Using Data to Navigate a Path Forward
Getting back to business in a pandemic-impacted landscape will be anything but usual. Banks and insurers can no longer just rely on past trends of one data set to forecast demand and impact. They’ll have to blend a plenitude of data types, including data across multiple systems—such as regulatory reporting data or customer transaction data—and analogous events, such as national unemployment rates, to create a complete picture of the path forward.
For example, Deloitte’s research methodology in their report, “The Path Ahead: Navigating Financial Services Sector Performance Post-COVID-19,” is an example of how blended data creates a big-picture forecast. According to the report, the research team at the Deloitte Center for Financial Services looked at “the statistical relationships among national unemployment rate, the homeowners’ unemployment rate, and the 30-day and 90-day delinquency rates for the past 17 years,” to forecast the impact of the COVID-19 pandemic on mortgage delinquencies from 2020 to 2024.
Likewise, blending data sources across systems and sources is exactly what banks must do to understand and respond to the short- and long-term impact of pandemic-driven behavioral trends. For example, by blending financial data and operational data—such as customer demographic data and FICO scores—banks can identify borrowers more likely to face financial difficulties, and provide those borrowers with personalized loan modifications or other solutions.
Same goes for insurance carriers. Deloitte Insight report researchers gave this advice for workers’ comp insurers to mitigate risks and respond to market shifts: “Carriers should look to shore up their risk-selection standards and pricing models. Underwriting profitability could be paramount to remain viable, particularly in this low interest rate environment, when investment income is likely to be impacted as well.” One way for insurers to measure the effectiveness of their underwriting discipline—the process of evaluating risks, pricing, and coverage—is by analyzing a blend of policy, claims systems, and insurance premiums data, which are coming from a blend of financial and operational systems.
Amid all the uncertainty brought on by the pandemic, one thing is for certain: Staying on the pulse of changing consumer behavior will be a constant need. Banks and insurance companies have the data to understand the short- and long-term impact of disruptions, and with the right technology capabilities, they can blend operational and finance data for the insights to do more than move forward—they can blaze their own trail.
Learn more from Workday customer Federal Home Loan Bank of Dallas (FHLB Dallas) about how unlocking financial insights drives more confident decision-making.
To learn more, read part two in this series: "It’s All in the Details: How Data-Rich Subledgers Fuel Financial Agility."