf~Supporting the all-island fraud strategy, the Claims Fraud Analyst will be experienced in managing and manipulating data to identify and report on trends that are linked to potential fraud.

Key Responsibilities

Analysis and Interpretation of Data~crlf~• Gather, analyse and interpret relevant claims data to identify instances of potentially fraudulent activity~crlf~• Utilise specialist data visualisation and analytics software to facilitate the analysis of claims customer activity and potential fraud ~crlf~• Analyse claims data across variables such as distribution channel and line of business to understand potential relationships~crlf~• Support the claims fraud team to identify and analyse trends such as claims fraud flags ~crlf~• Development of new referral indicators ~crlf~• Keep up-to-date on available internal and external data sources and technologies to track, analyse and identify potential fraud~crlf~• Collaborate with colleagues across the organisation to conduct trend analysis, and identify opportunities for improvements to fraud identification and management ~crlf~• Review referral indicators, business rules, network and prediction scores ~crlf~~crlf~Claims Fraud MI~crlf~• Track and report claims management information, both scheduled and ad-hoc including; cost of claims, claims volume and fraud savings ~crlf~• Manage data sets to ensure accessibility, accuracy and relevance~crlf~• Integrate relevant data to identify previously unknown or considered relationships between data sets ~crlf~• Recommend best actions to the business based on the output~crlf~• Continually refine analysis to maximise on business objectives, provide input to the fraud strategy ~crlf~~crlf~Interaction and Communication ~crlf~• Support the Claims fraud team with data-driven insights to support the development and evolution of our claims fraud strategy~crlf~• Share knowledge and best practice in data analysis and potential fraud identification with colleagues~crlf~• Support implementation and management of our all-island fraud strategy, ~crlf~• Work closely with relevant business areas including; operations, sales, underwriting and IT~crlf~• Develop propensity models to identify and understand potential link to customer behaviour and potential claims fraud ~crlf~• Represent the claims fraud team at relevant internal committees and projects and external forums as required

Key Requirements/ Skills

Essential Criteria~crlf~• 3+ Years in a data analytics related role~crlf~• Bachelor’s degree - Data Analytics, Mathematics, Engineering, Statistics, Economics, etc.~crlf~~crlf~Desirable Criteria~crlf~• Knowledge of i2 fraud software~crlf~• Experience in using analytical platforms and related programming languages (e.g. SAS, SQL, , Python, R, etc.)~crlf~• Experience of data infrastructures, involvement in strategic data projects and delivering enhancements to analytics processes (Automation, Real time Analytics, Machine Learning, Data Visualisation)~crlf~• Experience in working within a regulated environment

About Allianz

Allianz is the home for those who dare – a supportive place where you can take the initiative to grow and to actively strengthen our global leadership position. By truly caring about people – both its 88 million private and corporate customers and more than 140,000 employees – Allianz fosters a culture where its employees are empowered to collaborate, perform, embrace trends and challenge the industry. Our main ambition is to be our customers’ trusted partner, instilling them with the confidence to grow. If you dare, join us at Allianz Group.~crlf~~crlf~Allianz is an equal opportunity employer. Everybody is welcome, regardless of other characteristics such as gender, age, origin, nationality, race or ethnicity, religion, disability, or sexual orientation.


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