Blooma is a virtual CRE underwriting assistant that automates dull and tedious activities by combining artificial intelligence with comprehensive market data. The Blooma SaaS platform can therefore not only reduce loan origination time by around 80%, but also make the process more convenient – welcome to the 21st century! While the virtual assistant helps to extract, collect and analyze, final credit decisions always remain with the lender.
How does Blooma’s virtual underwriting assistant work?
Blooma’s virtual underwriting assistant helps with a variety of tasks, including document parsing, asset valuation, borrower financial analysis, asset and deal risk analysis, and real-time portfolio management. Lenders can set their own lending preferences and the assistant scores individual deals, as well as the entire portfolio, based on these preferences. Since the scoring system features full control and transparency, lenders can make rational decisions based on the scoring.
Blooma’s AI assists to extract information from documents, such as offering memoranda (OMs), borrower financial documents, profit and loss statements, or rent rolls.
The OM parser extracts the best property image, loan amount, loan term, loan type, borrower valuation, cash flow items, as well as unit mix and rent roll tables. Blooma uses the extracted information to collect market data and perform deal and asset analysis. After parsing detail about the property from an OM, the platform uses AI for an intelligent ranking of comparable assets.
AI also assists with financial documents, such as statements and tax returns. For example, the virtual assistant parses profit and loss statements and presents relevant market data from multiple vendors for comparison. Blooma’s AI continuously learns from customer data using federated learning and private AI. This way, every new deal contributes to making the product better.
Blooma is a virtual CRE underwriting assistant that automates dull and tedious activities by combining artificial intelligence with comprehensive market data.