Statistics for Risk Modeling (SRM) - All English

Statistics for Risk Modeling (SRM) – All English

₹22,100.00

SRM – Statistics for Risk Modeling  – Regular Lectures
Faculty: Shivangee Agarwal & Gaurav Patwary
Course Duration: 100+ hours

Category:

SOA Exam SRM – Statistics for Risk Modeling

Develop Expertise in Statistical Learning, Predictive Modelling and Data-Driven Risk Analysis

Exam SRM – Statistics for Risk Modeling is an actuarial examination conducted by the Society of Actuaries (SOA), USA, and forms part of the pathway towards the Associate of the Society of Actuaries (ASA) designation.

The examination focuses on applying statistical methods and predictive modelling techniques to analyse data, identify patterns, forecast outcomes and evaluate uncertainty.

Exam SRM covers regression analysis, statistical learning, time series models, decision trees, principal component analysis, clustering and model validation, developing essential analytical skills for actuarial science, insurance and financial risk management.

The subject builds upon fundamental concepts of probability and mathematical statistics, connecting statistical theory with practical applications in predictive analytics and risk modelling.

Course Structure & Syllabus

Exam SRM combines statistical learning principles with practical applications in actuarial modelling, predictive analytics and data analysis.

Key Topics Covered:

  1. Fundamentals of Statistical Learning:
    Supervised and unsupervised learning, regression and classification, bias-variance trade-off, overfitting, training and testing datasets.
  2. Linear Regression Models:
    Simple and multiple linear regression, least squares estimation, hypothesis testing, confidence intervals, residual analysis and interpretation of regression coefficients.
  3. Model Selection & Validation:
    Cross-validation, variable selection, regularisation techniques, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and model performance evaluation.
  4. Time Series Analysis:
    Stationarity, autocorrelation, random walks, autoregressive models, exponential smoothing, volatility models and statistical forecasting.
  5. Decision Trees & Ensemble Methods:
    Classification and regression trees, recursive partitioning, pruning, bagging, random forests and boosting.
  6. Principal Component Analysis (PCA):
    Dimensionality reduction, principal components, eigenvalues, eigenvectors and interpretation of variation in datasets.
  7. Cluster Analysis & Unsupervised Learning:
    K-means clustering, hierarchical clustering, distance measures, cluster identification and interpretation of grouped data.

The Exam SRM syllabus focuses on statistical modelling, predictive analytics, regression analysis, model selection and quantitative risk assessment.

Syllabus Topics & Weightages

The SOA Exam SRM syllabus comprises five principal areas:

Topic Approximate Weightage
Basics of Statistical Learning 5–10%
Linear Models 40–50%
Time Series Models 10–15%
Decision Trees 20–25%
Unsupervised Learning (PCA & Clustering) 10–15%

Topic weightages are indicative ranges rather than fixed percentages. Actual question distribution may vary between examination sittings.

Examination Structure

Exam SRM is a computer-based multiple-choice examination assessing statistical learning concepts and their applications in data analysis and risk modelling.

Particulars Details
Examination SOA Exam SRM – Statistics for Risk Modeling
Conducting Body Society of Actuaries (SOA)
Examination Format Multiple-Choice Questions
Total Questions 35
Examination Duration 3 Hours 30 Minutes
Examination Mode Computer-Based Testing (CBT)
Examination Centre Authorised Prometric Test Centres
Negative Marking No
Exam Months January, May and September

Important Examination Guidelines

  • Multiple-Choice Examination:
    Candidates must solve 35 statistical modelling questions within 3 hours and 30 minutes.
  • Conceptual & Analytical Applications:
    Questions assess the selection, application and interpretation of statistical models, with emphasis on understanding modelling techniques.
  • Regression & Predictive Models:
    Candidates must understand model assumptions, parameter estimation, validation and interpretation of results.
  • Calculators:
    Only calculators approved under SOA examination rules are permitted.
  • Reference Material:
    Statistical tables and other examination-specific reference information are provided where applicable under SOA guidelines.
  • Examination Booking:
    Candidates must register through the SOA and schedule their examination within the applicable testing window.
  • Examination Conduct:
    Candidates must comply with SOA and Prometric identification, security and examination regulations.

Eligibility Criteria

Exam SRM is suitable for actuarial students developing their knowledge of statistical learning and predictive modelling.

  • No prior actuarial examination pass is required solely to register for Exam SRM.
  • A strong understanding of SOA Exam P – Probability concepts is recommended.
  • Knowledge of calculus and mathematical statistics, including the material covered in VEE Mathematical Statistics, is assumed.
  • Students from Mathematics, Statistics, Data Science, Economics, Finance, Engineering and other quantitative backgrounds may prepare for the examination.
  • Candidates must meet SOA’s applicable registration, identification and examination entry requirements.

Learning Objectives

Studying Exam SRM develops the ability to:

  • Understand supervised and unsupervised statistical learning methods.
  • Apply simple and multiple linear regression techniques.
  • Evaluate statistical model assumptions and limitations.
  • Select appropriate models using validation and model selection techniques.
  • Analyse and forecast time series data.
  • Understand decision trees and ensemble learning methods.
  • Apply principal component analysis for dimensionality reduction.
  • Use clustering techniques to identify patterns in data.
  • Develop statistical reasoning and predictive risk modelling skills.

Practical Applications of Exam SRM

The knowledge gained in Exam SRM is applicable across several actuarial, financial and analytical disciplines:

  1. General Insurance:
    Analysing claims experience, identifying risk characteristics, developing predictive models and supporting insurance pricing decisions.
  2. Life & Health Insurance:
    Modelling mortality and morbidity experience, analysing policyholder behaviour and identifying risk factors.
  3. Banking & Financial Risk Management:
    Analysing financial data, forecasting trends and evaluating quantitative risk exposures.
  4. Data Science & Predictive Analytics:
    Applying regression, classification, decision trees and clustering to analyse complex datasets.
  5. Enterprise Risk Management:
    Developing predictive models, evaluating business risks and supporting data-driven decision-making.

Exam SRM establishes essential statistical learning knowledge that supports more advanced actuarial studies, particularly SOA Exam PA – Predictive Analytics, which develops the practical application and communication of predictive modelling techniques.

Technical Requirements – AEI Learning Application

To access online classes, recorded lectures and digital study resources, students must ensure their devices meet the following minimum technical requirements of the Actuators Educational Institute (AEI) Learning Application.

Device / Platform Minimum Requirement
Android Android 9.0 or above
Windows PC / Laptop Windows 10 or above
iPhone / iPad (iOS) iOS 12.0 or above
MacBook / iMac (macOS) Apple M1 chip or above with macOS 14 or later
WHAT YOU WILL GET

Course Deliverables

gold medal
Recorded lectures
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Live Discussion & Practice Sessions
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Softcopy of AEI Own Study Materials
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Access to Student Dashboard
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Technical Support
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Chapter Wise MCQ Bank
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Course Extension (2 More Terms)
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Interactive Q&A Forum

Mukti BanganiCleared
Harshvardhan VijayCleared
Khushi GargCleared

FACULTY

Meet The Instructor


Shivangee Agarwal is a globally qualified actuary holding the prestigious credentials of FIA (UK), FIAI (India) and FSA (USA), along with the C.Act designation, giving her professional recognition across three of the world’s leading actuarial bodies. She is also IFRI Certified, holds a Master’s in Data and Business Analytics from IIM Indore, and completed her B.Com (Hons. in Finance) from St. Xavier’s College, Kolkata. She secured All India Rank 1 in CT7 – Business Economics, reflecting her strong academic foundation in actuarial science, finance and analytics.

With over 10 years of teaching experience, she has taught and mentored 5,000+ students across Actuarial Science, Data Analytics and Finance. At Actuators Educational Institute, she teaches the Paper B components of CM subjects, along with CS2, CB2, CP2, CP3 and FRM, and also conducts training in Excel, VBA, SQL and R Programming. She has delivered workshops and academic sessions at institutions including SRCC, Lady Shri Ram College, St. Xavier’s College, Mithibai College, IIM Indore and IBS Hyderabad, combining deep technical expertise with a practical, structured and exam-focused teaching approach.

Gaurav Kumar Patwary is a risk management professional with nearly four years of experience in Model Risk Management, working with quantitative finance-based models used within the Asset Management division of a multinational bank. He holds a Bachelor’s degree in Economics from St. Xavier’s College, Kolkata and a Master’s degree in Economics from the Delhi School of Economics, and has cleared 9 out of 13 actuarial papers from the IAI.

With a strong foundation in statistics, economics and finance, Gaurav also brings hands-on experience in Python, using it to test and challenge different aspects of financial models. At Actuators Educational Institute, his teaching approach focuses on conceptual clarity, analytical thinking and practical application, helping students connect theoretical concepts with real-world quantitative and risk-management perspectives.

PLAYLIST

Demo Class Videos


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