{"id":144877,"date":"2026-10-28T17:23:21","date_gmt":"2026-10-28T11:53:21","guid":{"rendered":"https:\/\/www.guvi.in\/blog\/?p=144877"},"modified":"2026-10-28T17:23:23","modified_gmt":"2026-10-28T11:53:23","slug":"data-analyst-projects-banking-insurance","status":"publish","type":"post","link":"https:\/\/www.guvi.in\/blog\/data-analyst-projects-banking-insurance\/","title":{"rendered":"Data Analyst Projects Bankers Can Build with Banking or Insurance Data"},"content":{"rendered":"\n<p>Banking and insurance professionals can build data analyst portfolios using projects on loan repayment, insurance claims, customer churn, and policy renewals. Excel, SQL, Power BI, and Python help analyse data, identify trends, and present actionable insights that demonstrate practical skills for transitioning into data analyst roles.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>TL;DR<\/strong><\/h2>\n\n\n\n<ul>\n<li>Banking projects examine loan repayment, customer churn, transaction trends, and branch performance.<\/li>\n\n\n\n<li>Insurance projects analyse claims, policy renewals, processing times, and customer segments.<\/li>\n\n\n\n<li>Excel, SQL, and Power BI provide a practical starting toolkit; Python supports more repeatable analysis.<\/li>\n\n\n\n<li>A strong portfolio explains the business question, data source, preparation, findings, and limitations.<\/li>\n\n\n\n<li>Start with one complete project, then add projects that demonstrate different analytical skills.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Quick Answer<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>Choose a business question you understand, such as which loan categories show higher late-payment rates or where insurance claims take longer to process. Use public or synthetic data, analyse it with Excel or SQL, and present the findings in a Power BI dashboard. Find datasets through Kaggle and learn dashboard basics with Microsoft Power BI resources.\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/zen-class\/data-science-course\/?utm_source=blog&#038;utm_medium=cta-button&#038;utm_campaign=data-analyst-projects-banking-insurance\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Explore HCL GUVI Data Science Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<h2 class=\"wp-block-heading\"><strong>Choose Projects That Solve Clear Business Questions<\/strong><\/h2>\n\n\n\n<p>A useful project starts with a specific business question and measures that answer it.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Banking data analytics projects<\/strong><\/h3>\n\n\n\n<ul>\n<li><a href=\"https:\/\/www.scribd.com\/presentation\/566036605\/EDA-CASE-STUDY-ANALYSIS-PPT\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"><strong>Loan repayment analysis<\/strong><\/a><strong>:<\/strong> Compare late-payment rates across loan types, loan amounts, or repayment periods.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.guvi.in\/hub\/customer-churn-prediction-project-using-classification-techniques\/what-is-customer-churn-prediction-\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"><strong>Customer churn analysis<\/strong><\/a><strong>:<\/strong> Examine account activity and available customer attributes to identify patterns associated with account closure.<\/li>\n\n\n\n<li><strong>Branch performance <\/strong><a href=\"https:\/\/www.guvi.in\/hub\/power-bi-tutorial\/designing-an-effective-dashboard-layout\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>dashboard<\/strong><\/a><strong>:<\/strong> Compare deposits, loan activity, service volumes, and customer growth across branches.<\/li>\n\n\n\n<li><strong><a href=\"https:\/\/journey.temenos.com\/docs\/JM-Analytics\/TransactionTrendAnalyze.htm\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Transaction trend <\/a><\/strong><a href=\"https:\/\/journey.temenos.com\/docs\/JM-Analytics\/TransactionTrendAnalyze.htm\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"><strong>analysis<\/strong><\/a><strong>:<\/strong> Explore spending or transaction volumes by category, channel, and time period.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Insurance data projects<\/strong><\/h3>\n\n\n\n<ul>\n<li><a href=\"https:\/\/www.guvi.in\/blog\/insurance-claims-executive-to-data-analyst\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Claims analysis<\/strong><\/a><strong>:<\/strong> Compare claim amounts, claim types, and settlement times.<\/li>\n\n\n\n<li><a href=\"https:\/\/umbrex.com\/resources\/industry-analyses\/how-to-analyze-a-life-insurance-company\/policy-renewal-and-persistency-rate-analysis\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"><strong>Policy renewal analysis<\/strong><\/a><strong>:<\/strong> Examine renewal rates by policy type, customer tenure, or available segment.<\/li>\n\n\n\n<li><a href=\"https:\/\/vcasoftware.com\/claims-management-dashboard\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"><strong>Claims processing dashboard<\/strong><\/a><strong>:<\/strong> Track submitted, pending, approved, and settled claims.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.guvi.in\/blog\/product-for-multiple-customer-segmentation\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Customer segmentation<\/strong><\/a><strong>:<\/strong> Group policyholders by relevant characteristics to compare renewal or service patterns.<\/li>\n<\/ul>\n\n\n\n<div style=\"background-color: #099f4e; border: 3px solid #110053; border-radius: 12px; padding: 18px 22px; color: #FFFFFF; font-size: 18px; font-family: Montserrat, Helvetica, sans-serif; line-height: 1.6; box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15); max-width: 750px;\"> \n  <strong style=\"font-size: 22px; color: #FFFFFF;\">\ud83d\udca1 Did You Know?<\/strong> \n  <br \/><br \/> \nA useful dashboard answers a business question and highlights patterns worth investigating. Each visual should support a specific question.\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Build Three Practical Portfolio Projects<\/strong><\/h2>\n\n\n\n<p>Use a public dataset or create synthetic records when real data is confidential.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Project 1: Loan repayment analysis<\/strong><\/h3>\n\n\n\n<p><strong>Business question:<\/strong> Which loan categories show higher late-payment rates in the dataset?<\/p>\n\n\n\n<ul>\n<li>Check missing values, duplicates, inconsistent categories, and data types.<\/li>\n\n\n\n<li>Use <a href=\"https:\/\/www.guvi.in\/blog\/guide-on-sql-for-data-science\/\" target=\"_blank\" rel=\"noreferrer noopener\">SQL<\/a> or <a href=\"https:\/\/www.guvi.in\/blog\/excel-to-data-analytics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Excel<\/a> to calculate repayment and delinquency rates.<\/li>\n\n\n\n<li>Compare results across loan types or periods.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.guvi.in\/blog\/data-visualization-in-data-science\/\" target=\"_blank\" rel=\"noreferrer noopener\">Visualise<\/a> the main differences and identify questions for further investigation.<\/li>\n<\/ul>\n\n\n\n<p>Avoid treating association as proof of cause; explain the dataset\u2019s limitations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Project 2: Insurance claims dashboard<\/strong><\/h3>\n\n\n\n<p><strong>Business question:<\/strong> How do claim volumes and processing times vary by claim type or period?<\/p>\n\n\n\n<ul>\n<li>Standardise dates, claim statuses, categories, and numerical fields.<\/li>\n\n\n\n<li>Calculate claim counts, average processing time, and outstanding claims.<\/li>\n\n\n\n<li>Build a <a href=\"https:\/\/www.guvi.in\/hub\/power-bi-tutorial\/understanding-power-bi-dashboards\/\" target=\"_blank\" rel=\"noreferrer noopener\">Power BI dashboard<\/a> with filters for period, claim type, and status.<\/li>\n\n\n\n<li>Highlight backlogs or unusual changes that deserve operational review.<\/li>\n<\/ul>\n\n\n\n<p>Define processing time consistently, such as the number of days between claim submission and settlement. State how you handle open claims, since excluding them can make the average appear shorter than the experience.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Project 3: Customer churn or policy renewal<\/strong><\/h3>\n\n\n\n<p><strong>Business question:<\/strong> Which customer groups show lower retention or renewal rates?<\/p>\n\n\n\n<ul>\n<li>Calculate retention or renewal rates by tenure, product, or available segment.<\/li>\n\n\n\n<li>Compare patterns over time and identify groups to investigate further.<\/li>\n\n\n\n<li>Use SQL or Python for analysis and a dashboard to communicate results.<\/li>\n\n\n\n<li>Recommend follow-up questions about service delays, product fit, or customer engagement.<\/li>\n<\/ul>\n\n\n\n<p>Define churn or renewal precisely before calculating rates. For example, distinguish a policy that reaches its renewal date from one that is eligible for renewal, so the comparison uses a consistent denominator.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Use a Practical Analytics Toolkit<\/strong><\/h2>\n\n\n\n<p>Start with a small toolkit that takes raw data to a clear answer.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Recommended tools<\/strong><\/h3>\n\n\n\n<ul>\n<li><strong>Excel:<\/strong> Use formulas, pivot tables, filters, and charts to inspect and summarise data.<\/li>\n\n\n\n<li><strong>SQL:<\/strong> Query tables, join datasets, aggregate results, and compare groups.<\/li>\n\n\n\n<li><strong>Power BI:<\/strong> Build interactive dashboards and communicate trends.<\/li>\n\n\n\n<li><strong>Python:<\/strong> Use <a href=\"https:\/\/www.guvi.in\/blog\/pandas-introduction\/\" target=\"_blank\" rel=\"noreferrer noopener\">pandas<\/a> for repeatable data cleaning and analysis when the project needs it.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/zen-class\/data-science-course\/?utm_source=blog&#038;utm_medium=cta-button&#038;utm_campaign=data-analyst-projects-banking-insurance\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Explore HCL GUVI Data Science Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<h2 class=\"wp-block-heading\"><strong>Present Your Projects Clearly<\/strong><\/h2>\n\n\n\n<p>Recruiters need to understand your question, method, and findings.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Include these elements<\/strong><\/h3>\n\n\n\n<ul>\n<li><strong>Business question:<\/strong> State the problem in one or two sentences.<\/li>\n\n\n\n<li><strong>Data source:<\/strong> Link to the dataset or identify it as synthetic.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.guvi.in\/blog\/what-is-data-preparation-processes-and-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Data preparation<\/strong><\/a><strong>:<\/strong> Document missing values, duplicates, and assumptions.<\/li>\n\n\n\n<li><strong>Analysis:<\/strong> Include relevant SQL queries, calculations, or Python notebooks.<\/li>\n\n\n\n<li><strong>Findings:<\/strong> Present key results with readable charts and clear labels.<\/li>\n\n\n\n<li><strong>Recommendations:<\/strong> Suggest next steps that follow from the evidence.<\/li>\n\n\n\n<li><strong>Limitations:<\/strong> Explain what the dataset cannot establish.<\/li>\n<\/ul>\n\n\n\n<p>Include a README that makes the question, findings, tools, and limitations easy to locate. Before publishing, review every chart for accurate labels, consistent scales, and clear units; remove visuals that do not answer the project question or support a defensible recommendation carefully.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<div class=\"container-lazyload preview-lazyload container-youtube js-lazyload--not-loaded\"><a href=\"https:\/\/www.youtube.com\/watch?v=W002PK8gPLQ\" class=\"lazy-load-youtube preview-lazyload preview-youtube\" data-video-title=\"Increase Your Salary with These 3 Data Science Projects | Must-Try | Data Science | GUVI\" title=\"Play video &quot;Increase Your Salary with These 3 Data Science Projects | Must-Try | Data Science | GUVI&quot;\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=W002PK8gPLQ<\/a><noscript>Video can&#8217;t be loaded because JavaScript is disabled: <a href=\"https:\/\/www.youtube.com\/watch?v=W002PK8gPLQ\" title=\"Increase Your Salary with These 3 Data Science Projects | Must-Try | Data Science | GUVI\" target=\"_blank\" rel=\"noopener\">Increase Your Salary with These 3 Data Science Projects | Must-Try | Data Science | GUVI (https:\/\/www.youtube.com\/watch?v=W002PK8gPLQ)<\/a><\/noscript><\/div>\n<\/div><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">2. <strong>Connect the work to your experience.<\/strong><\/h3>\n\n\n\n<p>If you work in banking operations, customer service, sales, or insurance processing, explain the domain knowledge you bring. Use the project to demonstrate technical skills rather than describing your existing responsibilities as analytics experience without evidence.<\/p>\n\n\n\n<p>For example, experience answering customer queries can help you frame a service-quality question, while operations experience can help you understand turnaround times. Explain this context briefly, then let the analysis demonstrate your technical ability.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<p>Banking and insurance professionals can build relevant data analyst portfolios by investigating familiar business questions with accessible tools. Loan repayment analysis, claims dashboards, and customer retention projects provide practical starting points for early-career career switchers. Complete one project and then add work demonstrating SQL, dashboard design, or Python.<\/p>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/zen-class\/data-science-course\/?utm_source=blog&#038;utm_medium=cta-button&#038;utm_campaign=data-analyst-projects-banking-insurance\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Explore HCL GUVI Data Science Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<h2 class=\"wp-block-heading\"><strong>FAQs<\/strong><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1793172209814\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>1. Which project should a beginner start with?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Start with loan repayment analysis or an insurance claims dashboard. Both have clear business questions and work with Excel or Power BI.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172216268\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>2. Do I need Python for a data analyst portfolio?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Not always. Excel, SQL, and Power BI demonstrate useful analytical skills, while Python expands your options for repeatable analysis.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172225040\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>3. Where can I find banking or insurance datasets?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Explore public datasets on Kaggle or use synthetic data. Check the dataset documentation and usage permissions before publishing your project.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172232686\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>4. How many projects should my portfolio contain?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Start with one complete project and add two more as your skills improve. Clear documentation and sound analysis matter more than quantity.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172241288\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>5. Can non-IT professionals apply for data analyst jobs?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes, if they meet the role requirements and demonstrate relevant skills. Connect your domain knowledge to business understanding and use projects to show technical ability.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172253177\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>6. Should I include projects on my r<\/strong>esume?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes. Include the business question, tools, analysis, and key finding, with a working project link where available.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1793172268467\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>7. How can I make my project stand out?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Choose a focused question, verify calculations, use readable visuals, and explain limitations. End with practical recommendations supported by your analysis.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Banking and insurance professionals can build data analyst portfolios using projects on loan repayment, insurance claims, customer churn, and policy renewals. Excel, SQL, Power BI, and Python help analyse data, identify trends, and present actionable insights that demonstrate practical skills for transitioning into data analyst roles. TL;DR Quick Answer Choose a business question you understand, [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":144880,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[745,13,16],"tags":[],"views":"27","authorinfo":{"name":"HCL GUVI","url":"https:\/\/www.guvi.in\/blog\/author\/guvipr\/"},"thumbnailURL":"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/10\/Data-Analyst-Projects-Bankers-Can-Build-with-Banking-or-Insurance-Data-300x116.webp","_links":{"self":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/144877"}],"collection":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/comments?post=144877"}],"version-history":[{"count":4,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/144877\/revisions"}],"predecessor-version":[{"id":144972,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/144877\/revisions\/144972"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media\/144880"}],"wp:attachment":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media?parent=144877"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/categories?post=144877"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/tags?post=144877"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}