Tag: Decisioning as a Service

To drive profitable growth and customer retention in today’s highly competitive landscape, businesses must create long-term value for consumers, starting with their initial engagement. A successful onboarding experience would encourage 46% of consumers1 to increase their investments in a product or service. While many organizations have embraced digital transformation to meet evolving consumer demands, a truly exceptional onboarding experience requires a flexible, data-driven solution that ensures each step of customer acquisition in financial services is as quick, seamless, and cohesive as possible. Otherwise, financial institutions may risk losing potential customers to competitors that can offer a better experience. Here are some of the benefits of implementing a flexible, data-driven decisioning platform: Greater efficiency From processing a consumer’s application to verifying their identity, lenders have historically completed these tasks manually, which can add days, if not weeks, to the onboarding process. Not only does this negatively impact the customer experience, but it also takes resources away from other meaningful work. An agile decisioning platform can automate these tedious tasks and accelerate the customer onboarding process, leading to increased efficiency, improved productivity, and lower acquisition costs2. Reduced fraud and risk Onboarding customers quickly is just as important as ensuring fraudsters are stopped early in the process, especially with the rise of cybercrime. However, only 23% of consumers are very confident that companies are taking steps to secure them online. With a layered digital identity verification solution, financial institutions can validate and verify an applicant’s personal information in real time to identify legitimate customers, mitigate fraud, and pursue growth confidently. Increased acceptance rates Today’s consumers demand instant responses and easy experiences when engaging with businesses, and their expectations around onboarding are no different. Traditional processes that take longer and require heavy documentation, greater amounts of information, and continuous back and forth between parties often result in significant customer dropout. In fact, 40% of digital banking consumers3 abandon opening an account online due to lengthy applications. With a flexible solution powered by real-time data and cutting-edge technology, financial institutions can reduce this friction and drive credit decisions faster, leading to more approvals, improved profitability, and higher customer satisfaction. Having a proper customer onboarding strategy in place is crucial to achieving higher acceptance and retention rates. To learn about how Experian can help you optimize your customer acquisition strategy, visit us and be sure to check out our latest infographic. View infographic Visit us 1 The Manifest, Customer Onboarding Strategy: A Guide to Retain Customers, April 2021. 2 Deloitte, Inside magazine issue 16, 2017. 3 The Financial Brand, How Banks Can Increase Their New Loan Business 100%, 2021.

Call it big data, smart data or evidence-based decision-making. It’s not just the latest fad, it’s the future of how business will be guided and grow. Here are a few telling stats that show data is exploding and a new age is upon us: Data is growing faster than ever before, and we’re on track to create about 1.7 megabytes of new information per person every second by 2020. The social universe—which includes every digitally connected person—doubles in size every two years. By 2020, it will reach 44 zettabytes or 44 trillion gigabytes, according to CIO. In 2015, more than 1 billion people used Facebook and sent an average of 31.25 million messages and viewed 2.77 million videos each minute. More than 100 terabytes of data is uploaded daily to the social channel. By 2020, more than 6.1 billion smartphone users will exist globally. And there will be more than 50 billion smart connected devices in the world, all capable of collecting, analyzing and sharing a wealth of data. More than one-third of all data will pass through or exist in the cloud by 2020. The IDC estimates that by 2020, business transactions on the internet—business-to-business and business-to-consumer—will reach 450 billion per day. All of this new data means we’ll be looking at a whole new set of possibilities and a new level of complexity in the years ahead. The data itself is of great value, however, lenders need the right automated decisioning platform to store, collect, quickly process and analyze the volumes of consumer data to gain accurate consumer stories. While lenders don’t necessarily need to factor in decisioning on social media uploads and video views, there is an expectation for immediacy to know if a consumer is approved, denied or conditioned. Online lenders have figured out how to quickly capture and understand big data, and are expected to account for $122 billion in lending by 2020. This places more pressure on banks and credit unions to enhance their technology to cut down on loan approval times and move away from various manual touch points. Critics of automated decisioning solutions used in lending cite compliance issues, complacency by lenders and lack of human involvement. But a robust platform enables lenders to improve and supplement their current decisioning processes because it is: Agile: Experian hosts our client’s solutions and decisioning strategies, so we are able to make and deploy changes quickly as the needs of the market and business change, and deliver real-time instant decisions while a consumer is at the point of sale. A hosted environment also means reduced implementation timelines, as no software or hardware installation is required, allowing lenders to recognize value faster. A data work horse: Internal and external data can be pulled from multiple sources into a lender’s decisioning model. Lenders may also access an unlimited number of scores and attributes—including real-time access to credit bureau data—and integrate third-party data sources into the decisioning engine. Powerful: A robust decision engine is capable of calculating numerous predictive attributes and custom scoring models, and can also test new strategies against current decision models or perform “what if” simulations on historical data. Data collection, storage and analysis are here to stay. As will be the businesses which are savvy enough to use a solution that can find opportunities and learnings in all of that complex data, quickly curate the best possible actions to take for positive outcomes, and allow lenders and marketers to execute on those recommendations with the click of a button. To learn more about Experian’s decisioning solutions, you can additionally explore our PowerCurve and Attribute Toolbox solutions.

In order to compete for consumers and to enable lender growth, creating operational efficiencies such as automated decisioning is a must. Unfortunately, somewhere along the way, automated decisioning unfairly earned a reputation for being difficult to implement, expensive and time consuming. But don’t let that discourage you from experiencing its benefits. Let’s take a look at the most popular myths about auto decisioning. Myth #1: Our system isn’t coded. If your system is already calling out for Experian credit reporting data, a very simple change in the inquiry logic will allow your system to access Decisioning as a ServiceSM. Myth #2: We don’t have enough IT resources. Decisioning is typically hosted and embedded within an existing software that most credit unions currently use – thus eliminating or minimizing the need for IT.  A good system will allow configuration changes at any time by a business administrator and should not require assistance from a host of IT staff, so the demand on IT resources should decrease.  Decisioning as a Service solutions are designed to be user friendly to shorten the learning curve and implementation time. Myth #3: It’s too expensive. Sure, there are highly customized products out there that come with hefty price tags, but there are also automated solutions available that suit your budget. Configuring a product to meet your needs and leaving off any extra bells and whistles that aren’t useful to your organization will help you stick to your allotted budget. Myth #4: Low ROI. Oh contraire…Clients can realize significant return-on-investment with automated decisioning by booking more accounts … 10 percent increase or more in booked accounts is typical. Even more, clients typically realize a 10 percent reduction in bad debt and manual review costs, respectively. Simply estimating the value of each of these things can help populate an ROI for the solution. Myth #5: The timeline to implement is too long. It’s true, automation can involve a lot of functions and tasks – especially if you take it on yourself. By calling out to a hosted environment, Experian’s Decisioning as a Service can take as few as six weeks to implement since it simply augments a current system and does not replace a large piece of software.  Myth #6: Manual decisions give a better member experience. Actually, manual decisions are made by people with their own points of view, who have good days and bad days and let recent experiences affect new decisions. Automated decisioning returns a consistent response, every time. Regulators love this! Myth #7:  We don’t use Experian data. Experian’s Decisioning as a Service is data agnostic and has the ability to call out to many third-party data sources and configure them to be used in decisioning. --- These myth busters make a great case for implementing automated decisioning in your loan origination system instead of a reason to avoid it. Learn more about Decisioning as a Service and how it can be leveraged to either augment or overhaul your current decisioning platforms.