Om Pawar

Credit risk analyst across consumer, retail, and mortgage lending, specialising in scorecard development, credit strategy, and portfolio performance. Led scorecard and strategy development on acquisition portfolios exceeding £1B in annual lending - segmentation, cut-off calibration, reject inference, and risk monitoring - balancing approval rates, risk appetite, and profitability. Built credit policies, scorecards, decisioning strategies, and portfolio forecasts using statistical and machine learning techniques in Python, SQL, and SAS, leading a small team of analysts to drive lending decisions.

Advanced

Excel user for financial modelling, with Tableau and PowerBI for reporting.

Certified Financial Risk

Manager with an MBA from ESCP Europe and a Computer Engineering background. Full right to work in the UK.

Senior Portfolio Analyst - Property at Aldermore Bank (2025-08 – 2026-08)

• Application funnel: Mapped the full application journey from DIP to completion, quantifying drop-offs and diagnosing lost lending opportunity at each stage; presented findings that supported a 4-5pp approval-rate improvement and identified £100M+ incremental lending.
• LTV/LTI forecasting: Built forward-looking LTV and LTI forecast models projecting portfolio positioning and mix to support portfolio planning and regulatory flow-limit management.
• Strategy monitoring: Ran multiple decisioning workstreams end-to-end - real-time drop-off tracking (SAS/SQL + PowerBI), periodic rule evaluation, and rule-firing accuracy checks between SAS logic and technology implementation.
• Pipeline automation: Built and automated analytical and reporting pipelines in SAS and PowerBI, cutting manual reporting effort ~30%.
• Affordability review: Assessed essential-expenditure components and impact of heightened inflation expectations on acquisition and existing portfolio.
• Customer segmentation: Profiled enquiry-stage customers against market data to identify high-income segments and inform lending criteria.

Lead System Analyst, Credit Risk at VodafoneThree (2024-04 – 2025-07)

• Strategy build & testing: Built, configured, and regression-tested credit decisioning strategies, rules, and offer logic in Experian PowerCurve, ensuring accurate, error-free deployment of strategy changes.
• Data onboarding & modelling: Onboarded Experian CrossCore fraud and identity data into the SAS warehouse, designing the schema, logical data model, and source-to-target field mappings, with data dictionaries for downstream analysis.
• Process automation: Re-engineered the weekly CAIS/CAF bureau reporting process as an automated Python ETL pipeline, replacing standalone SAS jobs, resolving file-generation errors, and adding data quality checks for reliable submissions.

Manager, Risk Analytics at Home Credit (2023-04 – 2023-12)

• Credit Strategy: Led acquisition credit strategy on a £1B book, analysing delinquency, vintages, and roll rates to drive cut-off, policy, and credit limit changes that balanced approval rates, risk, and profitability.
• Team development: Managed, trained, and mentored a team of analysts, building capability across scorecard development, data pipelines, and MI/KPI reporting.

Assistant Manager, Credit Risk at Home Credit (2020-06 – 2023-03)

• Scorecard development: Built unified acquisition scorecards combining application, behavioural, bureau, and alternative data - logistic regression per pillar with a GLM ensemble, tuning WoE binning, weights, and parameters - reducing portfolio risk by 13%; owned testing, deployment, and Gini/PSI monitoring.
• Policy optimisation & reject inference: Designed a two-stage decisioning framework (hard rules, then scorecard strategy); optimised hard rules through staged A/B tests and reject inference (random holdout, override tracking, bureau comparison), unlocking a new medium-risk, higher-return segment.
• Merchant scorecard: Developed a star-rating scorecard for 50,000 point-of-sale partners (logistic regression on binned sales and risk variables), powering a risk-based incentive framework rolled out nationally that drove a 5% revenue uplift.
• Credit limit management: Designed automated credit limit strategy by risk, segment, and product, using bureau-imputed income to increase assessable income coverage 3x.
• Alternative-data scoring: Led credit-risk scoring for an alternative-data programme (device, telco, payments, geospatial), integrating partner scores as GLM pillars; contributed to an 18% increase in average credit limit while holding risk within appetite.
• Decisioning automation: Assessed risk and portfolio impact of moving the acquisition book to near-full straight-through processing.

Graduate Analyst - Risk at Home Credit (2019-06 – 2020-05)

• Bank validation: Built a fuzzy-name matching algorithm (character-distance, phonetic, tokenisation) for penny-drop account validation at origination, cutting direct-debit failures by 70% and initial defaults by 40%.
• Geospatial modelling: Developed geospatial risk pillar using KNN with imputation on point-of-sale to applicant distance, identifying fraud hotspots for geo-fencing.

Technology Analyst, Production Services at Nomura (2014-07 – 2016-07)

• Production support: Supported mission-critical back and middle-office trade, settlement, and reconciliation systems, improving availability through root-cause analysis and long-term fixes.

MBA in International Management – ESCP Business School (2019)

BE in Computer Engineering – University of Pune (2014)