Many underwriting teams struggle with slow reviews, manual data entry, and fragmented systems.
Processing times can stretch from minutes to hours, and important details often get lost when files move between inboxes and platforms.
For funders and brokers, these pain points create delays, missed opportunities, and weaker client relationships.
The good news is that underwriting does not have to work this way. In this article, we'll discuss four strategies that can help you move towards ideal underwriting efficiency.
How Does Underwriting Work?
Underwriting is the process of evaluating risk before making a financial decision. It involves reviewing information, checking for accuracy, and deciding if the applicant qualifies and on what terms.
Let's see how it works in specific industries:
In Lending
Underwriting is the step where funders decide if a business qualifies for financing. It is the point where risk assessment, financial data, and business practices come together.
The goal is to understand if the borrower can repay the loan or advance while keeping the funder protected.
The underwriting system varies by industry, but the overall process usually involves reviewing credit scores, cash flow, and collateral.
SMB Finance: Merchant Cash Advance (MCA)
Underwriting moves quickly in the MCA industry because businesses often need same-day funding. Funders review recent bank statements rather than full financials.
This helps them see daily cash flow and spot complex risks like overdrafts or sudden drops in deposits.
For example, if a small business shows consistent sales deposits but frequent overdrafts, the underwriting quality may be questioned even if the revenue looks strong.
The process often starts with an application that checks basic business details. After that, underwriters parse business bank statements line by line or using a document automation platform.
Some underwriters may also use bank verification software to check account ownership, transaction history, and daily balances. Once verified, they then look for stable cash flow to support repayment through revenue splits.
If daily deposits show a steady pattern, the business has a better chance of approval. Risk assessment here is less about credit scores and more about real-time revenue.
This practice allows funders to move fast and keep up with competitors in a high-volume environment.
Equipment Finance
Underwriting in equipment finance depends on the ticket size. For smaller deals under $400,000, the process is lighter. Business financial statements and application data are often enough to evaluate repayment ability.
Larger deals, however, bring more complex risks. These require full financial reviews, including profit and loss statements, balance sheets, and cash flow reports.
The underwriting process also considers the value and condition of the equipment. For example, a funder reviewing a construction company might focus on whether the bulldozer being financed holds enough resale value to serve as collateral.
Borrower character and cash flow patterns also matter. An established company with steady revenue and good practices will move through the loan process faster than one with inconsistent records.
Underwriters balance risk assessment with collateral checks to build fair terms. They work closely with brokers to review files, ask for missing documents, and structure repayment schedules.
Regulatory compliance is also part of the overall process, especially in larger deals where both equipment value and financial reporting must meet higher standards.
This careful approach helps protect funders while giving businesses access to the tools they need to grow.
In Insurance
Underwriting in the insurance industry is about balancing risk and pricing. Funders and brokers often think of it as the step where underwriters decide whether an insurance company should take on a client, and at what terms.
The overall goal is to practice good risk selection, price coverage fairly, and keep the insurer profitable.
The process is not one-size-fits-all. It changes depending on the structure, the type of coverage, and the role of the underwriter.
Managing General Agents (MGAs)
Managing General Agents operate with delegated authority from insurers, which means they can bind policies directly.
The underwriting workflow for MGAs usually starts with submissions from retail agents. From there, underwriters check if the submission matches the carrier’s appetite.
For example, if an insurer is interested in cyber liability but not in commercial auto, the MGA filters out the risks that fall outside that scope.
They then perform a detailed risk assessment, which often includes reviewing loss runs, studying historical claims, and analyzing risk factors tied to the client’s business.
An MGA might focus on fleet coverage. In that case, their underwriting system checks accident history, driver records, and vehicle condition.
Strong records improve underwriting quality, while frequent claims or poor maintenance identify areas of concern.
MGAs then prepare quotes, negotiate with agents, and bind coverage quickly, since speed often wins deals. It’s all about balancing decision-making with market competition.
They rely on document automation for insurance to process submissions, automate appetite checks, and share data with carriers.
Program Administrators (Large Multi-line)
Program Administrators manage entire programs for carriers or associations. They also hold underwriting authority, but usually cover multiple lines of business at a larger scale than MGAs.
In practice, this means they combine specialist underwriting with end-to-end program management. Their work begins with risk selection for specific industries or affinity groups.
For example, a program administrator handling a trade association’s insurance program may design policies tailored to member needs.
This could include setting deductibles, limits, and coverage features that account for common claims patterns in that sector.
Unlike MGAs that focus more narrowly, program administrators handle underwriting, rating, quoting, binding, and sometimes even claims management. Their role involves broader decision-making, balancing insurer profitability with client expectations.
A chief underwriting officer often oversees the underwriting quality, setting practices that guide underwriters across the program.
Automation and CRM tools can help program administrators manage high volumes while still tailoring policies. This allows them to scale programs without sacrificing underwriting quality.
4 Strategies to Improve Operational Efficiency in Your Underwriting Process
Underwriting is at the center of funding and insurance, but many teams face challenges that slow them down.
In SMB finance, processing one submission can take 10 to 12 minutes, and delays often happen because of time zone gaps, outages, or staff being away.
Scaling often means hiring more staff, which raises costs without improving efficiency. Oversight may also become inconsistent, causing missed details and weaker accountability.
The insurance industry faces similar struggles. Many firms still rely on manual processes to handle every submission. They open documents, pull out details, and re-enter them into the system. This takes a lot of underwriters' time and limits their focus on decision-making.
Both industries usually employ BPOs (business process outsourcing) to do the manual work for them. And this isn't exactly affordable. In fact, the global spending for BPOs reaches a staggering $300 billion.
If these problems are not fixed, funders and insurance teams risk higher costs, more mistakes, and lost deals. Competitors with faster systems will move ahead, and growth and stability will be at risk.
And so, what should you do? Here are 4 strategies you can try out.
1. Simplify Your Process with Automation and Technology
Both SMB finance and insurance rely on underwriting to make good funding and coverage decisions.
But when the process depends too much on manual data entry and repetitive tasks, the underwriting workflow slows down.
Automation and digital transformation can fix these gaps by giving decision makers better data, faster processing, and tools that reduce potential losses.
Available Technologies You Can Leverage
Below are some technologies that are changing how SMB finance and insurance teams handle their daily work:
- Intelligent document processing (IDP) – Automates intake of PDFs, contracts, and ACORD forms by extracting data, validating against rules, and classifying files. This saves hours of manual work and speeds up the underwriting workflow.
- Artificial intelligence (AI) – Learns from past underwriting data to refine risk assessment and pricing. It triages routine cases automatically while flagging complex files for human review.
- Machine learning (ML) – Detects patterns in large datasets to predict defaults and portfolio risks. Continuous updates improve accuracy and strengthen underwriting quality.
- Optical character recognition (OCR) – Converts scanned statements and claim forms into digital data. This reduces missing information and delivers structured records instantly.
- Robotic process automation (RPA) – Automates repetitive tasks like email processing and CRM updates. It cuts delays and frees underwriters from low-value work.
- Natural language processing (NLP) – Extracts insights from unstructured text like loss runs or claims narratives. It flags red flags and routes cases to the right team faster.
How Heron Helps Funders and Brokers
Heron is an automation platform built for high-volume MCA funders, brokers, and insurance partners who want to scale without adding headcount.
Heron saves underwriters' time by automating submission intake, bank statement scrubbing, and decision email processing.
- Automate data entry & document ingestion – Heron parses incoming submission packages from email, renames files, and creates structured records directly in CRMs or underwriting systems. This allows funders and brokers managing hundreds of ISO submissions to process them in seconds rather than hours.
- Validate & enhance applications – Heron checks submissions against underwriting criteria and flags missing information automatically. It enriches applications with external data sources so that underwriters receive decision-ready files.
- Integrates with existing workflows – Unlike generic tools that require expensive rebuilds, Heron plugs into CRMs, PAS, and underwriting workbenches already in use. It creates audit trails for every submission, helping teams stay compliant and efficient.
2. Data Integrity and Centralization
Data integrity is about making sure information stays accurate, consistent, and reliable from the moment it enters your system until the time it is used.
Data centralization means keeping all that information in one place so teams have a single source of truth.
This removes the problem of scattered records and makes it easier for many underwriters to see the full picture.
Imagine a broker working with five different funders. They don't have to dig through separate email chains and spreadsheets; all details sit in one platform. This approach improves pricing accuracy, strengthens risk assessment, and speeds up decision-making.
It also helps streamline daily workflows, cut manual errors, and handle more business without adding staff.
With centralized and trustworthy data, teams can respond faster to clients, avoid asking for the same documents twice, and build stronger relationships by delivering accurate quotes and quicker answers.
How Can You Accomplish Data Integration and Centralization?
Putting data integrity and centralization into practice takes more than just storing files in one place. Here’s how you can start building a stronger data foundation:
- Build a centralized data platform – Combine data from applications, bank statements, credit reports, and policy files into one unified system.
- Standardize data inputs – Use consistent formats, field names, and definitions so that information lines up correctly. For example, ensure revenue data, policy numbers, or claim IDs follow the same structure.
- Automate data validation – Set up rules that check for missing information, flag inconsistencies, and confirm accuracy as soon as data enters the system.
- Introduce continuous monitoring – Keep data health in check with automated tracking tools. These can alert teams if numbers stop matching, if documents are incomplete, or if updates are overdue.
- Set up data governance – Define who has access to what data, who can edit records, and how updates are logged.
- Use integration tools – Connect systems with APIs or ETL processes to pull data automatically. This allows funders and brokers to keep information fresh and reduces time spent on manual transfers.
- Prioritize security – Apply encryption and access controls to protect client and financial data. A secure system also makes it easier to meet regulatory requirements.
- Leverage analytics and reporting – Use centralized data to generate reports that improve pricing accuracy, spot market trends, and highlight areas for growth.
3. Use Global Data Insights and Predictive Analytics
Global data insights and predictive analytics combine advanced tools with smarter analysis to improve underwriting.
Global data insights mean pulling information from multiple regions, markets, and external data sources to create a fuller picture of risk and opportunity.
Predictive analytics then uses models, machine learning, and AI to study past and present data to forecast future outcomes, from pricing accuracy to claim likelihood.
Together, they give funders and brokers the ability to make faster, smarter, and more profitable decisions.
How Can You Start?
Here are some actionable steps that can help you get started on adapting data insights and predictive analytics into your underwriting workflow:
- Identify key data sources – List where your information comes from today, such as applications, bank statements, credit reports, and claims records. Add external data sources like industry databases, market reports, or credit bureaus to expand visibility.
- Choose the right tools – Select analytics platforms or underwriting tools that can integrate multiple datasets. Look for ones that offer predictive scoring, fraud detection, and reporting features built for finance or insurance.
- Run a pilot program – Begin with a small dataset or a single underwriting workflow, like business bank statement analysis or claims screening. This helps test predictive models before rolling them out across the business.
- Clean and standardize data – Make sure formats and categories are consistent. For example, align revenue fields or claim types so the models can read and compare information correctly.
- Define goals and success metrics – Set clear outcomes, like faster decision times, improved pricing accuracy, or fewer fraudulent applications slipping through. Measure results against these goals.
4. Provide Your Team with Continuous Training
Technology speeds up workflows, but it is your human underwriters who interpret results, apply judgment, and deliver the final decision.
Continuous training makes sure they have the skills and confidence to work alongside advanced systems while maintaining accuracy, compliance, and strong client service.
Training also supports the adoption of the tools discussed earlier, such as IDP, predictive analytics, and automation platforms.
Without the right preparation, underwriters may resist change or fail to take full advantage of the technology.
When they are well-trained, they can turn automation outputs into actionable insights that improve decision-making and portfolio performance.
How Can You Make Sure Your Team's Skills Are Up to Date?
Here are things you can do to make sure your team is well-trained.
- Regular formal education – Host webinars, workshops, and certification programs on underwriting fundamentals, regulatory compliance, and advanced analytics.
- On-the-job training and coaching – Pair new or less experienced staff with mentors and use a peer review process to reinforce decision-making. Reviewing real cases together builds consistency across the team.
- E-learning platforms – You can also give underwriters access to self-paced online courses and resources. This flexibility allows them to keep learning even during busy underwriting cycles.
- Simulations and case studies – Create practice sessions using real underwriting scenarios. For example, simulate how automation flags missing information and let underwriters decide how to act on it.
- Technology training – Offer focused tutorials on underwriting software, predictive analytics, and AI-driven tools.
- Monitoring and measurement – Track progress through assessments, portfolio performance metrics, and error rates. Use this data to refine programs so training directly supports how underwriting helps the business grow.
Smarter Underwriting Starts with Heron
Heron gives funders and brokers the speed and accuracy they need to grow without adding staff. Instead of dealing with legacy processes that slow down deal flow, Heron automates the messiest parts of underwriting.
From submission intake to document parsing, validation, and system syncing, the platform cuts processing times from hours to seconds.
With Heron, teams no longer waste effort on manual data entry or repetitive document checks. Underwriters receive clean, structured, and decision-ready data directly in their CRM or policy system, allowing them to focus on risk assessment and client relationships.
Whether you manage MCA deals, equipment finance, or insurance submissions, Heron streamlines your underwriting workflow and gives you the edge to close more business faster.
FAQs About Underwriting Efficiency
What are the 3 C's of underwriting?
The 3 C's of underwriting are character, capacity, and collateral. Character looks at a borrower’s reliability, capacity checks their ability to repay, and collateral is what they can offer as security. These help assess individual risks before approval.
What are the 4 types of underwriting?
The four types of underwriting are loan underwriting, insurance underwriting, securities underwriting, and real estate underwriting. Each type reviews financial or health records, depending on the case, to decide the level of risk and terms of approval.
How to measure underwriting performance?
Underwriting performance is measured by looking at loss ratios, expense ratios, and overall profitability. It also considers how accurately risks are priced and how well claims match projections in areas like casualty insurance.
What are the four stages of underwriting?
The four stages of underwriting are application, risk assessment, decision, and policy issuance. In these steps, details are reviewed, risks are analyzed, and a final decision is made before coverage or approval is given.
