Shikha Pathak

Business Analyst

Bengaluru, Karnataka, India4 yrs 2 mos experience

Key Highlights

Gold Medalist in Data Science Master's program.
Achieved 21% reduction in overdue loans through risk analysis.
Expert in Python, SQL, and Machine Learning for data insights.

Stackforce AI infers this person is a Fintech professional specializing in Credit Risk Analytics and Data Management.

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Skills

Core Skills

Risk AnalyticsCredit Risk Management

Other Skills

Risk ConsultingMetaBasedbtData AnalysisData ExtractionAutomationDashboard CreationSnowflakeSQLOrganizational ConsultingEvent ManagementTeam ManagementHexMicrosoft OfficeFinacle

About

As a Credit Risk Analyst, I bring a strong foundation in Python, Tableau, SQL, Excel and Machine Learning to the table. I am passionate about data exploration and love nothing more than digging into data sets to uncover valuable insights and create meaningful statistical models. My expertise in these tools and my eagerness to constantly learn and grow in the field make me a valuable asset to any team. Let's connect and explore opportunities to utilize my skills and drive impactful results together.

Experience

4 yrs 2 mos

Total Experience

1 yr 6 mos

Average Tenure

1 yr 1 mo

Current Experience

Atob

Risk Analyst

Apr 2025 – Present · 1 yr 1 mo · Bengaluru, Karnataka, India

Risk ConsultingMetaBaseRisk Analytics

Khatabook

2 roles

Business Analyst

Sep 2023 – Mar 2025 · 1 yr 6 mos · Bengaluru, Karnataka, India · On-site

Working with the Head of Risk and various stakeholders from Collection, Product, Finance, and Underwriting to monitor and oversee the portfolio and risk management processes.
Analysed end-to-end risk migration ratings having high bad rates and discontinued them for fresh BREs on account of extremely poor performance. This change resulted in a 21 % decrease in coincidental 30+ days past due loans over time, with a minimal 7% reduction in approval rates.
Conducted an analysis of the impact of more than 2 bounced payments on renewal loans, leading to the identification and removal of 30% of bad loans. This adjustment incurred a minimal 10% reduction in the approval rate for renewals.
Extracted data from the credit bureau to analyze customers who defaulted on loans outside Khatabook, creating a list of potential defaulters. Also identified individuals who defaulted in Khatabook but made payments externally, preparing a separate list of such cases and coordinated with the collection team to prioritize and emphasize efforts on these specific cases.
Automated various portfolio, loan level reports, and created lender level dashboard for finance team for easier consolidation with various lenders.

Credit Risk Managementdbt