Coding is increasingly not required for basic financial analysis but is rapidly becoming necessary for advanced roles, high-frequency trading, and handling large datasets. While Excel remains dominant for traditional financial modeling, proficiency in Python, SQL, and VBA allows for faster, more sophisticated data analysis, automation, and machine learning, particularly in investment banking, asset management, and fintech roles.
Beyond programmers and software developers, others in the finance industry may likewise use programming. For example, financial analysts and risk managers may use programming languages to analyze large data sets or create tools for making investment predictions.
The Level I, II, and III exams themselves remain calculator and Excel-driven. Python does not appear in the question bank, and no coding is required to pass all three levels. But and this is critical starting in 2026, candidates must complete at least one Practical Skills Module (PSM) per level to access exam results.
One key aspect of financial analysis is financial statement analysis, which involves comparing a company's financial statements to industry benchmarks and historical trends. Financial analysis is built on three core financial statements: the income statement, balance sheet and cash flow statement.
In finance, programming is useful in a variety of situations. These situations include pricing derivatives, setting up electronic trading systems, and managing systems. Banks such as Credit Suisse and Barclays are most interested in Java and Python skills. C++ is not as popular now but is still used.
Finance coding jobs blend programming with financial analysis, covering roles from Quantitative Developers (Quants) building trading algorithms (using C++, Python, Java) to Software Engineers developing financial platforms (backend, frontend) and data roles (Data Scientists, AI Specialists) for modeling and automation, often in FinTech, banking, and hedge funds, requiring languages like Python, SQL, Java, and C++. Key areas include algorithmic trading, financial infrastructure, risk management, and data analysis, with high demand for skills in Python, Java, C++, and data science.
Financial benchmarking & market analysis
ChatGPT supports evaluating financial performance and market positioning through benchmarking, competitor research, and industry analysis. Use web search or deep research for deeper real-time insights.
Common types of financial analysis include vertical and horizontal analysis, leverage analysis, liquidity analysis, and profitability analysis.
CFA is one of the toughest courses in the field of finance. To clear every level, the candidate needs to dedicate at least 300 hours of learning. MBA, on the other hand, is much easier as compared to CFA.
Here are ten high-paying non-coding jobs in IT:
Top 7 Most In-Demand Programming Languages for Finance and...
Is CFA tougher than CA? A: The CFA and CA (Chartered Accountant) qualifications have different focuses and challenges. While both are demanding, many find CA to be more rigorous due to its extensive practical training and exams.
Is a CFA job stressful? Finance roles are typically associated with high demands, tight schedules, and intricate decision-making and are inherently demanding. Yet, most professionals love the job and are at home in high-stress situations.
What are the best AI tools for financial services in 2025? Top AI tools include DataSnipper, Workiva, MindBridge, Datarails, Cube, Ramp, Brex, Validis, Power BI with Copilot, and Alteryx. Each supports different needs—from automation and anomaly detection to spend management and ESG reporting.
What are entry-level programming jobs? 5 roles to consider
SecDb is an ecosystem within Goldman Sachs which consists of object-oriented database technology, and data synchronizing mechanism. Also, the other core components of the SecDb are a language which we'll be discussing called Slang, which is a scripting language.
Work-from-home finance jobs are positions available in the finance industry that have job duties you can complete from a remote location.