Insurance AI
February 7, 2024

The Future of Loan Origination is AI-Powered

AI for loan origination automation and predictive modeling helps improve efficiency and applicant experience for lenders like Direct Mortgage.

The loan origination process is ripe for automation using artificial intelligence.

Manual processes for validating applicant identity, income, assets, and eligibility are inefficient, inconsistent, and costly for both lenders and applicants. AI offers a path to radically transform loan underwriting by improving speed, accuracy, and the applicant experience.

This article explores how generative AI and predictive modeling are modernizing the mortgage industry through enhanced decision-making. Key topics include:

  • The role of decision AI in loan underwriting
  • A case study on Direct Mortgage's transformation
  • Benefits of loan origination automation include faster approvals, enhanced compliance, and applicant conversions
  • Future directions, like automated appraisals and personalized recommendations

Generative AI Gives Mortgage Lenders a Competitive Edge for Loan Automation

Let’s start by looking at a recent case study.

Direct Mortgage is pioneering the future of mortgage lending. Despite nearly 30 years in business, their loan application workflow was still predominantly manual and paper-based as of early 2021.

CEO Jim Beech had unsuccessfully tried automating it for years before partnering with us. In just 30 days, we customized an AI agent that could accurately classify and extract data from paystubs; the most complex document type in an application.

“I’ve tried different people with [suitable] skillsets and several different entities. We even built our own programming team. But they could only get so far, and it took forever. (...) A 1040 tax return, for example. [It] took us about a year and a half to actually get that done.” - Jim Beech

This initial automation improved applicant approvals from weeks to days. With increased confidence in AI, we expanded to over 200 document types including bank statements, tax forms, and insurance documents.

Today, AI agents handle the entire process by:

  • classifying documents
  • extracting and validating applicant data,
  • and underwriting entire loans with minimal human involvement.

According to Jim Beech, AI agents have reduced their approval time from weeks to minutes and lowered document processing costs by 80%. Just as importantly, faster and more accurate loan decisions have increased applicant satisfaction and conversions.

To sum things up, using our AI solutions, we helped Direct Mortgage:

  • Automatically process 200+ types of documents
  • Achieve a 20x faster time-to-approval
  • Reduce cost by 80% per processed document
  • Get their first working prototype powered by Generative AI in less than a month

After 29 years in business, Direct Mortgage has a way of serving more customers, reducing costs, and improving employee and customer satisfaction.

Needless to say, Jim Beech loves the new changes and wouldn’t ever go back to pre-automation time:

“Nobody is doing what we’re doing with Multimodal, not even close.” — Jim Beech

Decision AI Levels the Playing Field for Mid-Market Loan Origination Automation

Decision AI benefits

Generative AI refers to models that can generate:

  • Content
  • Text
  • Code
  • Images
  • Other outputs from given custom inputs and prompts

Generative models have fueled innovations like chatbots.

In the context of mortgage underwriting, generative AI ingests applicant data from forms and documents to determine eligibility and risk. But unlike rigid traditional software, it dynamically adjusts its evaluation methodology based on changes to lending guidelines, applicant profiles, and loan products.

This adaptability, hyper-personalization, and automation are fueled by predictive modeling and machine learning algorithms underneath the hood.

Predictive models utilize historical training data to determine the likelihood of various outcomes, such as whether an applicant will default or prepay their mortgage. When paired with generative AI, predictive models enable complex decision-making that optimizes lender objectives like balancing profitability, defaults, and conversion rates across applicant segments.

Our mortgage underwriting automation solution helps:

  • Make expert loan decisions
  • Ensure year-round compliance
  • Prevent fraud
  • Get consistently better results
  • Serve 20x more customers
  • Assess risk your way

Our AI Agents integrate directly with your workflow and the main benefits and results they can provide include:

  1. 80% cost reduction - the way we helped Direct Mortgage
  2. 20% increase in client user base - the ability to make more money by increasing the paid customer base and improving the product offering
  3. 97% workflow automation - AI Agents can automate about 80-97% of end-to-end workflows

Implementation is rapidly becoming turnkey: Freddie Mac's Loan Product Advisor recently added access to third-party verification services and fraud tools as well as integrated assets, income, employment, and identity verification functions.

Loan Product Advisor distills insights from its analytics models into simple recommendations, allowing originators of any size to compete with large banks.

We know how important it is to implement and that’s why we can customize and deliver AI Agents within your existing systems.

From there, you can use our AI Agents to:

  • Extract applicant data in custom fields
  • Make automated, minimum-risk loan decisions
  • Retrieve data from your databases in seconds
  • Provide superior employee and customer support

The Future of Automated Loan Origination: Ubiquitous Decision Intelligence

Pros of automated loan origination with Multimodal's solutions

‍Mortgage lending is just the tip of the iceberg.

Across finance, insurance, and healthcare, manual document review and subjective human decision-making result in high costs and inconsistent applicant experiences.

AI-based automation will inevitably penetrate most facets of document-intensive workflows including:

  • Claims processing - evaluating coverage and determining approvals or denials
  • Policy underwriting - establishing risk assessment levels, appropriate coverages, and premiums
  • Compliance - identifying documents, data, or processes that violate laws or regulations

As AI adoption accelerates, expect to see AI-driven recommendations and automated loan processing become standard across the finance, insurance, and healthcare sectors, leading to faster and fairer decisions. Key trends to watch include:

  1. Compound improvements from model iteration - With more training data, predictive accuracy continually improves
  2. Stacked models for advanced capabilities - Combining multiple algorithms provides more representative outputs
  3. Workflow augmentation versus pure automation - AI's highest value propositions enhance human decision-making rather than replacing it

Across verticals, achieving AI's full potential requires pragmatism - focusing investment in areas where technology gaps allow for competitive differentiation and measurable value creation.

Lenders must be willing to embrace usability and conversion as equal priorities alongside compliance and risk mitigation.

Pioneers like Direct Mortgage demonstrate, however, that generative AI and decision intelligence are set to transform applicant journeys by eliminating friction through automation.

Competitors who fail to effectively leverage data and AI risk obsolescence within the next 3 to 5 years. The opportunity to reshape market positions by deploying AI, therefore, is urgent and substantial.

Want to learn more about how AI will impact decision-making in banking? Check out this episode on AI-powered risk management with Stephen Taylor, CIO at Vast Bank.

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