Saurabh Goyal

- Led the development of AI-powered pricing products, generating €2M+ revenue - Built cloud-native data pipelines (Google Cloud, BigTable, PySpark) to automate data processing. - Designed Ethereum-based Smart Contracts for Trade Finance automation, streamlining cross-border payments. - Pioneered IoT-driven products enabling usage-based payments for industrial clients. - Engaged executives & cross-functional teams, driving global digital transformation.

- Developed AI-based fraud detection models, saving €15M+ for global banking clients. - Automated financial crime investigations using Big Data, Machine Learning & ElasticSearch, cutting review time by 60%. - Consulted on digital transformation strategies, leading to 15%+ market penetration for an FMCG giant. -. Represented Deloitte at client sites across Europe & the USA, driving multimillion-dollar advisory engagements.

- Reduced online credit card fraud (HSBC) from 3.6% to 2.3% using AI & predictive modeling. - Developed AI-driven risk models (Munich Re) to forecast claims & optimize reinsurance policies. - Built Hadoop-based Big Data solutions for processing vast datasets, and enhancing actuarial analysis. - Won Best Performer & Innovation Awards for outstanding AI & digital risk management contributions.

Enhancing the shipping balance and provide with better shipping time estimation Roles and Responsibilities: • Analysis of Data, Discussed insights with Business. • Linear Regression Model to predict better shipping time. • Applied Poisson Distribution for better accuracy. Tools Used : R, Excel, Linear Regression Algorithm, Statistics

Roles and Responsibilities: • Analysis of Data, Understand Fraud Patterns in past. • Implemented Random Forest for credit card Fraud Detection. • Implemented Logistic Regression, multiple Iterations. • Stacking of RF & LR models for better accuracy. • Post Implementation , fraud rate came down from 3.6 % to 2.3%. Tools Used : SAS, R, Random Forest Algorithm, Logistic Regression Algo

Data in the form of .csv file was made available & copied to HDFS. Travelled to Munich to work with the Senior Actuaries at Munich Re. Roles and Responsibilities: • Data processing methods using PIG and then some Data queries using Hive. • Queries to perform basic exploratory analysis on the data available. • End objective was to study external factors which influenced the valuation and then did Risk Analysis. • Reports & Dashboard area generated using Tableau.

The Project Forecast Claims and Premiums Munich Re can expect from their clients. Travelled to Germany to understand Business and work closely with the Client Munich Re. Roles and Responsibilities: • Data Preparation. • Linear & Logistic Regression Model Designed using SAS. • Validated the Models.

Administration Tool to connect Munich Re and its Clients including the Agreement and Terms of use. Worked from Germany for the ease of understanding Business. Roles and Responsibilities: • Worked at Client location in Munich handling the Migration Test, Database Test. • Did User Acceptance Testing & Coordinating other teams. • Automation using Ranorex for Quality Assurance.

Product Management & Digital Transformation

- Engineering Mathematics - Computer Programming - Data Structure & Algorithms - Database Management System - Design & Analysis of Algorithms - Data Mining & Warehouse - Distributed System - Unix Network Programming