Streamline Your Underwriting Workflow with AI

Underwriting is everything in commercial real estate (CRE). It’s where risk is assessed and managed. Underwriters look at credit history, financials, property value, and market data to approve and price loan applications. 

Underwriting faster and more accurately means CRE deals close faster and more profitably for lenders and borrowers.

According to a Deloitte report, AI can cut insurance and loan underwriting costs significantly and sustainably increase accuracy and consistency. 

Here we look at how AI tools like Blooma are changing underwriting, workflows, human error, and decision-making in CRE.

What is an Underwriting Workflow?

Commercial real estate underwriting is a process lenders and insurance companies use to assess risk on loan applications and insurance policies. It’s a systematic way of looking at everything about an applicant—financials, property value, market data—before a decision is made. Here are the steps in the underwriting workflow:

1. Application Submission: The borrower submits the loan application, or the insurance applicant completes the insurance application. This includes tax returns, financials, credit reports, and property or insurance risk details.
2. Initial Review: Underwriters review the application to ensure it is complete and all documents are present. They also check for any obvious mistakes or missing bits that will affect the decision.

3. Data Collection and Verification: Underwriters look at credit history, credit score, financials, debt-to-income ratio (DTI), and all financials. For insurance policies, that’s medical history and previous claims.
4. Risk Assessment: Underwriters assess risk. That includes the applicant’s financial risk, the value and condition of the property, market data, and all that. For insurance, that’s a risk on the applicant’s risk profile.

5. Decision Making: Underwriters make the underwriting decision based on the information provided. This could include approval, denial, or adjusting loan terms or insurance policies. Credit score, credit history, interest rates, and overall financial health matter at this stage.
6. Final Review and Approval: The underwriting department conducts a final review to ensure that all underwriting guidelines and protocols are followed. For mortgage loan underwriting, this may involve coordination beyond the policyholders to loan officers, insurance agents, and other parties to close the application process.
7. Communication and Documentation: The decision is communicated to the borrower or policy applicant, along with any conditions or requirements that need to be met. Detailed paperwork is prepared to document the terms of the loan or policy so everyone knows their responsibilities and rights.

Challenges in Traditional Underwriting Workflows

Traditional underwriting workflows are thorough but have several challenges that hinder efficiency and accuracy in CRE transactions. Here are some of them:

1. Manual Data Entry: One of the biggest challenges with traditional underwriting is manual data entry. Underwriters have to enter tons of financial information, credit reports, and other critical data into different systems. This manual process is time-consuming and prone to errors which can lead to inaccurate assessments and decisions.
2. Slow Decisions: The traditional underwriting process is slow and can take days or even weeks to complete. Each stage, from initial review to final approval, involves multiple steps and stakeholders, which can cause delays. Slow decision-making is particularly inconvenient in a fast-paced market where timing is everything to secure deals and investments.
3. Human Error: Human error is a risk in traditional underwriting workflows. Mistakes in data entry, misinterpretation of financial information, and overlooking critical details can all lead to incorrect risk assessments and decisions. These errors can cost lenders and investors money and erode trust in the underwriting process.
4. Data Silos: Traditional underwriting involves working with multiple data sources that are not integrated. This lack of integration creates data silos, which make it hard to get a complete view of an applicant’s financial situation and risk profile. Data silos can lead to incomplete or fragmented information, which hampers risk assessments.

These challenges can impact deal timelines and investment outcomes with:

• Delayed Loan Approvals: Slow decisions can delay loan approvals cause deals to fall through, and result in lost opportunities for both lenders and borrowers.
• Inaccurate Risk Assessments: Human error and incomplete data can lead to inaccurate risk assessments, poor investment decisions, and financial losses.
• Inefficiency: Handling large volumes of applications can reduce the overall productivity of underwriting departments and limit their ability to scale.
• Compliance Risks: Difficulty in adapting to regulatory changes can expose lenders and investors to compliance risks, fines, and legal challenges.

The Revolution of AI in Underwriting Workflows

Artificial Intelligence (AI) is changing the underwriting game in CRE, and it’s big. AI solutions make underwriting faster, more consistent, and more intelligent. AI can handle data complexity, automate boring tasks, and give you real-time answers.

1. Machine Learning Models for Risk: Machine learning models are the lead AI application in underwriting. They analyze large amounts of historical data to find patterns and predict the future. 
2. Natural Language Processing (NLP) for Document Analysis: NLP is another AI technology that is changing underwriting by automating unstructured data analysis—documents and text. For example, it can scan and read tax returns, financial statements, and credit reports in seconds. 
3. Real-time Data Analytics: AI provides real-time analytics so underwriters have the latest information to make decisions. AI systems monitor market conditions, interest rates, and economic factors to see how they affect CRE investments.
4. Automation of Boring Tasks: AI automation performs mundane tasks so underwriters can focus on the complex stuff. This includes entering and validating data from multiple sources.

What are the benefits of this?

• Speed: AI processes huge amounts of data fast – underwriting decisions take less time.
• Accuracy: Minimizes human error and maximizes predictive analytics, risk assessment, and decisions.
• Scalability: AI systems handle applications by the dozen – underwriting departments can scale without sacrificing quality.
• Cost Efficiency: Automating boring tasks reduces operational costs, and underwriters can focus on value-added tasks, increasing profitability.

Blooma: Enhancing Underwriting Workflows with Technology

Blooma is an innovative solution that uses AI to change and improve the underwriting process in commercial real estate. Here’s how Blooma works to underwrite best.

1. Data Auto-Population: Blooma automatically gets the data it needs from all the places it needs to. Financials, credit reports, market data—everything an underwriter needs to see. This includes live data from providers for underwriters to trust. 

2. Risk Models: Machine learning models. Blooma uses them to calculate risk like never before. Historical data, credit scores, financials—all the metrics underwriters need to know to determine whether someone will repay a loan.
3. Predictive Analytics: Blooma’s models predict what’s going to happen next and what the market will look like. That means underwriters can decide and manage risk ahead of time.
4. Live Risk Monitoring: Blooma monitors risk throughout the underwriting process. Live means underwriters can see and respond to problems as they happen in the workflow.

Benefits of an AI-Enhanced Underwriting Workflow

Using AI underwriting with Blooma means all of the following key takeaways and benefits for your workflow.

Faster Processing

Automation means Blooma gets to the data and analyzes it fast. That means faster application evaluation and decision-making and no more data entry delays for verification.

Increased Accuracy in Risk Assessment

Blooma uses machine learning to assess risk profiles more accurately. This means underwriters can make better decisions and reduce defaults and losses. Automation eliminates data entry and document analysis errors, so underwriting outcomes are more reliable. This is critical for the integrity of the underwriting process and fairness.

Compliance Tracking

Blooma’s AI-powered workflow includes automated compliance checks to ensure all documents and processes comply with regulations. This makes the compliance verification process easier and reduces the risk of non-compliance.

More Loan Options and Better Customer Service

By speeding up processing and increasing accuracy, Blooma lets lenders offer more competitive loan products. Faster decisions and reliable risk assessments mean better terms and conditions, making the lender the go-to choice for borrowers.

Implementing Blooma in Your Current Operations

Integrating Blooma into your current underwriting will boost efficiency and accuracy for your CRE lending. Below is a step-by-step guide to getting started with Blooma, plus information on training and support to get you up and running quickly and start seeing benefits straight away.

Step 1: Review Current Underwriting

Start by reviewing your current underwriting workflows. What are the pain points and inefficiencies, and where can automation and AI add the most value? 

Create a detailed diagram of your current underwriting process from application intake to final decision. Think about what KPIs you want to improve with Blooma, e.g. processing time, accuracy, and compliance rates.

Step 2: Define Integration Objectives

What do you want to achieve by integrating Blooma into your business? This could include:

• Efficiency: Reduce processing time and streamline workflows.
• Risk: Improve risk assessment and mitigation.
• Compliance: Ensure regulatory compliance.

Step 3: Integration Planning

Make sure to plan the Blooma integration into your underwriting. This includes looking into the timeline for integration, such as key dates and milestones, who’s doing what, and the required resources.

Step 4: Make Blooma Your Own

Work with our implementation team to customize the platform—from business needs to underwriting rules—and integrate it with your current data sources and financial systems.

Step 5: Get Your Team Trained

Train your underwriters thoroughly on Blooma’s features and functions. 

This can include onboarding sessions with our team, training sessions when needed, and unlimited access to learning resources forever.

Step 6: Monitor and Refine

Monitor your new underwriting workflow with Blooma to achieve your goals. Track important KPIs like processing time, accuracy, and compliance regularly.

Also, set up a feedback loop. Get feedback from your team and refine your processes on that basis. 

Step 7: Training and Support

Leverage training and support to get you settled and make the most of the platform – dedicated to you. You can also check out our user guides, tutorials, and FAQs to help your team. 

Blooma also offers customer success managers (CSMs) to support you personally and integrate your business with your goals.

Preparing for the Future of Underwriting in CRE

The commercial real estate industry is changing fast, and underwriting processes are changing, too. To win and be efficient, CRE professionals need to be ready for the future of underwriting. Here are the emerging trends in underwriting technology and how to stay ahead of the game.

1. Artificial Intelligence (AI) & Machine Learning (ML): AI and ML are making underwriting data analysis, risk management, and decision-making easier. AI can forecast market and borrower behavior making underwriting more informed.
   
2. Blockchain Technology: Blockchain is going to change data security and transparency in underwriting. Decentralized ledger technology means all transactions and data are secure and immutable, reducing fraud and increasing trust in underwriting.
   
3. Internet of Things (IoT): IoT devices collect real-time data on properties so underwriters have property condition, usage, and risk data. IoT sensors can monitor a property’s temperature, humidity, and occupancy so risk can be managed proactively.
   
4. Advanced Data Analytics: Advanced data analytics tools are increasingly being used in underwriting to process and interpret large datasets and find hidden patterns.

How can you be ahead of the game?

• Professionals have to keep learning and be trained. That means knowing about new tools, methods, and best practices in underwriting. 
• Be forward-thinking and try new things, and you’ll win. Test new technology and see what it means to underwrite.
• Partner with technology providers like Blooma to get the latest solutions into your underwriting workflow. 
• Use integration services from technology partners to add new tools to your existing system.

Transform Your CRE Deals with Blooma

In the world of CRE, modernizing underwriting workflows with AI is no longer a nice thing but a must. Traditional underwriting processes, which involve manual data entry, long decision times, and a high risk of human error, are being disrupted by AI-driven solutions. This is key to faster, more accurate, and more profitable CRE transactions. 

Blooma is leading the way with a platform that puts AI at the heart of underwriting.

Blooma uses AI to touch every part of the underwriting process, from data gathering to loan approval. Its platform has a range of features to streamline workflows and decision-making.

Get started with Blooma’s AI-driven platform and transform your CRE deals, get more efficiency, accuracy and profitability. 

Book a demo with our team today and join the future of underwriting with Blooma to get the most out of your CRE deals.