As borrower demands and origination costs are rising, mortgage lenders are turning to data, analytics, and artificial intelligence (AI) in order to make better and faster business decisions. The implementation of AI in mortgage industry will help mortgage lenders to use analytics for making real time operational business decisions such as identifying fraud detection, assessing…
Mortgage lender can infuse every major decision to drive revenue, to control costs or to mitigate risks with data and analytics. Integrated risk management using risk analytics can trigger responsible and profitable growth for mortgage banks. Risk analytics in mortgage banking helps mortgage banks to identify, quantify and mitigate risks using data and analytics. Functional…
Big part of digital transformation in mortgage industry drills down to the number of data driven initiatives by mortgage lenders and banks namely AI/ML efforts, predictive analytics, data modeling and CRMs. Explosive growth in terms of total data volume poses many operational and data challenges in mortgage industry. Data challenges in mortgage industry The total…
Mortgage Banks want to better understand the borrower’s needs, increase their revenue and generate referrals from realtor partners to remain competitive in the mortgage banking domain. Einstein Analytics for Financial Services leverage Salesforce’s complete intelligence platform powered with analytics to help mortgage industry to achieve these goals. Einstein Analytics for Financial Services is a customizable…
While basic versions of analytic solutions focus on building data repositories and reporting, advanced predictive and prescriptive analytics can generate powerful insights. Prescriptive Analytics which use models to specify optimal behaviors and actions can be embedded as a part of real-time decision making process in the mortgage banking domain. Need for Prescriptive Analytics in Mortgage…
A robust and successful Data Analytics functionality encompasses more than a stack of technologies and is incomplete without getting incorporated into all key decisions across origination, sales, marketing, borrower experience and other core functions. So it is necessary to integrate Data Analytics into mortgage banking to aid the decision making process. How to integrate Data…
With rise in origination costs and lead generation costs, Mortgage banks need to optimize their digital marketing efforts to close more loans without increasing their marketing spend. Personalization of digital marketing efforts can go a long way in increasing the marketing efficiency and effectiveness of lead generation techniques. Benefits of personalization in lead generation Personalization…
Mortgage banks have with them a large database of information secured via loan origination platforms, application forms, POS platforms and other website features like contact forms, search patterns. Mortgage Banks by employing the right technology can leverage these existing data sets to gain meaningful insights about borrower behavior, buying patterns, trends, loan product performance and…
Faster and better data driven lending decisions requires timely and accurate information right at the fingertips of LOs and Lenders. Critical business decisions backed by real time data driven approach always prove to be more accurate and effective in the long run. Essential features of a BI dashboards for Mortgage Industry Advantages of BI dashboards…
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