As of January 01, 2025, the average annual salary for a Department Manager Fraud Prevention in Montgomery, AL is $95,300. Salary.com reports that pay typically ranges from $84,800 to $109,500, with most professionals earning between $75,240 and $122,428.
| Annual Salary |
Monthly Pay |
Weekly Pay |
Hourly Wage |
|
| 75th Percentile | $109,500 | $9,125 | $2,106 | $53 |
| Average | $95,300 | $7,942 | $1,833 | $46 |
| 25th Percentile | $84,800 | $7,067 | $1,631 | $41 |
An entry-level Department Manager Fraud Prevention with under 1 year experience makes about $90,606. With less than 2 years of experience, a mid-level Department Manager Fraud Prevention makes around $91,072. After 2-4 years, the Department Manager Fraud Prevention pay rises to about $92,157. Those senior Department Manager Fraud Prevention with 5-8 years of experience earn roughly $93,398, and those Department Manager Fraud Prevention having 8 years or more experience are expected to earn about $95,968 on average.
| Levels | Salary |
|---|---|
| Entry Level Department Manager Fraud Prevention | $90,606 |
| Intermediate Level Department Manager Fraud Prevention | $91,072 |
| Senior Level Department Manager Fraud Prevention | $92,157 |
| Specialist Level Department Manager Fraud Prevention | $93,398 |
| Expert Level Department Manager Fraud Prevention | $95,968 |
| Entry Level | 5% |
| Mid Level | 4% |
| Senior Level | 3% |
| Top Level | 2% |
| Experienced | 1% |
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Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
Leadership: Knowledge of and ability to employ effective strategies that motivate and guide other members within our business to achieve optimum results.
Data Analysis: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.
Commercial Banking: Is a profit oriented banking by providing loans to customers and charging interest. The bank’s funds come from money deposited by the bank customers in saving accounts, checking accounts, money market accounts, and certificates of deposit (CDs).
| Skill | Salary | Demand |
|---|---|---|
|
Fintech
|
$101,018 |
6%
|
|
Cybersecurity
|
$101,018 |
6%
|
|
Influencing
|
$100,065 |
5%
|
|
Python
|
$100,065 |
5%
|
|
Operational Risk
|
$100,065 |
5%
|
|
Results Oriented
|
$100,065 |
5%
|
