Focus is to work on all the asset classes such multifamily, retail, storage, Industrial etc. loans originated by the Insurance. The Candidate would be supporting on the different workflows as mentioned below:
Agency Pre-screening and ICM: Screening/underwriting of Agency Loans (Fannie Mae), deriving Underwriting Value, using financial spreading, rent roll analysis and creation of Investment Committee Memo.
Non-Agency/Deal Pre-screening and ICM: Screening/underwriting of Non-Agency Loans, deriving Underwriting Value, using financial spreading, rent roll analysis and creation of ICM.
Loan Portfolio Stratification and ICM: Stratification of portfolio of loans belonging to various asset classes, assessing their risk exposure using their property level, loan level and performance metrices.
Draw Review Process: Reviewing draw related Invoices, Proof of Payments, Construction Budget, TI/LC, etc. and updating the Draw Review Trackers accordingly.
On Boarding the delas on AI Based platform with the help of various closing documents, Offering Memorandum, Loan Agreement etc.
While the initial function will be to take direction from the Origination team members, the aspirational goal is to expand the Wipro scope to include the following:
Extracting market and asset specific statistics from various data sources (for eg: CoStar or similar platforms) for the pipeline deals which are shortlisted for screening or underwriting.
Comparing the key deal metrics which includes Occupancy, Cap Rates, Debt Yield, Cash Flow, NOI etc. of the pipeline deals with existing portfolio.
Analyzing property pictures & map for location-based insights, preparing the capital stack (i.e., Equity vs. Debt) and presenting them in an excel and ppt format.
Collecting and preparing sales and rent comparable of the target originations with the market data sourced through broker reports or web-based applications.
Studying the demographics to understand the unit mixes, interpreting all sources of incomes & expenses through review of cash flows, ascertaining vacancy rates & rental income using rent rolls and using NOI to calculate key liquidity ratios i.e., DSCR, DY etc.
Creating investment memorandums with the deal team ahead of investment committee.
Conducting due diligence prior to closing of deal as per closing checklist.
Data input in pipeline tool (i.e., DealPath, Loan Tapes) as and when required
Essential Skills & Experience:
Must have a good knowledge of US Real Estate Industry and Market in underwriting the CML/CRE loans across all the sectors; along with hand on experience in underwriting the Multifamily agency (Freddie & Fannie) loans.
Should be aware of the US taxes for different States and Counties; along with knowledge of various rent/sales comparable to be used in accordance with subject properties.
Must be well versed with concepts of Cap Rate/Index rate/ LTC/LTV/Spreads/Cap Stack, Implied vs Cash Equity and various loan specific terminologies. In addition, should know the implications and effect of UW In-place and Mark to Market assumptions using property financials and its demographics through broker provided offering memorandum.
Candidate should have the knowledge of US Market and Sub-Market to understand the deal’s demographics and its impact on the subject property.
Hand on experience and proficient in preparing the dynamic financial models in MS excel.
Master’s degree – Major in Finance or Banking and Capital Markets, CFA designation a plus.
Exceptional quantitative aptitude and skill set with a mastery of Microsoft Office applications.
Ability to manage multiple priorities in a fast paced, fluid environment.
Previous background with real estate lending required with Debt Underwriting’ in real estate preferable.
Rigorous analytical mindset with a high level of intellectual curiosity and excellent problem-solving skills.
Acute focus on attention to detail, accuracy, and data validation.
Effective communication skills (listening, verbal, and written).
Excellent interpersonal and teamwork skills.
Sound judgment and discretion.
Strong initiative, energy and confidence completing assignments with limited supervision
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