All posts by Neil Stephenson, Vice President, SaaS Client Engagement

The pandemic accelerated the number of digital interactions in finance. Typical methods of managing finances, connecting with lenders, and buying goods and services were much harder due to lockdown measures, so consumers went digital, including large numbers of non-digital natives. As the demand for online banking and services has intensified – moving from a necessity to a preference for many - pressure on businesses is twofold. They must rapidly build new and better models to onboard customers and create a more dynamic customer journey. In many markets, doing so is the biggest competitive differentiator right now. Creating a dynamic digital journey and understanding the customer With Millennial customers becoming a bigger influence in the space, organizations were always going to have to plan for a slicker and quicker digital customer experience to keep up with expectations. The pandemic simply accelerated this, forcing businesses to rapidly react. In fact, although 9 in 10 businesses have a digital customer journey strategy, 49% of those businesses only put this in place as Covid-19 began according to research in our Global Decisioning Report 2021. This did help them improve in some areas, including access to quicker customer service responses online. But without the right technology in place, it is not surprising that 55% of customers surveyed said they expect more from their digital experiences. Such a rapid shift has exposed weaknesses around agility, leaving traditional institutions trailing Fintech competitors further down the digital transformation road. However, whilst Fintechs have the benefits of agility, traditional, established lenders have large amounts of customer data from which they can target and tailor existing customer journeys more effectively. Improve the digital onboarding process Optimizing the digital experience for new customers from the beginning encourages usage and, ultimately, loyalty. A stress-free and fast onboarding process is an expectation for the younger generation but can also capture the ‘new to digital’ group migrating online. Bio-metric recognition technology, instant document verification, and auto-filling customer data are far more appealing than entering hundreds of data points, and can boost efficiency and reduce friction. The problem is businesses rightly want to make sure they can remove any bad actors to reduce risk and prevent fraud. The key is doing so without disrupting the genuine, low risk customers. Building better models to onboard customers Covid continues to shift population demographics due to factors such as job losses, furlough schemes and migration of workers to alternative sectors. There is also the realization of pent-up demand for property and vehicles, in particular - among those fortunate enough to be less impacted - such as those able to save more as they work from home. This has led to a change in the demand for finance with a need to tailor experiences to specific customer requirements. As the number of credit needs grow, lenders must have a structure in place that allows them to scale and handle the increased volume. New models must also be introduced to allow organizations to access extensive data insights and ensure they are reflecting the ‘new normal’. As businesses move away from sampling towards models that are based on full populations there must be a marriage of technology with data. Data is ultimately captured for the benefit of the lenders, helping them to gauge risk and tackle fraud. But a blended, multi-layered approach in which customers are only asked for the information specific to their individual circumstances – at the appropriate time – can provide a positive and tailored onboarding process. Having solutions in place that combine risk-based authentication, identity proofing, credit risk decisioning and fraud detection into a single platform ensures all checks can be carried out in one place with minimal disruption to the onboarding journey. Putting businesses in first place Online experience and credit and fraud risk management need to be more closely entwined. As the demand for a simple and fast experience intensifies, a digital-first approach that puts businesses ahead of the game must involve embracing the right technology that supports the entire customer journey. Download a copy of the eBook here.   Stay in the know with our latest research and insights:

Recently we commissioned Forrester Research to look into senior executives’ perceptions on key business data challenges and the importance of achieving a holistic view of their customers. This research uncovered that nearly a third of business leaders worldwide say they don't have enough data to get the insights they need or that the quality of the data they have access to is poor. While getting the type, quality, and amount of data right is paramount to success in your endeavors to create actionable insights that take your business to the next level, data alone is not enough. To get value from data, there's a whole ecosystem that needs to be in place that enables the business to create, manage and maintain a holistic view of the customer, create analytically driven insights into those customers, and deploy them into production environments that drive optimal customer actions and journeys. Organizations also have the opportunity to explore new data assets from traditional sources or those dynamically created in a myriad of places across mobile devices and the Internet of Things. There must be systems and procedures in place to continuously improve and assess these new data sources, by bringing them into analytical processes where insights are derived and predictive models generated.  The critical task is then to seamlessly ingest and embed the data and models into production environments in a robust and compliant way. And that's got to be a continuous process. Otherwise, businesses will stagnate, and they will lose out to those competitors who are actively doing this. Addressing the lack of data your business needs to get actionable insights: Three practical steps Prior to even considering external or additional data sources, you need to get a solid understanding of the data you currently have access to within your organization, what value those data sets bring in and what are the gaps to be filled.   You should also review your internal processes and technology stack to understand if further IT investment is required to create a more effective ecosystem.  With the right tools and processes, you must be able to easily assess the uplift of new data sources in your analytics environment, as well as ingest those new data sources into production environments, to drive new models, run segmentation rules, and execute customer-centric actions. What are the three steps you need to take to get enough data to gain business insight you can take action on? Look at the quality of your internal data. We see a number of organizations that have powerful data in their own business but don't leverage it as well as they could. So matching data together, making sure that they've got a really, really strong view of that customer across all of their systems is really essential. And then having processes ongoing to make sure that they maintain that view whenever they touch the customer, whether it's through an online channel or face-to-face, so that they always know who that customer is, and they can match them to their existing relationship profile. Getting your internal data process correct is a foundational element to this whole piece. Understanding the value and role of new data. In terms of new data, it’s about understanding if that new data can actually add value to the business rather than plugging it into core systems straight away.  You need to work with the vendor or the source of that data to get hold of a dataset, match it to your customers, and run analytical processes to identify whether the data adds value. If it does, consider what models or segmentations could you create from that data that'll actually drive value in the business.Identify the software and architectures you have in place that allow you to connect to data and drive that data into a tool that can dynamically apply models and rules in a heavily regulated environment.  With the right toolset forming the bridge between your off-line analytics environment and your on-line production environment, you can leverage predictive data to continuously improve your customer-centric decisoning across the lifecycle for all of your portfolios.