Tag: data analytics
Fintech analytics transforms fragmented data into real-time decisioning power, helping lenders manage risk and earn consumer trust.
Prescreen targeting solutions have evolved significantly, offering a competitive edge through more precise and impactful outreach strategies.
Seamless financial services onboarding requires organizations to enhance their identity verification methods.
Companies depend on quality information to make decisions that move their business objectives forward while minimizing risk exposure. And in today’s modern, tech-driven, innovation-led world, there’s more information available than ever before. Expansive datasets from sources, both internal and external, allow decision-makers to leverage a wide range of intelligence to fuel how they plan, forecast and set priorities. But how can business leaders be sure that their data is as robust, up-to-date and thorough as they need — and, most importantly, that they’re able to use it to its fullest potential? That’s where the power of advanced analytics comes in. By making use of cutting-edge datasets and analytics insights, businesses can stay on the vanguard of business intelligence and ahead of their competitors. What is advanced analytics? Advanced analytics is a form of business intelligence that takes full advantage of the most modern data sources and analytics tools to create forward-thinking analysis that can help businesses make well-informed, data-driven decisions that are tailored to their needs. Simply put, advanced analytics is an essential component of any proactive business strategy that aims to maximize the future potential of both customers and campaigns. These advanced business intelligence and analytics solutions help leaders make profitable decisions no matter the state of the current economic climate. They use both traditional and non-traditional data sources to provide businesses with actionable insights in the formats best suited to their needs and goals. One key aspect of advanced analytics is the use of AI analytics solutions. These efficient and effective tools help businesses save time and money by harnessing the power of cutting-edge technologies and deploying them in optimal use-case scenarios. These AI and machine-learning solutions use a wide range of tools, such as neural network methodologies, to help organizations optimize their allocation of resources, expediting and automating some processes while creating valuable insights to help human decision-makers navigate others. Benefits of advanced analytics Traditional business intelligence tends to be limited by the scope and quality of available data and ability of analysts to make use of it in an effective, comprehensive way. Modern business intelligence analytics, on the other hand, integrates machine learning and analytics to maximize the potential of data sets that, in today's technology-driven world, are often overwhelmingly large and complex: think not just databases of customer decisions and actions but behavioral data points tied to online and offline activity and the internet of things. What's more, advanced analytics does this in a way that's accessible to an entire organization — not just those who know their way around data, like IT departments and trained analysts. With the right advanced analytics solution, decision-makers can access convenient cloud-based dashboards designed to give them the information they want and need — with no clutter, noise or confusing terminology. Another key advantage of advanced analytics solutions is that they don't just analyze data — they optimize it, too. Advanced analytics offers the ability to clean up and integrate multiple data sets to remove duplicates, correct errors and inaccuracies and standardize formats, leading to high-quality data that creates clarity, not confusion. The result? By analyzing and identifying relationships across data, businesses can uncover hidden insights and issues. Advanced analytics also automate some aspects of the decision-making process to make workflows quicker and nimbler. For example, a business might choose to automate credit scoring, product recommendations for existing customers or the identification of potential fraud. Reducing manual interventions translates to increased agility and operational efficiency and, ultimately, a better competitive advantage. Use cases in the financial services industry Advanced analytics gives businesses in the financial world the power to go deeper into their data — and to integrate alternative data sources as well. With predictive analytics models, this data can be transformed into highly usable, next-level insights that help decision-makers optimize their business strategies. Credit risk, for instance, is a major concern for financial organizations that want to offer customers the best possible options while ensuring their credit products remain profitable. By utilizing advanced analytics solutions combined with a broad range of datasets, lenders can create highly accurate credit risk scores that forecast future customer behavior and identify and mitigate risk, leading to better lending decisions across the credit lifecycle. Advanced analytics solutions can also help businesses problem-solve. Let's say, for instance, that uptake of a new loan product has been slower than desired. By using business intelligence analytics, companies can determine what factors might be causing the issue and predict the tweaks and changes they can make to improve results. Advanced analytics means better, more detailed segmentation, which allows for more predictive insights. Businesses taking advantage of advanced analytics services are simply better informed: not only do they have access to more and better data, but they're able to convert it into actionable insights that help them lower risk, better predict outcomes, and boost the performance of their business. How we can help Experian offers a wide range of advanced analytics tools aimed at helping businesses in all kinds of industries succeed through better use of data. From custom machine learning models that help financial institutions assess risk more accurately to self-service dashboards designed to facilitate more agile responses to changes in the market, we have a solution that's right for every business. Plus, our advanced analytics offerings include a vast data repository with insights on 245 million credit-active individuals and 25 million businesses, as well as the industry's largest alternative data set from non-traditional lenders. Ready to explore? Click below to learn about our advanced analytics solutions. Learn more
Learn how AI analytics helps lenders improve their underwriting.
Learn how high-quality data from multiple data sources can help drive business growth.
With an ever-present need for efficiency, security, and seamless citizen services, many agencies are looking at the benefits of a data-driven government. Last year, the federal government kicked off a unified effort to enable data-driven decision making. The goal at that level – and across all agencies – is to serve citizens more efficiently and effectively. By embracing the power of data and analytics, agencies of all sizes can set themselves up to better serve their citizens. What is a data-driven government? Agencies collect citizen data from a variety of service-based sources, including the Postal Service, Census Bureau, social welfare departments, and agencies that issue government IDs. When properly leveraged, this data holds many possibilities. However, many agencies face challenges when it comes to efficient collection, sharing, usage, integrity, and accessibility. Due to the amount of data collected and the potential lack of consistency in the collection and storage techniques, the data may not be usable. Without proper management and analysis, there’s little government agencies can do with their data to improve their processes. A data-driven government has well-managed data and uses that data to drive their decisions as they relate to citizen requests for benefits, tax collection, elections, and more. What are the benefits of data-driven decision making? Data management and government data analytics enable agencies to react quickly to citizen demands and concerns and proactively anticipate an issue before it becomes a crisis. With the right tools, agencies can gain a holistic view of their citizens, communicate effectively internally, provide digitally-driven services and improve overall efficiency through government-wide data integration and management. These changes have a wide range of benefits, including reduction of cost, fraud, waste and abuse, the automation of manual processes, and better service delivery. Why is a data-driven strategy required? In addition to the benefits listed above, a data-driven strategy also helps agencies align with published NIST guidelines and the need to monitor, evaluate, and maintain digital identity systems. Proper use of data-driven digital identity strategies will enhance equity and the usability of the solutions agencies provide to their citizens. Building an effective data-driven strategy The right strategy starts with ensuring that all departments about the need for proper data management and analytics and the guidelines that will govern it, such as maintaining up-to-date data, removing silos, and leveraging the right tools. The next step is finding the right partner. An effective partner can help agencies develop and maintain data management systems and implement the right tools and analytics – things like machine learning in government – to help each agency function efficiently and safeguard the data of its citizens. To learn how Experian can help your agency improve its use of data, visit us or request a call. Visit us
CrossCore named Overall Leader, Product Leader in Fraud Reduction Intelligence Platforms, Innovation Leader and Market Leader in Fraud Reduction..
Business leaders accross industries are using predictive analytics to make informed decisions.
Learn how Washington State Employees Credit Union increased their revenue and member satisfaction by implementing a digital prequalification process.
Discover the dos and don’ts when it comes to implementing a successful strategy for income and employment verification for mortgage. Read more!
Experian created the 2022 Future of Fraud Forecast to help businesses anticipate and prevent new fraud trends in the year ahead.
Incorporating artificial intelligence and machine learning into your business strategy can improve decisioning and reduce risk. Read more.
Underreported income is a significant budget complication that can frustrate even the most effective tax agencies, until the right tools are used.
Learn about some specific Experian solutions that are especially timely for lenders strategizing their response to the COVID Recession.