Digitally connecting the housing industry ecosystem

The post-pandemic phase has brought interesting challenges to the housing industry. During the pandemic, the industry enjoyed a high demand environment, low interest rates, and Fed-sponsored forbearance programs. As a result, companies benefited from increased business across the board. This uptick masked some existing operating model issues for many title insurers, lenders, and others within the industry. However, rising interest rates, reduced available home inventories, and increasing home prices began creating difficulties for these housing players from the start of 2022, bringing the inefficiencies to light. In an industry that’s faced many historical cycles of ups and downs, the question arose on how to holistically reimagine these highly human-centric, leaner operating models to more intelligent and scalable operating model that digitally connects different players in the housing ecosystem.

Connecting the housing ecosystem through data and digital

The housing industry includes many players, each with a unique role in the overall process. With lenders, real estate agents, title and escrow agents, title insurance companies, appraisers, notaries, property management firms, county clerk offices, and government-sponsored enterprises part of the mix, at various stages of the cycle, it can be a long, complex process for everyone involved.

The complicated nature of this ecosystem hasn’t completely prevented companies from innovating, such as moves to automate loan processing and underwriting or the adoption of remote online notarization (RON) etc. Some players invested in digital and data analytics to transform their business model. Many opportunities still exist depending on the investment appetite and strategy of the company. In the long run, those who leverage the right mix of automation and humans to improve experiences for purchasers and borrowers, create a sustainable business model, and automate the complete lifecycle and communication flow between various parties will be the winners.

Creating smart, connected enterprises with cloud-native AI, interconnectivity, and data analytics

To adjust to the constantly changing market that is driven by macroeconomic environment and other factors which are usually outside the control, housing industry players must create a sustainable operating model that effectively manages swings. Creating a future-proof, differentiated operating model requires building a smart, connected enterprise that seamlessly integrates with other providers. Lenders, title settlement and insurance companies, SFR and property management firms, and appraisal and valuation organizations that are considering taking this journey should keep in mind some key considerations.

Pragmatic use cases that leverage cloud-native AI and RPA solutions and provide high ROI, scalability, and variable cost structure
Interconnectivity with other business partners and eco-system providers that offers near-real time communication
Data analytics that provide intelligent insights and predictions to improve customer acquisition, operational efficiency, and customer experience

a. Cloud-native AI and RPA

While there are multiple ways of leveraging AI, algorithms, and RPA within housing business processes, it is important to select the right use cases that will result in higher ROI and scalability. Implementing such solutions in a cloud-based infrastructure avoids higher upfront capital expenditure and provides improved reliability, agility, and cost variability.

At EXL, we have identified key use cases and built specialized AI and RPA solutions for the housing industry that can be rapidly deployed in a cloud-based environment. Below are some of the key AI and RPA solutions for the mortgage and housing industry:

Smart document processing: AI-driven intelligent information extraction from various documents such as paystubs, bank or income statements, tax documents, closing disclosures, mortgage and deed of trust documents, and title search packages offers significant efficiency improvements for loan processing, closing and escrow, title settlement, and title production processes. This can significantly improve overall customer experience. EXL XTRAKTO.AI™ solution has been trained for mortgage- and title-specific documents, and has proven to be a great tool for improving efficiency and enabling near-real time processing.
Smart email communication and processing: Implementing API-based, real-time integration with all business partners and housing ecosystem players isn’t always feasible. For example, communications between lenders and certain title companies require email-based workflows at various stages within the escrow and closing process, such as making a scheduling request for closing upon completion of mortgage underwriting. Applying AI or natural language processing (NLP) algorithms can enable automated classification, sensitivity analysis, intent identification and response, and processing. EXL’s Smart Email solution enable automated communication and processing for email traffic much more efficiently and intelligently, requiring human intervention only for exception management. Actions can be taken based on the intent of the email through transaction processing within a line of service or title settlement platforms.
Automated web crawling: In processing mortgages, closing and escrow process and title production, a lot of manual effort is involved in verifying data and extracting documents from external sources such as county websites. Automated web crawling and NLP-based data extraction provides an efficient way to get tax and title data from county sites where necessary. EXL’s configurable web crawling solutions enable such automation, requiring human intervention only for managing exceptions.
Conversational AI for efficient customer and partner engagement: Whether during mortgage processing, closing and escrow, servicing, or default management, clients and partners need direct, intelligent, and efficient conversation that improves engagement. Borrowers, especially millennials, are demanding improved digital engagement with reduced touchpoints, minimal and relevant documentation, and faster closing cycles. It is becoming more and more critical to leverage cognitive chatbots, mobile communication channels, omni-channel integrations, and enhanced contact center performance throughout the customer journey. EXL EXELIA.AI™ provides a common conversational AI solution for chatbot and human-like voice communication channels before handing over to human contact center agents for managing of complex interactions

Important data elements about borrowers, properties, and past loan payment transactions can offer insights that improve client acquisition and retention, speed up mortgage underwriting decisions, and increase the efficiency of title settlement and insurance processes.

b. A need for interconnectivity and real-time communication

The housing ecosystem requires multiple channels of communication between various participants. Lenders need to engage title agents for closing, escrow, or title settlements, and valuation providers for property appraisals. Title agencies work with title insurance companies, real estate agents, and notaries. SFR providers engage with property management firms, and so forth. To ensure a smoother workflow with other industry participants, companies involved in this ecosystem must consider integrated transaction flow between systems. This can be accomplished via an API-based integrations for real-time or near real-time transaction processing.

However, the players within this field are at different digital maturity levels, which complicates establishing a high level of interconnectivity.

c. Using data analytics for intelligent insights

In the housing industry, putting the data to the right use can be valuable in many ways. Important data elements about borrowers, properties, and past loan payment transactions can offer insights that improve client acquisition and retention, speed up mortgage underwriting decisions, and increase the efficiency of title settlement and insurance processes. However, many organizations lack the analytics capabilities to generate these insights. This is often due to data siloes and a lack of data organization. By overcoming these obstacles, businesses can leverage data including:

Customer data: Customer life event data, mortgage payoff patterns, and social media data can offer intelligent insights for acquiring new clients, improving recapture rates, cross-selling products and services, and improving overall customer experiences.
Property and credit data: Title records and customer credit data are used by lenders and title companies to make critical underwriting decisions, as well as during the title production process. Intelligent, proactive insights from this data can significantly increase efficiency for the loan origination and title insurance processes.
Predictive default management: Sophisticated delinquency models can predict which loans have a high likelihood of default with over 95% accuracy levels. Such models utilize historical payment data from millions of external transactions, historical portfolio performances, economic factors, and other data points to proactively plan and action loan modifications or other tasks.
Predictive analytics for demand forecast and capacity planning: Analytical models can provide meaningful insights and forecast demand by products, geographic regions, and timelines of macroeconomic variables and historical channel performance. Historical throughput and capacity data can then be leveraged to proactively plan staffing needs.

Summary

The housing ecosystem involves many players, each with an important role to play. It is critically important for lenders, title companies, and others involved in the industry to leverage data and digital interventions to stay competitive and build a non-linear, scalable operating model that can withstand the cyclic nature of the industry. More importantly, building a connected enterprise that can seamlessly integrate with customers and other business partners can bring significant competitive advantages, improve revenue, and reduce operating cost.

Written by:

Kalpesh Master
Vice President
Banking & Financial Services