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Artificial Intelligence (AI) in Mortgage
ScienceSoft relies on 35 years of experience in AI and 19 years in lending software development to design and build reliable AI solutions for mortgage.
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AI for Mortgage in a Nutshell
Artificial intelligence in mortgage drives up to a 50% increase in mortgage origination volume, brings up to a 20% reduction in mortgage defaults, and helps close mortgage deals 2.5x faster than the industry average. The technology helps mortgage providers unlock a 30–50% decrease in operational expenses and achieve a 2–5%+ growth in revenue.
AI in the Mortgage Industry: Market and Technology Adoption
The global market of artificial intelligence for the financial services industry was valued at $20 billion in 2022 and is projected to exceed $100 billion by 2032, growing at a CAGR of 20%. The key factor driving the popularity of AI solutions for mortgage is the need to ensure accurate mortgage underwriting decisions, streamline data-intensive mortgage origination and close processes, and provide top-notch mortgagee experience. According to Forbes, 55% of senior mortgage executives believe that AI can make their company more competitive and has the potential to disrupt the entire mortgage industry.
Sample Architecture of AI-Powered Mortgage Solutions
ScienceSoft builds custom mortgage solutions with secure and scalable architectures that ensure smooth mortgage data processing flows. Below, our consultants share a sample architecture of AI-powered mortgage analytics software and describe its key components:
- Mortgage data (mortgage applications, borrower documents and credit ratings, real estate market data feeds, etc.) gets automatically aggregated from the available sources and transferred to the data lake to be stored in its raw format.
- The raw data is instantly routed to the advanced analytics system for preprocessing (filtering, cleansing, enrichment), which improves data quality. The structured data is then stored in a data warehouse.
- Data from both the data lake and the data warehouse can be used to train mortgage AI/ML models, depending on their purpose. Non-neural-network (non-NN) ML models are suited for analytics tasks of moderate complexity like application triaging or fraud detection. Neural networks (NN), including complex deep learning models like LLM, are best for real-time decisioning and natural language interactions. Model design, training, and performance control take place in the model management module.
- An advanced analytics engine with AI models at its core analyzes the obtained data, delivers predictions on mortgage transactions and events, and recommends optimal actions.
- AI model outputs get stored in the analytical database and can be accessed by the mortgage team via a dedicated web or mobile app. Analytical results and prescriptions can be instantly communicated to the connected systems.
We typically integrate AI-powered mortgage software with:
- Back-office systems: a CRM or a loan servicing system, a customer portal, accounting software.
- Communication channels: email services, messaging services, auto-dialing systems.
- Third-party data sources: payment gateways, bank accounts, credit rating platforms of credit bureaus, local title and deed registries, and more.
What AI Does for Mortgage
Mortgage application processing
OCR and image analysis techs automatically extract data from digital and paper mortgage applications and borrower documents. AI validates borrower data against the data from public sources (e.g., credit rating platforms) and instantly notifies loan officers of missing or mismatched data that requires manual review.
Borrower risk assessment
AI instantly quantifies borrower credit risks based on the analysis of their credit history, income sustainability, spending patterns, and more. To get a comprehensive picture of borrower creditworthiness, AI leverages data from all available sources, including non-traditional ones like social media.
Defining personalized mortgage terms
AI determines the optimal mortgage terms (loan limit, down payment amount, interest rate, mortgage insurance, etc.) for each borrower based on a borrower’s risk score and expected mortgage deal profitability.
Intelligent mortgage decisioning
AI matches the mortgage terms requested by a borrower to the pre-estimated optimal price thresholds and coverage limits and provides intelligent suggestions on mortgage loan approval or rejection.
Collateral valuation
AI automatically valuates non-financial collaterals (e.g., real estate, cars, equipment) based on the analysis of available data on their condition, market prices for the assets, collateral liquidity, and risks.
Mortgage closing automation
AI analyzes the approved mortgage terms and instantly calculates a down payment, an escrow deposit, APR, and closing-associated fees. It also automatically generates mortgage amortization schedules and closing disclosure documents.
Debt collection planning and execution
AI recommends optimal debt recovery strategies based on the analysis of debtor behavior. It drafts personalized reminders on due payments, demand letters, and notices of default (in a textual or voice format) and submits them to debtors via their preferred communication channels.
Mortgage task triaging and assignment
AI prioritizes mortgage tasks based on their urgency, expected value, financial losses associated with task non-completion, and more. It can automatically assign mortgage origination, servicing, and debt collection tasks to the relevant employees based on their qualifications, availability, location, etc.
Mortgage analytics
AI accurately predicts mortgage demand, default rates, mortgage-related revenue, and expenses. For this, it analyzes historical data on mortgage applications, borrower payment behavior, and market-available data on projected mortgage rates and property prices.
Automated borrower interaction
AI-powered chatbots automatically notify borrowers about mortgage loan status changes, due loan repayment dates, expiring documents that need updating, etc. AI instantly processes borrower queries and responds in a human-like manner.
Opportunities AI Unlocks Across Key Mortgage Processes
Mortgage data processing
3x+ faster mortgage loan boarding and up to a 50% decrease in operational costs due to AI-enabled real-time aggregation and processing of multi-format mortgage data from all available sources.
Fraud prevention
Automated borrower document validation and borrower pre-qualification against internal standards and KYC/AML requirements to promptly spot fraud and prevent illegitimate access to mortgage services.
Mortgage underwriting
A 10–50% increase in mortgage origination volume due to AI-powered analysis of borrower creditworthiness and data-driven decision-making on mortgage loan approval.
Mortgage servicing
A 30%+ reduction in mortgage write-offs due to AI-supported borrower risk assessment and prescriptions on the optimal debt recovery strategies. 3–4x faster collections thanks to intelligent process automation.
Borrower support
Improved borrower experience due to 24/7 resolution of transactional, technical, and security issues by intelligent virtual assistants.
Mortgage business planning
Accurate planning of employee workload, portfolio activities, and liquidity and minimized financial and operational risks due to AI-powered forecasting of mortgage demand, risks, and profitability.
How Mortgage Companies Benefit From AI
US Credit Union with $9B+ in assets uses AI to get accurate mortgage decisioning
GreenState Credit Union, the largest independent financial institution in Iowa, launched an intelligent mortgage solution by Zest.AI to enhance the efficiency and accuracy of its mortgage underwriting processes.
The solution automates mortgage application processing, borrower risk assessment, and mortgage decisioning. It leverages 240 borrower data points from various channels to ensure accurate evaluation of borrower creditworthiness.
With the help of AI, GreenState Credit Union managed to increase the general approval rate by 26% and the approval rate for protected classes (women and Hispanic applicants) – by 32% with no added risks. It brought a $132M increase in annual revenue and a $11M increase in profit. AI-powered decision-making automation helped increase the speed of mortgage loan origination.
Mortgage AI startup raised $77M+ in 3 years
Cloudvirga, a Californian fintech startup, developed an AI-powered digital mortgage lending platform for buyers, brokers, and loan officers.
The solution offers fully automated mortgage application processing and generation of mortgage underwriting and close documents. It creates underwriter-ready loan files in <10 minutes and helps eliminate 70% of creditor-borrower interaction tasks. The platform users report shorter mortgage close cycle times, improved productivity of the mortgage origination teams, and an overall reduction in operational costs.
Cloudvirga raised over $77 million in funding in the first three years after the platform launch in 2017. Today, the company’s AI platform is used by 10 of the Top 40 US mortgage originators with a total annual loan volume of $200 billion.
Tech Stack for AI-Powered Mortgage Software Development
Addressing the Challenges of AI in Mortgage
Despite the proven advantages of AI for mortgage, many real estate financing providers still doubt AI’s ability to handle mortgage tasks in an efficient, ethical, and compliant manner. Having decades-long experience in AI software development and mortgage digital transformation, ScienceSoft knows how to address these issues.
Challenge #1. Explainability of AI underwriting decisions
Mortgage lenders must provide a clear explanation of their loan granting or rejection decisions to borrowers and regulators (e.g., FHA in the US) to ensure fair business practices. The sophisticated logic of AI models can be challenging to break down, which raises ethical and legal concerns associated with the poor explainability of AI-supported underwriting decisions.
Challenge #2: High requirements for data management infrastructure
AI solutions need considerable processing power, scalability, and sufficient storage space to seamlessly analyze large volumes of multi-format mortgage data in real time. Most legacy mortgage IT infrastructures fail to provide the required capacities.
Costs of Implementing AI for Mortgage
Based on our experience, developing an AI-powered mortgage solution may cost around $100,000–$650,000, depending on the solution’s functional scope, the number of AI models, security and compliance requirements, and the complexity of integrations.
$100,000–$250,000
An AI-powered mortgage solution that relies on non-NN machine learning models to process data from 1–3 internal sources and delivers analytical output in batches (e.g., every 24 hours).
$250,000–$450,000
AI software that employs NN models to process mortgage data from corporate and third-party sources and deliver intelligent predictions.
$450,000–$650,000+
A complex predictive and prescriptive system that uses advanced NN models for real-time processing of mortgage data from 5–10+ proprietary and third-party sources.
Mortgage AI Consulting and Implementation by ScienceSoft
In AI implementation since 1989 and in mortgage software development since 2005, ScienceSoft delivers secure AI solutions for consumer and commercial mortgages.
Consulting on AI for mortgage
We design an architecture of your mortgage AI solution and provide a detailed roadmap to smooth AI implementation. You also get expert advice on the project cost optimization opportunities and achieving regulatory compliance.
Implementation of AI for mortgage
We develop your AI-powered software, integrate it with the required systems, and run all necessary QA procedures. Our data scientists design, train, and tune AI models to ensure high-quality and fully explainable analytical results.
What makes ScienceSoft different
We achieve project success no matter what
ScienceSoft does not pass off mere project administration for project management, which, unfortunately, often happens on the market. We practice real project management, achieving project success for our clients no matter what.
About ScienceSoft
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. Since 2005, we have been delivering AI solutions for accurate, prompt, and efficient mortgage processes. In our AI projects, we rely on robust quality management and security management systems backed up by ISO 9001 and ISO 27001 certifications.