Abhinav Goel, Sr. Manager, Advisory Services, EY

Abhinav is a Sr. Manager in EY’s Data & Analytics practice with 11 years of experience in the financial services industry and management consulting. He is experienced in building analytics solution for monitoring for Internal Audit and Compliance (e.g. IA analytics, FA behavior analysis, compliance monitoring & supervision, client segmentation, and strategic targeting for Banking & Wealth and Asset Management institutions. Abhinav is proficient in designing tech-strategy & architecture, spearheading business & technical teams and managing key stakeholders. He holds an MBA in Finance from Baruch College and a Engineering in Computer Science from India.

Managed delivery of advanced analytics solutions, including hypothesis generation, model implementation, systems integration and insights generation.

  • US Wealth Manager: Designed AI solution to process voice transcripts data to identify prohibitive advisor behavior -  unapproved advise, missed disclosures
  • Global Commercial Bank: Setup Operating model and Framework for Internal Audit. Performed DA tech assessment and led automation for KYC/ AML controls
  • US Private Bank: Implemented a machine learning models to classify False/ True Positive portfolio return outliers. Created automation pipeline to identify data issues
  • US Wealth Manager: Designed AI enabled virtual assistant to aid in compliance review process by process automation and performing reviews for regulatory and company specific branding & marketing guidelines
  • Global Insurance Provider: Developed machine learning solution to measure underwriting risk and price guaranteed Workers Comp. insurance. Created analytical model to isolate fraudulent medical provider claims. Engineered several fraud detection approaches to identify linkages between claimants, doctors and attorneys associated with the fraudulent claims. Created top-of-the-funnel tool intended to generate new business leads and aide in strategic planning while evaluating companies across product lines
  • Major US Investment Bank: Developed NLP driven technical solution for classifying marketing documents on DOL Fiduciary Rule Non-compliance. Implemented advanced techniques like Word Embedding, NER and Topic Modeling). Implemented document pre-processing using key NLP functions (tokenization, reg-ex etc.)

Technical Skills

  • Programming: Python (NumPy, Pandas, Scikit-learn, NLTK, SpaCy, Stanford CoreNLP)
  • Specialties:
    • Machine Learning –  Unsupervised and Supervised Modeling
    • NLP – Named entity recognition (NER), Dependency parsing, Word Embedding