Bank OZK operates a 1,000+ person financial services organization headquartered in Arkansas, with a hiring surge dominated by finance (155 roles) and operations staff. The tech stack reveals a hybrid analytics and core banking architecture—SAS, Power BI, Alteryx, and dbt for decisioning; Fiserv and SWIFT for settlement; Workday for workforce management. Active projects center on fraud detection, control remediation, and business development, while pain-point signals (transaction fraud, risk control, network bottlenecks) suggest the bank is modernizing compliance and operational infrastructure to support faster lending growth.
Bank OZK is a publicly traded regional bank serving mid-market and community lending across the United States from its Little Rock headquarters. The institution combines traditional relationship banking with data-driven decision-making, using SAS and Snowflake for analytics and risk modeling alongside core banking systems (Fiserv, SWIFT). Current initiatives include fraud detection strategy implementation, control gap remediation, and a risk control self-assessment program—indicating a multi-year operational maturity push. The rapid hiring velocity (173 roles posted in the last 30 days) is concentrated in finance and operations, consistent with scaling compliance, credit, and back-office functions.
Bank OZK uses Fiserv and SWIFT for core banking, SAS and Power BI for analytics, Snowflake and dbt for data transformation, Workday for HR, ServiceNow for IT service management, and Azure DevOps for deployment.
Active projects include fraud detection strategy implementation, control gap remediation, risk control self-assessment, business development in trust and wealth, down payment assistance programs, and operational risk training and awareness initiatives.
Bank OZK's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.