Breaking Property New 20/08/24
Daily bite-sized proptech and property news in partnership with Proptech-X.
How useful is Artificial Intelligence (AI) in mortgage lending?
Darina Moliva from Ascendix, outlines how AI is transforming the mortgage industry.
‘In America according to Fannie Mae, 30% of lenders have already adopted or tried AI software. With this figure is expected to climb to 55% by 2025. AI in mortgage lending can cover many traditionally manual tasks. You can extract relevant data from leases, analyse financial data, and predict the risk of loan defaults. Mortgage AI tools are useful in the post-approved stage as well.
With the help of predictive analytics, mortgage AI tools can review your borrowers’ credit reports to find warning signs, like changes in how they borrow or pay. By catching these signs early, you can contact your clients and offer a more affordable repayment plan, which can help prevent them from missing payments. With the help of AI, lenders can speed up application approvals, flag signs of potential fraud, and improve risk assessment.
AI in mortgage lending is built on machine learning (ML) algorithms that ease the lending process. Using data analytics to evaluate risks, creditworthiness, property valuation, fraud detection, and more. It identifies patterns and trends humans might miss. For example, AI can detect that borrowers who make frequent, small payments are less likely to default. This helps lenders make better decisions and reduce risk.
Mortgage lending involves several pain points that complicate the process for both lenders and borrowers. Listed below are just some of the most significant issues:
Lengthy application process: It often requires extensive documentation, such as proof of income, credit history, and property details. This can take weeks or even months to gather and verify. Risk of fraud and errors: Lenders must meticulously review every document to ensure accuracy and authenticity. Incorrect or falsified information can lead to delays and potential legal issues.
Fluctuating interest rates: Fluctuating interest rates make it difficult to secure favourable terms and causing potential delays in finalizing loans. Large volume of documents: Borrowers and lenders handle a ton of paperwork, from initial applications to closing documents. This can potentially increase the risk of mistakes and adds complexity to the process.
Lack of personalized mortgage offerings: Many mortgage products are created to fit broad groups of borrowers rather than being tailored to individual needs. This means borrowers often have limited choices, such as fixed-rate or adjustable-rate mortgages, which may not consider their unique financial situation or future goals. (Picture – Darina Moliva – Ascendix)
How the introduction of AI in mortgage lending is helping professionals in real estate
- Automating Mortgage Document Processing
Traditionally, a human would manually review your credit history, financial statements, and other documents to determine if you qualify. This process can be slow and prone to human error or bias. With mortgage AI tools, the experience is much more efficient and accurate.
Document automation focuses on processing financial statements, tax returns, pay stubs, and other relevant paperwork. As shown in the picture below, you start by uploading a static document, whether it’s a PDF, Excel sheet, Word file, or a hand-written note. The AI tool with the OCR component then converts it into text that you can easily copy and paste.
The best part is that you can also ask the AI to summarize the document or extract key information. For example, if you want to know the mortgage interest rate for a customer back in 2018, you can simply ask the tool, and it will quickly find and present that information in a concise, easy-to-read format.
Document automation goes beyond just speeding up the process. It allows lenders to handle large volumes of documents and flag inconsistencies or missing information. Our Ascendix team has developed a framework for mortgage document abstraction, tailored to fit your specific needs.
- Enhancing Credit Scoring
Credit scoring is a long and meticulous process. One must check the borrowing history, review payment patterns and total income, as well as the client’s financial stability. Credit scoring becomes quick and seamless. Machine learning algorithms process vast amounts of information, identify patterns, and provide a more comprehensive view of a borrower’s creditworthiness.
AI helps you see the details, like spending habits and income sources. It can scan documents in minutes, so you get faster results. Its credit scoring can spot early signs if someone is likely to miss a payment before it happens, helping lenders make better decisions.
- Personalizing Micro-Lending Solutions
Every borrower has different financial situations and needs. But traditional mortgage products often lack the flexibility to adapt to these individual circumstances.
With AI, lenders can craft lending solutions that fit the specific needs of each borrower. By analysing extensive data, AI finds patterns in borrower behaviour and preferences. So, lenders know how to create personalized micro-loans. It’s beneficial for clients of every walk of life: first-time buyers, freelancers, or those with non-traditional income. It makes the lending process more relevant for the borrower but also boosts the chances of timely repayment.
- Automating Underwriting
Automated underwriting leverages AI to assess loan applications more quickly and accurately than traditional methods.
Mortgage AI underwriting systems evaluate borrower data, credit scores, employment history, and other relevant factors to make real-time decisions. This not only speeds up the approval process but also ensures consistency and reduces human bias. Automated underwriting can identify potential red flags, such as discrepancies in income reporting or previous defaults, allowing lenders to make informed decisions and offer suitable loan products.
- Detecting and Preventing Fraud
It can detect and prevent fraud in a smart way, AI systems analyse patterns and behaviours to identify suspicious activities. Detecting anomalies in loan applications, such as inconsistencies in reported income or employment history. AI can also monitor transactions for signs of money laundering or identity theft. By flagging these issues early, lenders can take preventive measures, safeguarding their operations and maintaining regulatory compliance.
- Enhancing Risk Assessment
Mortgage AI enhances risk assessment by analysing vast amounts of data. AI in mortgage lending can assess risks by identifying potential environmental hazards, local market fluctuations, and neighbourhood crime rates. For example, if mortgage AI detects that the property is in a flood-prone area based on historical data and recent weather patterns, it might flag this as a risk. This allows the lender to adjust the loan terms or require additional insurance to mitigate potential losses.
- Better Data Organization Customer Relationship Management (CRM) Systems
AI-boosted CRM systems, like Salesforce, manage and analyse customer interactions and data throughout the customer lifecycle. Imagine a mortgage broker using an AI-enhanced CRM system. Here’s a case study, a client recently inquired about refinancing the mortgage. Mortgage AI in CRM tracks client’s interactions, such as email exchanges and call logs, and notes her specific interest in lower interest rates. Based on this data, the AI predicts that the client is likely to be interested in promotional refinancing offers.
The next time the client logs onto the mortgage broker’s website, they receive a personalized message offering a new refinancing option with competitive rates. Mortgage AI feature also suggests relevant loan products based on their financial profile and previous interactions. Additionally, the CRM system alerts the broker to follow up with the client at an optimal time, based on their past engagement patterns.
- Improving Customer Service with AI-Powered Chatbots & Assistants
Chatbots and virtual assistants automate customer interactions. They can cover the following tasks: answer frequently asked questions, schedule appointments, and provide initial mortgage advice.
Concluding thoughts
AI will not replace mortgage brokers, according to the top mortgage technology executives, companies indeed are embracing AI in mortgage lending for the purpose of assistance and speed and removal of human error. In terms of helping a mortgage broker, mortgage AI tools can automate day-to-day tasks in broker’s routine. The tools include document processing, AI mortgage lending, data analysis, risk assessment. Additionally, AI chatbots improve customer experience.
As to what are the best AI tools for mortgage, here in America there are many that simplify and automate the process of applying for a loan. The well-known AI mortgage broker tools include such names as Wealthfront, Betterment, Schwab IP, Interactive Advisors, and others.
Andrew Stanton Executive Editor – moving property and proptech forward. PropTech-X
You May Also Enjoy
Landlord Demographics Remain Broadly Unchanged
London’s most prestigious postcodes revealed
Software GDTJ45 Builder Problems: Causes, Solutions, and Best Practices
Developers draw confidence from improving lending landscape
Happy New Year! UK construction performance finishes 2025 on a high
