Find & Apply For Credit Analyst / Authorizer Jobs In Forrest, Mississippi
Credit Analyst / Authorizer jobs in Forrest, Mississippi involve evaluating credit data and financial statements to determine creditworthiness and authorize credit limits. Responsibilities include reviewing applications, analyzing payment history, and assessing risk levels. Successful candidates possess strong analytical skills, attention to detail, and the ability to make sound credit decisions. Below you can find different Credit Analyst / Authorizer positions in Forrest, Mississippi.
Jobs in Forrest
Browse jobs from a variety of sources below, sorted with the most recently published, nearest to the top. Click the title to view more information and apply online.
Latest Jobs in Forrest
Salary Information & Job Trends In this Region
Credit Analysts / Authorizers in Forrest, Mississippi assess and approve credit to manage financial risk. - Entry-level Credit Analyst salaries range from $40,000 to $50,000 per year - Mid-career Credit Risk Manager salaries range from $55,000 to $70,000 per year - Senior Credit Officer salaries range from $75,000 to $95,000 per year The role of Credit Analysts in Forrest has a long history, closely tied to the region's banking sector which began to develop robustly in the early 20th century. The job has traditionally involved assessing the creditworthiness of individuals and businesses based on their financial history and broader economic conditions. Over the decades, the job of Credit Analysts in Forrest has evolved significantly. Initially focused mainly on local agricultural businesses, the role now encompasses a variety of industries, including retail and technology startups, reflecting the broader economic diversification of the area. The introduction of sophisticated statistical and analytical tools has also transformed how credit analysis is conducted, making it more efficient and precise. Current trends in the credit analysis field in Forrest include a growing reliance on big data and artificial intelligence to predict loan default likelihood, leading to more accurate and nuanced risk assessments. Additionally, there's a noticeable shift towards sustainable and socially responsible lending practices, mirroring global movements in finance.
