The Best Ever CRE Show JF2759: Improve Your Underwriting With These Data Science Tips ft. Nelson Lin
Mar 23, 2022
Nelson Lin, a multifamily syndicator and data scientist, shares his expertise in analyzing real estate data. He discusses the importance of creating a comprehensive database to uncover value-add opportunities and optimize rent pricing. Nelson explains how machine learning can enhance asset management and risk assessment in real estate. He also emphasizes the need for flexibility in deal structuring and the value of understanding micro-market trends for smarter investment strategies. Tune in for practical data science tips that can elevate your underwriting game!
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Use Data for Expense Benchmarks
- Accumulate and analyze a large sample of offer memoranda to find expense averages and outliers.
- Use this data to identify value-add opportunities, like fixing leaks or inefficient utilities, before visiting a property.
Build Rent Estimates with Statistics
- Gather a statistically significant number of rental comps to determine rent estimates conservatively.
- Use rent ranges like the 25th, 50th, and 75th percentiles to create best, average, and conservative revenue cases.
Combine Rent Data Sources
- Use multiple data sources like rentometer and active rental listings to understand both historical and current rental market conditions.
- Analyze neighborhood-level rent variations and amenities to predict rent growth and plan renovations effectively.
