RBI Grade B Salary 2025 and Important Dates

RBI Grade B Salary and Quick Highlight

Good news for all those preparing for bank jobs! The Reserve Bank of India (RBI) has officially released the RBI Grade B 2025 recruitment notification. This is a golden chance to build a career with India’s central bank. The post comes with an attractive RBI Grade B Salary starting around ₹1,50,374/- per month, making it one of the highest-paying government jobs in banking.

The online application form is available from September 10, 2025, and the last date to apply is September 30, 2025. If you’ve been dreaming of a stable and rewarding government job, this is your chance! Keep reading for complete details on vacancy, eligibility, exam date, salary, and how to apply online.

RBI Grade B 2025 | Vacancy Details

Here’s the complete breakdown of vacancies released under this recruitment:

Eligibility Criteria for RBI Grade B 2025

Age Limit: Candidates must be between 21 and 30 years as of September 1, 2025. (Relaxation available for reserved categories).

Educational Qualification:

• DSIM Cadre: Master’s in Statistics / Econometrics / Data Science / AI / Machine Learning with 55% marks (50% for SC/ST/PwBD) OR 4-year Bachelor’s with 60% marks.
• General Cadre: Graduation with 60% marks (50% for SC/ST/PwBD) OR Post-Graduation with 55% marks.
• DEPR Cadre: Master’s in Economics / Finance / related subjects with minimum 55% marks (50% for SC/ST/PwBD).

RBI Grade B Salary 2025

RBI Grade B Salary Officers enjoy one of the best salary packages in the government sector.

• Basic Pay: ₹78,450/- per month (with increments as per pay scale).
• Gross Salary: Approx. ₹1,50,374/- per month.
• Perks & Benefits: DA, HRA, medical facilities, leave fare concession, loans at concessional rates, NPS coverage, and much more.

Selection Process for RBI Grade B 2025

The recruitment process has three stages:

1. Phase I (Prelims – Online Exam):
   • General Awareness
   • English Language
   • Quantitative Aptitude
   • Reasoning
2. Phase II (Mains – Online Exam):
   • Economic & Social Issues (Objective + Descriptive)
   • English (Descriptive – Writing Skills)
   • General Finance & Management (Objective + Descriptive)
3. Interview (75 Marks): Final merit list will be prepared based on Phase II + Interview scores.

How to Apply Online for RBI Grade B 2025

Follow these simple steps to apply:

1. Visit the official RBI website.
2. Open the “Opportunities@RBI” and Current Vacancies section.
3. Click on Direct Recruitment for RBI Grade B 2025.
4. Register with basic details and get your provisional ID & password.
5. Log in and fill the form with accurate details.
6. Upload your photo, signature, thumb impression, and declaration.
7. Pay the application fee online.
8. Submit the form and take a printout for future use.

Most Important Dates

Application Fee

• SC/ST/PwBD: ₹100/- + 18% GST
• GEN/OBC/EWS: ₹850/- + 18% GST
• RBI Staff: No Fee

RBI Grade B 2025 | Detailed Syllabus

The RBI Grade B syllabus is vast and covers advanced topics in Statistics, Economics, Econometrics, Data Science, and Computing. Below is the topic-wise syllabus in a simplified format:

1. Probability, Distributions & Sampling

• Probability concepts: Classical & axiomatic approach, Bayes’ theorem, laws of large numbers.
• Probability inequalities, characteristic functions, central limit theorem.
• Distributions:
  • Discrete: Binomial, Poisson, Geometric, Negative Binomial.
  • Continuous: Uniform, Normal, Exponential, Logistic, Log-normal, Beta, Gamma, Weibull.
  • Others: Bivariate normal.
• Sampling distributions: Chi-square, t, F, Z-distributions (applications).
• Large sample tests, contingency tables.
• Sampling methods: Simple random, Stratified, Systematic, Cluster, Two-stage, PPS.
• Estimation methods: Ratio, Regression.
• Issues: Non-sampling errors, non-response.

2. Linear Models & Economic Statistics

• Linear Algebra: Vectors, matrices, inverse, g-inverse, orthogonal & idempotent matrices, quadratic forms, eigenvalues & eigenvectors.
• Regression:
  • Simple & multiple regression, assumptions, inference, diagnostics.
  • Polynomial regression, Box-Cox transformations.
  • Weighted least squares, correlated observations.
  • Model selection (ridge, LASSO, Elastic Net).
  • Outlier detection, categorical data (dummy variables).
• Economic Statistics:
  • Index numbers – fixed base, chain base, splicing.
  • Measurement of inequality – Gini coefficient, Lorenz curve.
  • Basics of macroeconomics & national accounts.

3. Statistical Inference & Non-Parametric Tests

• Estimation: Unbiasedness, consistency, sufficiency, efficiency.
  • MVUE, Rao-Blackwell theorem, Lehmann-Scheffe theorem, Cramer-Rao inequality.
  • Estimation methods: Moments, MLE, Least squares, Chi-square, Bayes.
• Testing of Hypothesis:
  • Type I & II errors, significance level, p-value, power of a test.
  • Neyman-Pearson Lemma, Likelihood Ratio Tests.
  • Goodness of Fit tests, Bartlett’s test.
• Non-Parametric Tests:
  • K-S test, Sign test, Wilcoxon tests, Mann-Whitney U-test.
  • Kruskal-Wallis ANOVA, Friedman’s test.
  • Rank correlations (Kendall’s Tau, Spearman).
  • Distribution of order statistics, density estimation.

4. Stochastic Processes

• Poisson Process: Interarrival times, Non-homogeneous Poisson, Compound Poisson.
• Markov Chains: Transition matrix, Chapman Kolmogorov equations, regular chains, stationary distributions, periodicity, recurrence, limit theorems.
• Brownian Motion: Random walk limit, martingales, properties.

5. Multivariate Analysis

• Multivariate normal distribution (properties).
• Mahalanobis’ D² statistics.
• Principal Component Analysis (PCA), Factor Analysis.
• Discriminant Analysis (LDA).
• Canonical correlation analysis.
• Cluster Analysis – methods & validation.
• Logit & Probit models.

6. Econometrics & Time Series

• Econometrics:
  • General linear model, OLS, GLS, heteroscedasticity, autocorrelation.
  • Instrumental variables, ridge regression, panel regression.
  • Distributed lag models, simultaneous equations, identification problem.
  • Estimation methods, prediction, simultaneous confidence intervals.
• Time Series:
  • Stationarity concepts.
  • AR, MA, ARMA, ARIMA, SARIMA models.
  • Model selection (ACF, PACF), diagnostic checks.
  • ARCH/GARCH models.
  • Tests for non-stationarity (trend vs difference stationary).

7. Optimization & Statistical Computing

• Optimization:
  • Unconstrained optimization: Calculus, Newton’s method, Gradient methods, Quasi-Newton.
  • Constrained optimization: Lagrange multipliers, Penalty methods.
  • Linear Programming: Convex sets, Simplex method, Graphical method.
• Statistical Computing:
  • Simulation, bootstrap, jackknife, cross-validation.
  • Robust regression, GLMs, tree-based models.
  • EM algorithm, imputation, Bayesian modeling.
  • MCMC methods – Gibbs sampling, Metropolis-Hastings.
  • Neural Networks, association rules.

8. Data Science, AI & Machine Learning

• Supervised Learning: Linear regression, logistic regression, penalized regression, Naïve Bayes, SVM, Decision Trees, Random Forests, Gradient Boosting, AdaBoost.
• Unsupervised Learning: Clustering (k-means, k-medoids, hierarchical methods), validation indices.
• Deep Learning: RNN, CNN, NLP basics.
• Other Techniques: Bagging, stacking, ensembling, feature selection (RFE, VIF), hyperparameter tuning (Grid Search), cross-validation.

9. Database & Data Warehousing

• Databases: RDBMS concepts, normalization, SQL queries (joins, aggregation, updates).
• NoSQL Databases: Document-based, key-value, wide-column, graph databases.
• Data Warehousing: ETL processes, OLAP vs OLTP, star & snowflake schema.
• Big Data: Indexing, optimization, large-scale storage frameworks.

RBI Grade B 2025 Booklist

Phase I (Prelims)

1. Quantitative Aptitude
   • Quantitative Aptitude for Competitive Exams – R.S. Aggarwal
   • Fast Track Objective Arithmetic – Rajesh Verma
2. Reasoning Ability
   • A Modern Approach to Verbal & Non-Verbal Reasoning – R.S. Aggarwal
   • Analytical Reasoning – M.K. Pandey
3. English Language
   • Objective General English – S.P. Bakshi
   • Word Power Made Easy – Norman Lewis (for vocab)
4. General Awareness (GA / Current Affairs)
   • Manorama Yearbook (for static GK)
   • Monthly magazines like Pratiyogita Darpan or Banking Awareness – Arihant
   • Daily current affairs from reliable apps/websites (AffairsCloud, Gradeup, etc.)

Phase II (Mains)

Paper I – Economic & Social Issues (ESI)

• Indian Economy – Ramesh Singh
• Indian Economy: Performance and Policies – Uma Kapila
• NCERT (Class 11 & 12) Macroeconomics basics
• RBI official reports: Annual Report, Monetary Policy Report

Paper II – English (Writing Skills)

• Descriptive English – S.P. Bakshi & Richa Sharma
• Practice Essays & Precis from newspapers (The Hindu, Indian Express)

Paper III – Finance & Management

Finance

• Principles of Corporate Finance – Richard Brealey & Stewart Myers
• Indian Financial System – Bharati V. Pathak
• RBI’s Financial Stability Reports

Management

• Principles and Practices of Management – L.M. Prasad
• Organizational Behaviour – Stephen P. Robbins

Mock Tests & PYQs

• RBI Grade B Previous Year Question Papers (Phase I & II)
• Online mock test series (Oliveboard, PracticeMock, Testbook – whichever suits you)

RBI Grade B Previous Year Question Papers Sources to Download PYQs (Phase I & Phase II)

Disclaimer:

We do not promote or endorse any third-party website. The links to RBI Grade B Previous Year Papers are widely available online, and candidates can choose to download them at their own discretion. Always verify authenticity and ensure you are referring to the correct year and exam phase (Phase I or Phase II).