Credit Risk · AI-Based Underwriting · Strategic Leadership

Fifteen years of credit judgment, engineered into underwriting systems.

I'm a Chartered Accountant and credit risk leader who builds the thing most lenders only operate: scoring models, eligibility engines, and decisioning logic for MSME lending — designed for the API-and-alternative-data world of fintech.

Credit Appraisal MemoRef: AP-2026
ApplicantAmit Pujara, CA
Vintage15 yrs · credit underwriting
SegmentMSME lending
Proposed useFunctional expert, AI underwriting
Credit & policy judgment30%
Scoring model architecture25%
Alternative data — AA / GST / Bureau20%
BRE, API & platform fluency15%
Team & stakeholder leadership10%
Approved
Decision basis: demonstrated ability to design, document and implement end-to-end credit decisioning.
15 yrsCredit underwriting across HDFC, Kotak & YES Bank
+40%Unsecured loan portfolio growth led across Gujarat & MP
14Credit managers led and mentored as a regional team
CA + PL-300Chartered Accountant with Microsoft Power BI certification

What I build

A scoring model for India's hardest-to-read borrowers

Self-employed non-professional (SENP) businesses rarely have clean financial statements — but they leave rich digital footprints. I design scoring architecture that turns those footprints into defensible credit decisions for unsecured business loans in the ₹25L–₹1.5Cr range.

Track A · Statement-free

Digital-footprint scoring

  • Banking / Account Aggregator signals — balances, flow ratios, volatility, negative signals
  • GST behaviour — turnover trend, filing timeliness, GST-to-banking match
  • Bureau — score, enquiry intensity, obligations & FOIR
  • Business stability, promoter profile & data-consistency checks
Track B · Statement-backed

Financial-matrix escalation

  • Adds a full financial-statement pillar for lower-eligibility or offer-declined cases
  • Runs in parallel with Track A — same applicant, second lens
  • Recovers viable borrowers a single-track model would decline
  • Risk-sector overlays score to zero instead of hard-gating, preserving exception handling
// Eligibility engine — income estimation
Monthly_Income = MIN(GST_Turnover_12M, Banking_Credits_12M) × Industry_Margin% ÷ 12
// PMT-based max eligibility, then risk score caps by band (A→D)
Final_Eligibility = MIN(Max_Eligibility_PMT, Risk_Score_Cap)

Every parameter — from cashflow volatility bands to enquiry-intensity scoring — is documented with explicit rationale, so the model survives credit committee scrutiny, audit review, and regulator questions. That documentation discipline is the difference between a model that scores and a model that ships.

Decisioning systems & automation

  • Business Rule Engine (BRE) configuration and scorecard trigger design
  • Score model design end to end — pillar weights, parameter bands, swimlane caps and risk-based pricing logic
  • Credit policy and process design translated into executable decisioning — field lists, gate checks and stage-wise data flows across the loan origination journey

Platform & data fluency

  • Probe42 entity intelligence, Salesforce, Power BI (PL-300 certified)
  • Account Aggregator, GST and bureau data pipelines as underwriting inputs
  • Sector taxonomies and income-margin benchmarks for SENP segments

Experience

Fifteen years underwriting India's business borrowers

Fifteen years across the full MSME lending product suite — commercial vehicle loans, loan against property, working capital and business loans — from branch-desk underwriting to regional credit leadership. Every product added a layer of the judgment that now goes into the models.

06/2018 — Present

Regional Credit Manager

YES Bank · Ahmedabad

  • Designed scorecard triggers that cut early-stage delinquencies across the region
  • Proposed API upgrades to the underwriting stack to lift operational efficiency
  • Grew the unsecured loan portfolio ~40% across Gujarat & MP, consistently exceeding benchmarks in TAT, credit quality and profitability
  • Led a 14-member credit team; standardised onboarding with integrated policy and digital tools
  • Ran geo-level analytics and cost-of-credit evaluations feeding policy refinement
04/2015 — 05/2018

Senior Credit Manager

Kotak Mahindra Bank · Ahmedabad

  • Owned credit appraisal and decisioning for high-value unsecured business loans
  • Built early-warning and portfolio monitoring practice to flag deterioration pre-emptively
  • Strengthened credit governance — policy compliance, credit integrity, prudent judgment
09/2012 — 03/2015

Credit Manager

HDFC Bank · Gandhidham

  • Underwrote commercial-vehicle loans in the CTG credit team — the underwriting foundation
  • Balanced portfolio quality with growth across individual and small-business applicants
05/2011 — 09/2012

Audit Manager

Hitesh Thakkar & Associates · Ahmedabad

  • Statutory audit and verification — where the documentation discipline started

Credentials

Qualified, certified, and awarded along the way

Education

  • Chartered Accountant — ICAI, 2011
  • 21st All-India Rank — CPT, ICAI 2006
  • B.Com — Gujarat University, 2009

Certifications

  • PL-300 — Microsoft Power BI Data Analyst

Recognition

  • YES Bank — Yes Exemplar · Process Champion · Shining Star · SPOT ON · Long Service
  • HDFC Bank — Silver Star

Contact

Building AI-based underwriting? Let's talk.

I'm looking to bring fifteen years of credit judgment into a functional-expert role at a fintech building credit decisioning — model design, credit policy, or the bridge between risk and product teams. Open to relocating.

Ahmedabad, India