The Role of Data Science in Prioritizing FinTech Market Entries
CoreLogic’s Discovery Platform Solves for Data Challenges Industry-Wide
Data science has emerged as the key to fintech and established financial services companies meeting critical business objectives and completing time-sensitive processes more efficiently and affordably.
However, a scarcity of data scientists and the complexity of managing data scattered across multi-cloud and hybrid platforms present challenges for companies looking to harness the full potential of big data and analytics.
Data science is revolutionizing value generation and customer journeys in the fintech and financial services sector. It has emerged as a critical differentiator that enables companies to meet critical business objectives and complete time-sensitive processes—such as credit risk scoring and property value assessments—more efficiently and affordably.
However, a scarcity of data scientists and the complexity of managing data scattered across multi-cloud and hybrid platforms present challenges for companies looking to harness the full potential of big data and analytics. Many leaders are rapidly concluding that simply putting diverse data into cloud environments or data lakes does not automatically lead to the generation of meaningful insights that advance their market positions.
“Extracting value from large data sets is not a simple proposition. It requires sophisticated integration, transformation, enrichment and orchestration that is very difficult to execute across heterogeneous enterprise computing infrastructures. Data scattered across many different locations in various formats create confusing and difficult-to-rationalize environments. Bringing this data together at scale is far from trivial,” explains Mark Weaver, head of real estate tech solutions and data partnerships at CoreLogic, a leading global property information, analytics and data-enabled solutions provider.
Success is Found in the Nuances
Organizational structures and processes established to execute big data analytics strategies are often flawed. Poor design and inappropriate allocation of expertise and resources are common in the industry, leading to outcomes that inhibit return on data science investments.
Adding insult to injury is the nomadic nature of the data science talent pool. Because data scientists and engineers are in such high demand, they often move from one company to another—and from one industry to another—as different organizations bid for their services. As a result, many data scientists and engineers tend to be generalists rather than industry-specific specialists. It presents a major challenge for organizations interested in establishing sophisticated data analytics programs in the property sector.
“Success in data science, predictive modeling, and analytics is often found in the nuances. If you're a data scientist or analyst from the automotive industry and suddenly find yourself in a prop-tech or fintech environment, there is a whole array of industry knowledge that needs to be mastered quickly,” says Heidi Russell, director of strategic accounts at CoreLogic.
Achieving this mastery is difficult when data scientists have a rudimentary understanding of the industry and business leaders lack experience with data-driven decision-making.
“One of the factors missing in the fintech or prop-tech space is a way to upskill data scientists and engineers on industry-specific nuances rapidly. The faster they can be brought up to speed on the intricacies of the new industries they serve, the smoother the path to harnessing their talent to achieve mission-critical objectives,” says Russell.
Discovery Platform from CoreLogic Integrates Data Science and Property Expertise
CoreLogic has developed a new offering called Discovery Platform, which addresses the talent and technology knowledge gap challenging many fintechs, prop-techs and financial service providers (such as mortgage bankers) that require an intimate and ongoing understanding of the constantly changing dynamics of the property sector.
Discovery Platform is a secure, cloud-based platform that allows data scientists from fintech, prop-tech and other sectors to rationalize and analyze their own data in a secure environment optimized for understanding all property data. The offering also allows proprietary data to be compared, contrasted, and mined for insights with the most comprehensive and timely industry-wide data captured by CoreLogic.
“Discovery Platform brings data owned and gathered by our clients together with CoreLogic’s best-in-class market data by leveraging the CoreLogic Integrated Property Identification number (CLIP). The CLIP ID makes it possible to take a vast array of property data sources and connect them to create a single integrated source of truth that data scientists can work with,” says Weaver.
In addition, CoreLogic Discovery provides a workbench that allows data scientists from client organizations to collaborate with CoreLogic data scientists who have extensive experience modeling and analyzing property data. More importantly, CoreLogic Discovery offers tools and resources that automate and accelerate the foundational work that must be performed before effective analysis of large data sets can take place.
“The CoreLogic Discovery platform takes most of the lifting, shifting, cleansing, and data standardization out of the equation. This means data scientists and analysts can focus on the more significant business objectives and solutions to enable the company to meet those objectives,” says Weaver.
“It is a one-stop-shop that enables client-facing data scientists to accelerate and improve their data-driven decision-making processes,” concludes Russell.
To learn more about the Discovery Platform by CoreLogic, visit:
http://www.corelogic.com/discovery-platform