Loading...

Four Features You Need in an Analytical Environment

Published: October 24, 2018 by Jesse Hoggard

Big Data AnalyticsI believe it was George Bernard Shaw that once said something along the lines of, “If economists were laid end-to-end, they’d never come to a conclusion, at least not the same conclusion.”

It often feels the same way when it comes to big data analytics around customer behavior. As you look at new tools to put your customer insights to work for your enterprise, you likely have questions coming from across your organization.

Models always seem to take forever to develop, how sure are we that the results are still accurate? What data did we use in this analysis; do we need to worry about compliance or security?

To answer these questions and in an effort to best utilize customer data, the most forward-thinking financial institutions are turning to analytical environments, or sandboxes, to solve their big data problems. But what functionality is right for your financial institution?

In your search for a sandbox solution to solve the business problem of big data, make sure you keep these top four features in mind.

  1. Efficiency: Building an internal data archive with effective business intelligence tools is expensive, time-consuming and resource-intensive. That’s why investing in a sandbox makes the most sense when it comes to drawing the value out of your customer data.By providing immediate access to the data environment at all times, the best systems can reduce the time from data input to decision by at least 30%. Another way the right sandbox can help you achieve operational efficiencies is by direct integration with your production environment. Pretty charts and graphs are great and can be very insightful, but the best sandbox goes beyond just business intelligence and should allow you to immediately put models into action.
  2. Scalability and Flexibility: In implementing any new software system, scalability and flexibility are key when it comes to integration into your native systems and the system’s capabilities. This is even more imperative when implementing an enterprise-wide tool like an analytical sandbox. Look for systems that offer a hosted, cloud-based environment, like Amazon Web Services, that ensures operational redundancy, as well as browser-based access and system availability.The right sandbox will leverage a scalable software framework for efficient processing. It should also be programming language agnostic, allowing for use of all industry-standard programming languages and analytics tools like SAS, R Studio, H2O, Python, Hue and Tableau. Moreover, you shouldn’t have to pay for software suites that your analytics teams aren’t going to use.
  3. Support: Whether you have an entire analytics department at your disposal or a lean, start-up style team, you’re going to want the highest level of support when it comes to onboarding, implementation and operational success. The best sandbox solution for your company will have a robust support model in place to ensure client success. Look for solutions that offer hands-on instruction, flexible online or in-person training and analytical support. Look for solutions and data partners that also offer the consultative help of industry experts when your company needs it.
  4. Data, Data and More Data: Any analytical environment is only as good as the data you put into it. It should, of course, include your own client data. However, relying exclusively on your own data can lead to incomplete analysis, missed opportunities and reduced impact. When choosing a sandbox solution, pick a system that will include the most local, regional and national credit data, in addition to alternative data and commercial data assets, on top of your own data.The optimum solutions will have years of full-file, archived tradeline data, along with attributes and models for the most robust results. Be sure your data partner has accounted for opt-outs, excludes data precluded by legal or regulatory restrictions and also anonymizes data files when linking your customer data. Data accuracy is also imperative here. Choose a big data partner who is constantly monitoring and correcting discrepancies in customer files across all bureaus. The best partners will have data accuracy rates at or above 99.9%.

Solving the business problem around your big data can be a daunting task. However, investing in analytical environments or sandboxes can offer a solution. Finding the right solution and data partner are critical to your success.

As you begin your search for the best sandbox for you, be sure to look for solutions that are the right combination of operational efficiency, flexibility and support all combined with the most robust national data, along with your own customer data.

Are you interested in learning how companies are using sandboxes to make it easier, faster and more cost-effective to drive actionable insights from their data? Join us for this upcoming webinar.

Register for the Webinar

Related Posts

Using AI in debt collection can help financial institutions leverage technology to ensure more accurate and timely collections.

Published: January 14, 2025 by Brian Funicelli

Learn how background screeners can optimize pre-employment verification processes, reduce fraud risks, and ensure compliance.

Published: December 12, 2024 by Theresa Nguyen

We are squarely in the holiday shopping season. From the flurry of promotional emails to the endless shopping lists, there are many to-dos and even more opportunities for financial institutions at this time of year. The holiday shopping season is not just a peak period for consumer spending; it’s also a critical time for financial institutions to strategize, innovate, and drive value. According to the National Retail Federation, U.S. holiday retail sales are projected to approach $1 trillion in 2024, , and with an ever-evolving consumer behavior landscape, financial institutions need actionable strategies to stand out, secure loyalty, and drive growth during this period of heightened spending. Download our playbook: "How to prepare for the Holiday Shopping Season" Here’s how financial institutions can capitalize on the holiday shopping season, including key insights, actionable strategies, and data-backed trends. 1. Understand the holiday shopping landscape Key stats to consider: U.S. consumers spent $210 billion online during the 2022 holiday season, according to Adobe Analytics, marking a 3.5% increase from 2021. Experian data reveals that 31% of all holiday purchases in 2022 occurred in October, highlighting the extended shopping season. Cyber Week accounted for just 8% of total holiday spending, according to Experian’s Holiday Spending Trends and Insights Report, emphasizing the importance of a broad, season-long strategy. What this means for financial institutions: Timing is crucial. Your campaigns are already underway if you get an early start, and it’s critical to sustain them through December. Focus beyond Cyber Week. Develop long-term engagement strategies to capture spending throughout the season. 2. Leverage Gen Z’s growing spending power With an estimated $360 billion in disposable income, according to Bloomberg, Gen Z is a powerful force in the holiday market​. This generation values personalized, seamless experiences and is highly active online. Strategies to capture Gen Z: Offer digital-first solutions that enhance the holiday shopping journey, such as interactive portals or AI-powered customer support. Provide loyalty incentives tailored to this demographic, like cash-back rewards or exclusive access to services. Learn more about Gen Z in our State of Gen Z Report. To learn more about all generations' projected consumer spending, read new insights from Experian here, including 45% of Gen X and 52% of Boomers expect their spending to remain consistent with last year. 3. Optimize pre-holiday strategies Portfolio Review: Assess consumer behavior trends and adjust risk models to align with changing economic conditions. Identify opportunities to engage dormant accounts or offer tailored credit lines to existing customers. Actionable tactics: Expand offerings. Position your products and services with promotional campaigns targeting high-value segments. Personalize experiences. Use advanced analytics to segment clients and craft offers that resonate with their holiday needs or anticipate their possible post-holiday needs. 4. Ensure top-of-mind awareness During the holiday shopping season, competition to be the “top of wallet” is fierce. Experian’s data shows that 58% of high spenders shop evenly across the season, while 31% of average spenders do most of their shopping in December​. Strategies for success: Early engagement: Launch educational campaigns to empower credit education and identity protection during this period of increased transactions. Loyalty programs: Offer incentives, such as discounts or rewards, that encourage repeat engagement during the season. Omnichannel presence: Utilize digital, email, and event marketing to maintain visibility across platforms. 5. Combat fraud with multi-layered strategies The holiday shopping season sees an increase in fraud, with card testing being the number one attack vector in the U.S. according to Experian’s 2024 Identity and Fraud Study. Fraudulent activity such as identity theft and synthetic IDs can also escalate​. Fight tomorrow’s fraud today: Identity verification: Use advanced fraud detection tools, like Experian’s Ascend Fraud Sandbox, to validate accounts in real-time. Monitor dormant accounts: Watch these accounts with caution and assess for potential fraud risk. Strengthen cybersecurity: Implement multi-layered strategies, including behavioral analytics and artificial intelligence (AI), to reduce vulnerabilities. 6. Post-holiday follow-up: retain and manage risk Once the holiday rush is over, the focus shifts to managing potential payment stress and fostering long-term relationships. Post-holiday strategies: Debt monitoring: Keep an eye on debt-to-income and debt-to-limit ratios to identify clients at risk of defaulting. Customer support: Offer tailored assistance programs for clients showing signs of financial stress, preserving goodwill and loyalty. Fraud checks: Watch for first-party fraud and unusual return patterns, which can spike in January. 7. Anticipate consumer trends in the New Year The aftermath of the holidays often reveals deeper insights into consumer health: Rising credit balances: January often sees an uptick in outstanding balances, highlighting the need for proactive credit management. Shifts in spending behavior: According to McKinsey, consumers are increasingly cautious post-holiday, favoring savings and value-based spending. What this means for financial institutions: Align with clients’ needs for financial flexibility. The holiday shopping season is a time that demands precise planning and execution. Financial institutions can maximize their impact during this critical period by starting early, leveraging advanced analytics, and maintaining a strong focus on fraud prevention. And remember, success in the holiday season extends beyond December. Building strong relationships and managing risk ensures a smooth transition into the new year, setting the stage for continued growth. Ready to optimize your strategy? Contact us for tailored recommendations during the holiday season and beyond. Download the Holiday Shopping Season Playbook

Published: November 22, 2024 by Stefani Wendel

Subscribe to our blog

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Subscribe to our Experian Insights blog

Don't miss out on the latest industry trends and insights!
Subscribe