5 Reasons Why the Mortgage Industry Needs Smart Data Fabrics

5 Reasons Why the Mortgage Industry Needs Smart Data Fabrics

Nexval Infotech

Nexval Infotech

The financial services sector – particularly mortgage – has a long history of relying on data for decision-making and business processes. From assessing the risk level of a loan applicant to maintaining property records and adhering to title process rules, nearly every step of the mortgage value chain leverages data. Yet, most of these processes are stuck in a legacy era, riddled by silos and inefficiencies, without a unifying thread across the enterprise such as a centralized data fabric.

An Ellie Mae report published in 2020 found that mortgage businesses lag woefully behind in data and analytics maturity. Most (37%) have just begun their journey, and only 3% have achieved the maturity needed for predictive analysis – for example, auto-recommending a mortgage product based on a set of predetermined factors and borrower behavior. Less than a quarter of lenders are able to detect patterns and trends using data.

This inability to mobilize and monetize information (although so much of it is available to mortgage businesses today), is due to data silos and the lack of a coherent data strategy. Indeed, nearly 2 in 5 lenders are unsure of their total investment in data and analytics, which reflects the larger confusion around this space. Smart data fabrics can be a solution to this problem as they provide your company with a clear, unified, and pragmatic roadmap for data-driven processes – aided by automation and the removal of silos.

Also read: Can Mortgage Automation Help Detect and Prevent Fraud in 2022?

What Does a Smart Data Fabric Mean for the Mortgage Industry?

A smart data fabric can be defined as a set of tools, technologies, and software that eliminate data silos in a business and connect the various sources of information spread across data warehouses, data lakes, data marts, etc., putting in place controls that you can use to govern the data and convert it into analytical insights. Smart data fabrics take data from being an isolated digital asset in the hands of one stakeholder or business unit to being a value generator for the enterprise.

Across industries, a smart data fabric will have the following key features:

  • Integrations and connectors to unify the touchpoints where data is generated and stored
  • Metadata management, with automated discovery, classification, organization, and analytics
  • Security and governance features for data compliance as per industry laws
  • Data quality assurance through deduplication, cleansing, etc.

On top of these core capabilities, mortgage businesses can add on features relevant to their own domain. For example, it may be possible to connect the data fabric with an AI-enabled document management solution so that the rules contained within the data fabric can help check documents in a dynamic and auto-updated manner.

Also read: Leveraging Hyperautomation to Transform Mortgage Processes: A Quick Primer

5 Reasons Why Mortgage Businesses Need a Smart Data Fabric

Mortgage companies can benefit from data fabrics in the following ways:

1. Stay ahead of increasing silos

Silos have always been a major problem for the financial services sector, primarily due to the laws and complexities around data sharing. With the rise of new digital technologies, the problem has only gotten worse – with every new digital transformation project, the lender adds on a fresh data system, which could be an additional cloud service, a risk management platform, an LOS, etc. A smart data fabric in mortgage allows you to stay a step ahead of silo risk by proactively integrating new systems into a consolidated framework.

2. Minimize the risk of non-compliance

When data exists in multiple disparate systems, there is always a risk of non-compliance due to the lack of oversight. For example, let’s say a borrower record exists in two copies on two different cloud platforms. It may be destroyed on one platform as per your region’s data retention laws, but may continue to be available on the other platform, inadvertently causing non-compliance. A smart data fabric removes duplication and other data quality issues to reduce such operational risks.

3. Support prescriptive analytics

Another reason why mortgage businesses need a smart data fabric is to support prescriptive analytics. Mortgage data analytics can be of four types – descriptive, diagnostic, predictive, and prescriptive. These help to obtain facts about business operations, diagnose the reasons behind them, identify future trends, and prescribe the next steps, respectively. 73% of mortgage businesses are stuck in the first two types of analytics and smart data fabrics can provide the baseline information necessary for grayer maturity.

4. Lay the foundation for sophisticated AI

Artificial intelligence (AI) is now a revolutionary force in the mortgage sector. At a basic level, it enables high-volume data processing and automated manual tasks like chatting with customers or screening documents. Since 2020, large organizations like Freddie Mac have started testing AI-based applicant screening models. The next step is to develop generative AI and individual AI, which can mimic human cognition even in highly complex scenarios. All of this requires a massive repository of high-quality data, which is only possible through smart data fabrics in mortgages.

5. Avoid vendor lock-in

Finally, one of the most important benefits of smart data fabrics in mortgages is that they reduce the risk of vendor lock-in to a significant extent. A data fabric essentially deploys an end-to-end, organization-wide solution that can incorporate or remove data origination/storage systems in a modular manner. It is highly scalable to meet your business needs. This reduces the dependence on a single technology vendor to power data systems thanks to a centralized unifying fabric.

Also read: Top Tech Trends Reshaping the Mortgage Industry in 2022: A Definitive Guide

Getting Started with Smart Data Fabrics

There are three ways to get started with data fabrics. The mortgage business could design and build its own solution, from scratch, using a custom architecture and homegrown or open-source connectors. It is highly intensive in terms of technical know-how and efforts but provides maximum flexibility and control. Or, you could purchase and deploy a ready-to-use solution like Google Dataplex, Azure Data Factory, etc. this is technically less challenging but does not tailor the solution for mortgage-specific business processes.

Finally, you could partner with a proven mortgage technology specialist with data fabric expertise and industry understanding. This ensures the solution meets mortgage business needs while minimizing your in-house efforts and overheads. To learn how our team of 1000+ SMEs could help kickstart your data fabric adoption journey, talk to our Tech Gurus today!

Frequently Asked Questions About Smart Data Fabrics

Q1. How can smart data fabrics be used?

Smart data fabrics are the future of data management. There are many use cases of smart data fabrics for mission-critical initiatives, like regulatory compliance, wealth management, and enterprise risk and liquidity management.

Q2. What are the core capabilities of a smart data fabric?

A smart data fabric has several analytical capabilities like business intelligence, machine learning, natural language processing, and data exploration that help in gaining new insights.

Q3. What are the best practices of data management in the mortgage industry?

Data management to critical to every business and mortgage business are no exception. Originators and servicers can follow some vital steps for ensuring successful data management. The best practices include digitization of data, creation of efficient data storage solutions (like, cloud storage), conducting periodic data audits for higher accuracy, and automating the document management process.

Nexval Infotech

About the author

{"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}