Automation & Technology
The big deal about Big Data
“If you are not working on implementing data & analytics technology, you are fighting an uphill battle.” –CTO, Leading National Lender
Any sports fan can appreciate the value of data and analytics. Baseball, in particular, utilizes statistical data constantly, from player evaluations to in-game decisions. For instance, when the team on defense moves to an “infield shift” position, they use accumulated data on where the batter typically hits balls, and place their players in strategic positions to make an out. Similarly, in business, data analysis increases an organization’s ability to extract meaningful insights from their data and make more informed decisions.
Currently, the residential mortgage industry is in different stages of the data journey. Savvy lenders have embarked on this journey, while others have yet to take the first steps. In any case, proper use of data and analytics is now a strategic imperative, which involves a distinctive cultural shift and commitment from the very top of an organization.
Ellie Mae recently conducted a survey of mortgage lender executives to gain insights on the adoption and utilization of data analytics solutions. The findings from this survey were used to create an eBook, entitled “The Big Data Revolution: Helping Lenders Make Better Business Decisions to Drive Past the Competition”.
This eBook highlights the importance of using data and analytics tools to become more operationally efficient. These tools help lenders process loans faster, control costs, identify and mitigate risks, establish repeatable and measurable processes, and uncover new business opportunities. Data-wise lenders can also increase their throughput, and then reinvest the cost savings into people and processes that enable them to manage an even higher loan volume.
The data maturity model
The level of advancement in an organization’s data practice is referred to as data maturity. When used properly, data helps lenders grow their business and become more operationally efficient. As organizations develop their use of data, and improve their adoption of advanced analytics, they progress through the following four stages of data maturity:
- Descriptive: The foundational level that helps lenders understand what has already occurred.
- Analytical: Using additional data sources, lenders gain a bigger picture into why their business is trending one way or another.
- Predictive: Lenders begin to recognize patterns and detect meaningful trends.
- Prescriptive: Once trends and related outcomes are understood, lenders can make more informed decisions related to the entire loan production process.
Best practices that work
No matter where your organization is on its data journey, the following best practices can help advance your data and analytics strategy:
- Recruit a C-level sponsor within the organization so initiatives are properly resourced and prioritized.
- Invest in team and technology to ensure that you have people with the right skills to use, manage, and customize your technology tools.
- Go beyond technology, and pay attention to internal cultural changes and your employees’ ongoing training needs.
- Ease implementation by creating a common data model and data reporting approval process.
- Implement governance policies and procedures that will deliver repeatable and predictable results.
There’s much more to learn, so download the eBook now to gain additional insights.