Building Credit Risk Models
This session is for aspiring and current data scientists working in the Fintech domain. Our speaker, Dhruv, has experience in building and deploying credit risk models that have had millions of dollars worth of decisions taken through them. The goal of this session will be to help you -
1. Understand the role of data science (and consequently, data scientists) in the lending industry.
2. Get hands-on experience with building real-world state-of-the-art credit risk models.
3. Appreciate the challenges of model explainability, interpretability, drift, and decay that real-world practitioners face.
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About the Speaker
Dhruv is a seasoned data scientist with a track record of delivering meaningful business value by ideating, building, and deploying models at scale. He started his career as an investment banking analyst, where he built quantitative models to help asset managers trade billions of dollars worth of financial instruments efficiently. Most recently, he was a Director and founding member for data science and risk at Protium, a fintech startup enabling SMEs in India to access low-cost credit. Protium has built an AUM of ~200mn USD in 2 years through data and model-driven decision making.
Dhruv has a bachelor's and master's in Electrical Engineering from IIT Bombay. He likes to listen to podcasts, write on his blog and bake in his spare time.
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This session is a collaborative event by DPhi and Databuzz.
Databuzz is a volunteer-driven community of AI and Tech enthusiasts working on a mission to help Aspiring Data Scientists/Data Analysts/Business Analysts/Technology Analysts pivot in this field. It's co-founded by Jatindeep Singh and Supreet Kaur, one of DPhi's past guest speakers and a VP at Morgan Stanley.
DPhi is a global community of AI enthusiasts from 150+ countries. We started with the vision to make AI education accessible to everyone and build AI for good to solve key challenges of humanity. As part of our community initiatives, we provide free AI and data science courses by industry experts from large tech companies or startups worldwide.