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Artificial intelligence (AI) has changed the way many industries work, and finance is no exception. Banks, brokers, and other financial institutions are using this technology to process data faster and reduce errors.
What once took days of paperwork and manual reviews can now be done in minutes with AI-driven tools.
From credit assessments to fraud detection, this technology is reshaping how funders, brokers, and banks handle lending decisions.
This article explores what AI can do for financial institutions and borrowers.
Introducing Artificial Intelligence in Financial Services
Many funders are now leveraging AI systems to review applications, track patterns, and make quicker funding decisions.
Machine learning helps funders study large sets of information to assess credit risk with more accuracy. Natural language processing (NLP) allows systems to read contracts or respond to customer questions in real time. These tools not only speed up operations but also give financial teams sharper insights.
Adoption is rising quickly. A 2023 Fannie Mae survey found that 73% of funders prioritize operational efficiency with AI and ML, a big leap from 42% in 2018.
McKinsey’s State of AI in 2024 shows that 78% of organizations already use AI in at least one business function, with financial services focusing heavily on lending processes like loan origination and credit decisions.
As the technology continues to grow, artificial intelligence in finance is becoming less of an option and more of a standard practice.
Book your demo today and see how Heron automates the document-heavy work.
Main Applications of AI in Funding Services
Artificial intelligence is changing how funders and the broader banking sector handle daily work. Let's look at some of the main applications.
Loan Processing Automation
AI tools like optical character recognition (OCR) and natural language processing make document intake and review much faster. They reduce the need for manual data entry and paperwork.
Instead of staff entering income statements line by line or scanning ID documents one by one, OCR can extract the details instantly. NLP then interprets contracts or supporting files so they can be verified without delay.
For funders, this speeds up document intake, cuts processing time from days to hours, and makes loan origination much quicker. Customers also benefit by getting decisions sooner.
Fraud Prevention
Fraud is a constant challenge in the funding space. AI systems track transactions, borrower histories, and identity records in real time.
If a borrower’s payment pattern suddenly shifts or if identification details appear inconsistent, the system raises an alert right away.
This allows funders to stop fraud before financial losses occur while also meeting regulatory standards.
Borrower Risk Assessment
Credit assessments often depend on more than just traditional credit scores.
AI models analyze both standard and nontraditional data, such as utility payments, online transaction history, or business performance metrics. This gives funders a more complete view of a borrower’s ability to repay.
By combining these data points, funders can set accurate credit limits, offer fairer credit scoring, and expand credit access to customers who might otherwise be overlooked.
Loan Decisioning
AI helps funders separate straightforward cases from those that need more attention. Low-risk applications can be approved instantly, while higher-risk cases go to a human reviewer.
For example, if a borrower has a strong repayment history and steady income, the system can tag their application for approval automatically.
If the profile shows gaps or irregularities, it routes the application to a credit officer. This automation removes much of the manual work in lending processes and allows funders to focus on the exceptions.
Personalized Loan Pricing
AI looks at borrower behavior, credit scoring, and market conditions to shape personalized loan terms. Funders can adjust pricing based on actual risk levels rather than a one-size-fits-all rate.
For instance, a borrower with a steady payment record might receive a lower interest rate, while someone with limited history might be offered higher but still fair terms.
This helps funders stay competitive and gives banking customers better options.
Customer Interaction
AI-powered virtual assistants now manage a large share of borrower questions.
From checking loan status to explaining credit limits or guiding applicants through forms, these assistants give quick, accurate answers.
Customers get faster service, while staff gain more time to focus on strategic relationships and high-value tasks.
Loan Portfolio Management
Managing a large set of loans is challenging without real-time insights. AI-driven analytics track repayment trends, detect early signs of default risk, and suggest strategies to strengthen portfolio performance.
If borrowers in a certain region start missing payments, the system highlights this pattern so funders can act quickly. This proactive approach helps protect profitability and stability across the funding business.
Benefits of Using AI in Lending
When implemented carefully, AI can give your team clear advantages, such as:
Faster Approvals That Improve Customer Experience
AI helps banks and funders move far beyond the long waits often tied to traditional methods. For example, what once required days of manual reviews can now be completed in minutes.
Systems powered by AI scan income statements, IDs, and credit data automatically, which means applications are processed faster without sacrificing accuracy.
According to an article by Science Soft Finance, AI can automate up to 75% of credit decisioning and can potentially make loan processing 25x faster.
This speed creates a better customer experience, as borrowers no longer face delays for approval, and funders can handle more applications in less time.
Smarter Lending Decisions With More Data
AI transforms credit reviews by using multiple sources of information, not just credit scores. For instance, a borrower’s digital payment history, utility payments, or even seasonal income trends can all be analyzed alongside standard reports.
AI combines this data to build a fuller picture of borrower behavior and improve lending decisions.
This approach expands credit access, raises approval rates, and lowers default risk compared to relying solely on traditional methods.
Strong Fraud Prevention And Risk Reduction
Fraud and money laundering are serious risks in the banking sector. AI systems constantly monitor applications and transactions for unusual activity.
For example, if an applicant submits documents with subtle tampering or if payments suddenly appear from a high-risk region, the system flags it instantly.
This real-time detection helps funders reduce risks, protect their portfolios, and maintain customer trust. With AI, potential fraud is caught before it causes losses.
Lower Costs Through Automation
Repetitive tasks like entering borrower information, cross-checking documents, or updating files often consume a lot of staff time.
Before automation, it could cost banks more than $50 per application just to get it into the system.
Automated document scanning can replace hours of staff input, and AI-driven credit scoring can route simple cases directly to approval.
This shift can cut processing costs by 75% or more, reduce errors, and free underwriters to focus on complex cases that require human judgment.
How Heron’s AI Speeds Up Lending and Cuts Manual Work
Brokers deal with nonstop submissions, multiple funders, and tight turnaround times. Manual steps such as entering data, reviewing PDFs, and chasing funder responses take up valuable hours. Heron is a game-changer for this process.
Using AI and machine learning, the platform tackles repetitive tasks, helping MCA brokers and funders increase efficiency, improve customer experience, and focus on better decisions for clients and borrowers.
Let's get into detail about how Heron can help you manage your increasing application volume:
Automate Data Entry And Document Ingestion
Daily submissions often arrive through email in messy, inconsistent formats. Heron cleans up this process by parsing document packages, standardizing file names, and categorizing files automatically.
Structured data then flows directly into the broker’s CRM. This approach reduces the time required for manual prep and lowers cost, since there’s no need to hire additional processors.
Helping Brokers Handle Massive Submission Volume
Brokers act as the bridge between small business borrowers and multiple funding sources. Each day, they may process over 100 submissions that generate hundreds of funder decisions.
The challenge is not just intake, but also portal submissions, matching clients to the right funders, and keeping up with 2–4 hour response requirements.
Heron automates the heavy lifting. Submissions arriving by email are parsed, organized, and pushed directly into the broker’s CRM.
Decision emails from funders, sometimes more than 500 daily, are automatically captured and sorted so brokers do not spend hours digging through their inbox.
This reduces cost, improves customer experience, and gives brokers more time to build trust with clients and strengthen services.
Helping Equipment Finance Scale Without Extra Headcount
Equipment financing faces challenges that shift with deal size. Small-ticket financing often requires quick credit assessments, while large-ticket deals depend on hours of manual financial statement analysis.
In both cases, repetitive tasks such as spreading financials and calculating ratios slow down turnaround times.
Heron solves this by automating financial statement spreading, standardizing submissions, and providing analysts with structured files that already include key ratios.
What once took hours can now be done in minutes. This ability helps funders increase efficiency, keep compliance strong, and deliver financial products faster to clients.
A credit team handling more than 500 submissions monthly can scale without adding headcount, reduce cost, and improve service to borrowers who depend on timely approvals.
Faster Decision Making Without Extra Staff: Try Heron Today
Heron is built for high-volume funders and brokers who need to move faster without adding more people to their teams.
Take your team out of paperwork and put them back into funding deals. Manual processes like application intake, bank statement analysis, and funder decision emails slow growth and cost money.
Heron automates these tasks, sending clean, structured data straight into your CRM in seconds. That means less time wasted, more deals closed, and greater ability to handle higher application volume.
Unlike generic automation tools, Heron is designed for MCA and lending workflows. It plugs into your existing system of record without an expensive rebuild, helping you enhance efficiency right away.
- Smarter intake: Heron captures documents from email, portals, or APIs and organizes them automatically. File types are identified and classified, eliminating manual prep work and saving hours each day.
- Accurate parsing: Complex financial files like ACORDs, loss runs, or handwritten forms are processed instantly. Heron extracts clean data, flags missing fields, and removes duplicates so every record is decision-ready.
- Data enrichment: Parsed data is strengthened with details from internal and third-party sources. Vehicle data is normalized, NAICS codes are assigned, and financial metadata is added for a complete borrower profile.
- Built-in checks: Business rules are applied to every file. Inconsistencies, non-compliant entries, or missing information are flagged right away to reduce rework and maintain compliance.
- Actionable analytics: Metrics hidden in documents, such as premiums, loss ratios, or utilization rates, are pulled into clear outputs. This powers underwriting, lending, and risk decisions without extra manual processes.
FAQs About AI in Lending
How is AI being used in the lending industry?
AI is helping the lending industry speed up loan approvals, spot fraud, and give more accurate risk checks. It can also match borrowers with financial products that fit their needs, which makes lending smoother for both banks and customers.
What is the role of AI in loan approvals?
AI looks at more than just credit scores. It studies spending habits, income patterns, and other data to give funders a clearer view of an applicant’s ability to repay. This allows approvals to be quicker and often fairer, improving customer satisfaction in the process.
Is there a ChatGPT for finance?
Yes, finance-focused AI tools are available, and some work like ChatGPT but are trained specifically for money-related tasks. They can answer questions, analyze data, and even provide insights that help both funders and customers make better decisions.
Is AI good or bad for finance?
AI can be both, depending on how it’s used. It improves accuracy, saves time, and reduces risks, but it also raises concerns about bias, transparency, and data privacy. The key is balancing innovation with safeguards so finance remains fair and trustworthy.