According to the Mortgage Bankers Association, outstanding mortgage debts were estimated to total $14 trillion in 2024. Ever-rising interest rates, which the US Federal government raised 11 times from February 2022 to October 2023 to contain inflation, have made homebuying more challenging.
The mortgage industry has remained unchanged for several years, with struggles of disgruntled customers and complex calculations. With the advancements in AI technology, it is time to revamp the user experience and technology around mortgage banking.
Key Priorities in Mortgage Banking
To meet the changing needs of customers in this environment, here are some key priorities that have helped the mortgage banking industry to make usability simpler for their customers:
- Digital Transformation: Embracing digital technologies is essential for improving efficiency, reducing costs, and enhancing the customer experience. This includes digitizing processes like loan origination, underwriting, and closing.
- Regulatory Compliance: Adherence to strict regulatory guidelines is crucial for mortgage banking institutions. Staying up-to-date with evolving regulations and implementing robust compliance measures is a top priority.
- Customer Experience: Providing exceptional customer service is vital for attracting and retaining borrowers. This involves offering personalized experiences, streamlining the application process, and communicating promptly.
- Risk Management: A critical aspect of mortgage banking is managing risks associated with lending. This includes assessing creditworthiness, pricing loans appropriately, and mitigating potential losses.
Introducing AI in Mortgage Banking
Artificial intelligence (AI) has the potential to revolutionize the mortgage banking industry by automating processes, improving decision-making, and enhancing customer satisfaction. Here are some key areas where AI can be applied:
- Underwriting: AI algorithms can analyze vast amounts of data to assess borrower risk more accurately and efficiently, reducing the time and cost associated with manual underwriting.
- Fraud Detection: AI-powered systems can identify fraudulent activity patterns, helping protect lenders from financial losses.
- Customer Service: AI-powered chatbots can provide instant customer support, answer common questions, and assist borrowers throughout the application process.
- Predictive Analytics: AI can analyze historical data to predict market trends, identify potential risks, and optimize pricing strategies.
- Regulatory Compliance: AI can help automate compliance tasks, such as monitoring regulatory changes and ensuring adherence to guidelines.
Use Cases of Gen AI in Mortgage Banking
Generative AI is revolutionizing the mortgage banking industry by automating processes, improving decision-making, and enhancing customer experiences. Some of the modules that we can non-exhaustively use are:
1. Sales and Relationship Management
A broad segment covering client activities, personalizations, and industry trends that are all about simplifying the customers and managing existing relationships.
- Develop an Outreach plan for target prospects that allows creating a tailored outreach plan (channel, time, frequency) based on client preferences using AI to automate these interactions.
- Marketing personalization with AI creates context for digital client outreach (e.g., tailor-made creatives/images per client)
- Client advisory solutions combine ML with Gen Al and transform a large volume of relevant and curated data insights into searchable, summarize-able, and conversational formats.
- Summarize industry trends & research can help generate insights and materials on key industry factors impacting clients
2. Client Onboarding, Underwriting, and Administration
Automating numerous tasks is possible with AI can help employees utilize their time with more valuable tasks.
- Client and product onboarding can be simplified by analyzing text-heavy documents like annual reports, news reports, etc., further enhancing KYC and onboarding review.
- Automate credit memo generation based on client and industry context.
- Generate internal communications for responding internally and for closing deals with clients.
3. Product Fulfilment and Implementation
Developing Products is tedious, but utilizing document exception tracking with AI helps summarize the information received/needed from clients based on the structure and terms of the requirements.
4. Servicing
Managing post-sales services is very essential for customer retention and improve customer satisfaction.
- Transaction and cash flow insights help summarize changes in client behavior based on historical transactions and AI-projected cash flows and explain the change's root cause.
- Customer-facing chatbot can expand the breadth and effectiveness of chat-based servicing solutions using open LLM and AI platforms.
- Process & knowledge management provides how-to AI-driven insights from bank data, processes, and policies with links to sources.
- Payment reconciliation services significantly reduce the time spent researching and resolving reconciliation breaks to improve data quality in golden source systems using AI-driven testing.
5. Corporate Actions
Managing a corporate is lots of work and finding support with AI is beneficial.
- Smart Inbox Management helps summarize content, suggest the next best actions, and automate email responses to help simplify enterprise management.
- Summarize meeting notes & actions with AI to synthesize notes, actions, speakers, and attendees into shareable/searchable content across the organization.
- Data analysis & visualization assistant provides summary insights and visuals from ad hoc data sets (e.g., bank statements)
Balancing Momentum with Complexity and Value
Within mortgage banking, prioritizing use cases is crucial to balancing building momentum with the complexity and value of each initiative. Mortgage banking institutions can maximize their return on investment and drive innovation by focusing on use cases that deliver the most significant benefits while minimizing complexity. One of the USA's largest housing loan mortgage providers is our customers, who engaged with our AI-driven solution firsthand.
1. Product Management Navigator
They unlocked a seamless journey from concept to code with CirrusInsightsAI, the ultimate co-pilot for Product Managers and Owners. By streamlining their strategy using a lean business canvas and mastering workflow efficiency, they effortlessly defined your system and user requirements to generate comprehensive Epics, Features, and Capabilities.
Saved 4-6 months time
2. Code Creation
AI can facilitate app modernization through tools like TensorFlow for machine learning, GitHub Copilot for code generation, and AWS Lambda for serverless architecture. These tools automated the refactoring process and integrated advanced functionalities with minimal manual intervention for this client.
Saved 3-4 months
3. AI-powered IT Operations
IT operations powered by AI can leverage machine learning and data science to automate the identification and resolution of common IT issues, fundamentally transforming the landscape of IT management.
Saved 3-4 months
As the mortgage banking industry evolves, embedding AI will play an increasingly important role in shaping the company's future. By prioritizing key initiatives and leveraging AI's power, mortgage banking institutions can improve efficiency, enhance customer experiences, and stay ahead of the competition by saving time and resources to help increase profitability. Contact CirrusLabs to generate a customized plan that works for your mortgage firm.