Scope of the Report
The report titled ˝The US SaaS Mortgage Software Market: Size, Trends & Forecasts (2017-2021)ţ, provides an in-depth analysis of the US SaaS mortgage market opportunity by value. The report also gives an insight of the global SaaS software market and the share of the US in same.
The report also includes the analysis of the US total production expenses per loan and non-personnel expenses per loan.
It assesses the key opportunities in the market and outlines the factors that are and will be driving the growth of the industry. Growth of the overall US Saas Mortgage Software market has also been forecasted for the period 2017-2021, taking into consideration the previous growth patterns, the subprime lending crisis of 2008-2009, the growth drivers and the current and future trends. The competition in the US SaaS Mortgage Software market is fragmented. However Ellie Mae dominates the market.
Further, key players of the US SaaS Mortgage Software Market, Ellie Mae, Black Knight Financial Services, Inc., Accenture and Wipro are also profiled with their financial information and respective business strategies.
Ellie Mae, Inc.
Black Knight Financial Services, Inc.
The collateral that is kept while initiating a loan for the purchase of real estate or property or a house is known as mortgage. The banks or the mortgage lenders loan a large chunk of money that is around 80% of the price of home that the borrower is required to pay back with interest over a set period of time. On failure of repaying the loan, the lender takes the mortgage through a legal process known as foreclosure.
The mortgage origination process has slightly changed over the decades. The technology penetration into mortgage institutions is considered of significance increasingly.
The loan servicing software therefore helps the banks, wholesale lenders, commercial finance, and specialty lenders to manage all types of instalment loans, notes, contracts, mortgages, and deeds of trust, as well as some clients and contracts. Loan servicing software automates the loan decisions and plays an important role in increasing the speed of service and borrower satisfaction.
The loan servicing software are of two types: the in-house or the on-premise server and cloud based server.
The cloud-based software is secured on the host company═s server. The software and the server are managed at one place. The data and the software both are located on cloud. The data is accessible from anywhere to the mortgage lender.
The Saas software in mortgage enables the customers to utilize a seamless workflow across point-of-sale, processing, underwriting, closing and funding, post-closing, shipping, delivery and CRM requirements. Such solutions serve all the players in the loan origination market from borrowers to lenders to investors.
The US SaaS Mortgage Software market is expected to increase at a significant CAGR during the years 2017-2021. The SaaS mortgage software market is expected to increase due to growth in network effect, increase in employment levels in the US, etc. Yet the market faces some challenges such as, need for data security, risks associated with SaaS offerings, compliance regulations, etc.
1. Executive Summary
2.1 Mortgage Industry: An Overview
2.1.1 History of Mortgages
2.1.2 The Emerging Future of Mortgage Origination
2.1.3 Technology in Mortgage
2.2 Cloud Computing: An Overview
2.2.1 Cloud Computing on the Basis of Service
2.2.2 Software-as-a Service (SaaS) Software
2.3 Loan Servicing Software: An Overview
2.3.1 Advantages/Features of Loan Servicing Software
2.3.2 Types of Loan Servicing Software
2.3.3 Types of Loan Servicing Software: A Comparison
2.3.4 SaaS Mortgage Software
2.3.5 Working of SaaS Mortgage Software
3. Market Analysis
3.1 Global SaaS Market: An Analysis
3.1.1 Global SaaS Market by Value and by Geography
3.2 The US SaaS Mortgage Software Market: An Analysis
3.2.1 The US Total Production Expenses per Loan
3.2.2 The US Total Production Expenses per Loan by Segments
3.2.3 The US Personnel Expenses per Loan
3.2.4 The US Non-Personnel Expenses per Loan
3.2.5 The US SaaS Mortgage Software Addressable Market by Value
4. Market Dynamics
4.1 Growth Driver
4.1.1 Declining US Unemployment Rate
4.1.2 Rising US Urban Population
4.1.3 Increasing Network Effect
4.2.1 Increasing US Mortgage Rates
4.2.2 Decline in Mortgage Lending Volume and Increase in Nominal House Prices
4.2.3 Need to Comply with Multiple Regulations
4.2.4 Sensitive to Economic Fluctuations
4.3 Market Trends
4.3.1 Consistent US Home Ownership Rate
4.3.2 Increasing Number of Active Users of Ellie Mae
4.3.3 Decrease in Refinance Mortgage Originations
4.3.4 Minimum Costs
4.3.5 Increased Investments in the Software
4.3.6 The US Mortgage Origination Composite Forecasts
5. Competitive Landscape
5.1 The US SaaS Mortgage Software Players: A Comparison
6. Company Profile
6.1 Ellie Mae
6.1.1 Business Overview
6.1.2 Financial Overview
6.1.3 Business Strategy
6.2 Black Knight Financial Services, Inc.
6.2.1 Business Overview
6.2.2 Financial Overview
6.2.3 Business Strategy
6.3.1 Business Overview
6.3.2 Financial Overview
6.3.3 Business Strategy
6.4.1 Business Overview
6.4.2 Financial Overview
6.4.3 Business Strategy
List of Figures
Figure 1: Desired Attributes and Technology-Enabled Capabilities
Figure 2: Cloud Computing on the Basis of Service
Figure 3: Advantages/Features of Loan Servicing Software
Figure 4: Types of Loan Servicing Software
Figure 5: Types of Loan Servicing Software: A Comparison
Figure 6: Global SaaS Market by Value; 2016-2021 (US$ Billion)
Figure 7: Global SaaS Market by Geography; 2016 (Percentage, %)
Figure 8: The US Total Production Expenses per Loan; 2012-2016 (US$)
Figure 9: The US Total Production Expenses per Loan by Segments; 2016 (Percentage, %)
Figure 10: The US Personnel Expenses per Loan; 2012-2016 (US$)
Figure 11: The US Non-Personnel Expenses per Loan; 2012-2016 (US$)
Figure 12: The US SaaS Mortgage Software Addressable Market; 2010-2016 (US$ Billion)
Figure 13: The US SaaS Mortgage Software Addressable Market; 2017-2021 (US$ Billion)
Figure 14: The US Unemployment Rate; 2009-2014 (Percentage, %)
Figure 15: The US Urban Population; 2009-2015 (Million)
Figure 16: The US Mortgage Rate; 2012-2017 (Percentage, %)
Figure 17: Gross New Mortgage Lending; 2009-2017 (Volume Index)
Figure 18: Nominal House Prices; 2009-2017 (Price Index)
Figure 19: The US Home Ownership Rate; 2012-2017 (Percentage, %)
Figure 20: Number of Active Users of Ellie Mae; 2013-2020 (Million)
Figure 21: The US Mortgage Originations and Refinance Share; 2009-2018
Figure 22: Ellie Revenues; 2012-2016 (U$ Million)
Figure 23: Ellie Revenue by Type; 2016
Figure 24: Black Knight Revenues; 2012-2016 (US$ Million)
Figure 25: Black Knight Revenues by Segments; 2016
Figure 26: Accenture Net Revenues; 2012-2016 (US$ Billion)
Figure 27: Accenture Net Revenues by Operating Groups; 2016
Figure 28: Accenture Net Revenues by Type of Work; 2016
Figure 29: Wipro Revenues; 2012-2016 (US$ Million)
Figure 30: Wipro Revenue by Segments; 2016
Table 1: The US Mortgage Origination Composite Forecasts
Table 2: The US SaaS Mortgage Software Players: A Comparison
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.