Abhaya Jaiswal

Operations Associate

Bengaluru, Karnataka, India10 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Counterparty Credit Risk and Market Risk modeling.
Proficient in Machine Learning techniques for financial applications.
Strong background in statistical analysis and model validation.

Stackforce AI infers this person is a Fintech expert with strong capabilities in risk modeling and machine learning.

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Skills

Core Skills

Counterparty Credit RiskMarket RiskRisk ModelingMachine LearningBusiness AnalysisStatistical Analysis

Other Skills

Model DevelopmentModel ValidationMachine Learning TechniquesStatistical Data AnalysisPythonRegressionTime Series AnalysisFinancial Risk ManagementCredit RiskSAS ProgrammingAlgorithmsData MiningDeep LearningRMicrosoft Office

About

Work-Experience Summary - Counterparty Credit Risk - Market Risk - Stochastic Processes & Numerical Techniques - Derivatives Valuations - Regulatory Requirements - Model Development - Model Validation - Retail Credit Risk - Machine Learning Techniques Education - Financial Risk Manager (FRM) certification from GARP - Masters of Management - Data Science - IISc, Bangalore - B.Tech in Electrical & Electronics Engineering - NIT, Delhi Programming languages - Python, C++, R, SAS, SQL, Matlab Tools/Platforms - Github, Jenkins, RiskMetrics, Murex, EQF, Spectrum, Leversys, Bloomberg

Experience

10 yrs 6 mos

Total Experience

3 yrs 6 mos

Average Tenure

5 yrs

Current Experience

Ey

Manager

May 2021 – Present · 5 yrs · Bengaluru, Karnataka, India · On-site

Developed monitoring methodologies for CCR (IMM) and XVA use models, involving MC Sim models for risk factors, Pricing models and Aggregation/Netting/Collateralisation models.
Conducted validations of Counterparty Credit Risk models (PFE, CVA/DVA models) at netting set and firm level for un-margined and margined portfolios in EQ, FI and FX asset-classes.
Validated market risk models (Scenario Generation, VaR) for different payoffs in EQ, FI and FX classes.
Conducted validation of model for ‘PD for Commercial Obligors’ with its usage for Loan Loss Reserve calculation of Obligor Loans, Securities and Account Receivables as per IFRS9 standards, and Risk Adjusted Present Value (RAPV) calculation for Loans’ Fair Value.
Validated model for ‘Projection of Credit Spreads’ with its usage for Other Comprehensible Income (OCI) calculation on the Balance sheet, under the FRB Severely Adverse and CCAR Downside scenarios.
Worked on calibration of parameters of Local Volatility and Heston’s stochastic volatility model for pricing of options using the market data for vanilla-options and used the calibrated model to price exotics using Monte Carlo simulations.
Worked on implementing the market risk charge computation as per FRTB guidelines on its components: (i) Sensitivity based market risk charge under the SA method and, (ii) Expected Shortfall (tail-risk) based market risk charge under the IMA method, for a sample of trades in Equity asset class. Also, compared the risk charges obtained under SBA and ES.

Counterparty Credit RiskMarket RiskModel DevelopmentModel ValidationMachine Learning Techniques

Citi

Senior Analyst, Risk modeling (Regulatory)

Jan 2018 – May 2021 · 3 yrs 4 mos · Bangalore

Developed account level model for forecasting PD using a super panel structure of hazard rate, behavioral variables and macroeconomic drivers. Utilized an amortization curve to forecast the EAD and hence, the expected gross loss. Arrived at an empirical recovery curve to eventually forecast the net losses for the portfolio, for CCAR submission.
Designed an early loss recognition framework using a simpler regression on portfolio level aggregated data.
Conducted the stress v/s non-stress recent period backtesting and macroeconomic-sensitivity analysis during the development phase.
Built the analytical part of a smart alerting system for better wealth management by our clients. First use case being, sending alerts for retail-foreign exchange trading in Hong Kong. The key objectives were determining when to alert, which item(currency) to alert and what news feed to be alerted with.
Built a tool in python to standardize the feature engineering and model selection process for non-regulatory marketing models’s on bank’s customers’ data, to reduce the turn-around time of approval from model risk validators and its subsequent deployment.

Risk modelingStatistical Data AnalysisMachine LearningPython

The d. e. shaw group

Statistical Analyst-Intern

May 2017 – Jul 2017 · 2 mos · Hyderabad Area, India

-Conducted statistical analysis on Energy Commodities’ data, forecasting demand using Regression & Multivariate Time Series Analysis. Used Fourier Series Dummies to capture the bi-seasonality (weekly and monthly) in the daily collected data of natural gas consumption. Established a 14-day forecast horizon with changing prediction accuracy

Statistical AnalysisRegressionTime Series Analysis

Emirates technical associates-llc, abu dhabi

Construction Planning Engineer

May 2014 – Jul 2016 · 2 yrs 2 mos · Abu Dhabi, United Arab Emirates

The Project involved Engineering-Procurement-Construction of 33/11 kV electrical substations at Abu Dhabi Gas Industries Limited, Asab-site.
Arrived at a deterministic baseline planning schedule for the project with insights from design, procurement and commissioning teams.
Successfully charted the schedule for Tie-In/Interface of new and existing technical facilities in the brown field regions to match with the shutdown and maintenance schedule of the plant, after the electrical substation’s data analysis.