Innovation

Insights from Harry Singh, SVP, Global Decisioning, and Hristo Zahariev, Global Product Manager. Due to the global pandemic, one of the key challenges facing many consumers today is the ability to obtain support either from their credit provider or from government. This is manifesting itself in two ways – consumers facing very short-term financial difficulty, which might mean a payment holiday for a few months, or longer-term structural issues such as unemployment, which requires a very different set of treatments and outcomes. But what can businesses do to ensure consumer demand is met while taking care of customer experience? We look at the importance of digital channels within the decisioning environment, and how investment using AI can not only lead to consumer satisfaction now but also a sound business strategy for the future, regardless of how unpredictable that future may be.    How the industry can respond to consumers during this time of need A recent study from March this year looked at businesses that are not yet fully digital in terms of how they handle their consumer interactions, and how they can reach out to consumers to help them during the Covid-19 crisis. With call centers and operational centers closed, and anything between five and 50,000 applications a week coming into banks across the world since the pandemic began, businesses have inevitably been struggling with demand. Based on existing operational models examined within the study, if businesses were to manually manage these applications, they would need to double in size in terms of full-time employees, and follow-up interactions post approval may still not be met. Managing demand and staying compliant, while enabling consumers to successfully interreact without waiting hours to get through is the challenge faced by many businesses. It’s a balancing act that is both an opportunity and a risk and should be treated as such. Helping consumers in a way that is digital, while allowing for self-serve, is fundamental in meeting these new levels of demand - and doing so in a way that doesn’t feel demeaning to the consumer is where true differentiation begins. During a stressful time for consumers, it’s important that businesses step up to the challenge of demystifying their interactions, removing embarrassment around finances while also retaining an element of human engagement. Thanks to AI and a layered, cloud-first approach to decisioning, contacting pre-qualified consumers for both forbearance and hardship can now be done through a business’s banking application or their website, using artificially intelligent virtual assistants that can be deployed in a multitude of different digital channels. The consumer perspective: we need more than a chatbot Chatbots are very effective and useful in many ways, but when an interaction gets complex or there's something of a regulated or more subjective nature, it becomes difficult for that chatbot to provide the kind of service consumers are looking for. The answer lies in continuous learning, which moves away from the decision tree structure of a traditional chatbot and into the realms of natural language processing. The new age of virtual assistant remembers interactions and then learns from them, has short-term and long-term conversation goals, and recognizes small talk. The result feels a lot more empathetic and allows for always-on and real-time consumer interaction. How businesses can develop their strategies not only for today, but going forward Bringing together digital capabilities, analytical insights, and data to understand the affordability of a consumer is critical. Using demographic and geographic data, businesses need those insights, regardless of whether we are in a growth environment, a benign environment, or as we're seeing right now, a recession of macro-economic downturn. Businesses choosing to invest now to address their operational and strategic challenges are not just responding to Covid-19, they are looking beyond and into strategic requirements of the future. Financial difficulty may be more acute right now, but it has always existed and always will, for various reasons.  

In the second part of the Juniper Research and Experian podcast series on online payment fraud, we talk to Nick Maynard from Juniper Research, and David Britton, Vice President of Industry Solutions at Experian, about maturity in artificial intelligence and virtual assistants, and their current ability to respond to current business challenges. "What we're seeing in the consumer space is that AI is powering these virtual assistants and typically Alexa, Siri, Google, are the three big examples. What that's doing is creating an additional channel, it's a new way for users to interact... it mirrors the digital transition and the mobile transition over a number of years."Nick Maynard, Juniper Research "If you consider where artificial intelligence and machine learning are coming together, this is not going to be a big bang launch into market. We're seeing a slow, incremental roll-out." "In the physical world, when we talk about risk and recognition of a consumer, the human to human interaction takes in a tremendous number of variables to ensure that the person you're engaging with is who they claim to be.... in the digital space, that was eliminated overnight, and cosnumers were using a device as a proxy to represent them to another system or set of devices, like bank servers and eCommerce web servers." David Britton, VP of Industry Solutions We also discuss key points around evolving regulatory frameworks, and how they are driving change in identity-based solutions. Listen to the full podcast episode here, and don't forget to listen to What’s new in online payment fraud Part 1: Implications for consumers and businesses if you haven't already.

In a recent piece for the Forbes Technology Council, Businesses Need to Modernize Their Approach For Delivering Digital Experiences, I shared how the current rapidly changing environment has greatly accelerated the shift from offline to digital interactions. As businesses experience a need for heightened governance and controls, they must look towards technologies such as artificial intelligence (AI) and machine learning, coupled with access to data in real-time, to move forward. According to the report Experian commissioned Forrester Consulting to conduct, 53% of businesses struggle to make consistent customer decisions. Additionally, only 29% of businesses believe they do a good job of connecting analytics to action. When applying AI and machine learning to customer experiences, there are some concerns that businesses must keep in mind. The first is legal implications and privacy protections, which must always be a priority. The second is to combine analytics models with real-time decisions so that predictions can be harnessed and put into action in real-time. As more and more businesses shift to fully digital experiences, they must learn how to apply their vast amounts of data to models that can help inform the newly remote customer experience. If interested in the topic of businesses’ modernized approach to digital experiences, you can find the full article here.

The decisioning landscape is changing rapidly. In parallel to this, digital continues to redefine the customer experience with a big focus on removing friction from the customer journey. Mounting expectations around online customer experience mean that we are seeing a digital transformation both in terms of consumer interaction, and what the businesses are processing in the background. The front and back end are no longer mutually exclusive, and the driving force behind this transformation is digital, and it’s enabled by the cloud. How the pandemic has shifted priorities Before the Covid-19 pandemic took hold, businesses were well on their way to recognizing this. Digitizing more workflows while incorporating a truly customer-centric view was the goal of 2020. A Gartner report shows that in January, priorities for CIOs centered around Cloud and DevOps. This push to shorten the development lifecycle by combining software development and IT operations into a single discipline, alongside demand for Robotic Process Automation, using bots to focus on automating high volume repetitive tasks, were top of the list for businesses. By April, these priorities had changed. Businesses quickly shifted their focus to the pandemic, and with that, the need to enable remote or home working. But Cloud remains firmly within the top three. We look at why cloud-first decisioning remains critical to digital transformation, now more than ever. Why Cloud-first is even more important now Managing cash flow: When a CIO is in the cost optimization mode and trying to conserve cash, scaling back on the use of existing Cloud technology can afford immediate cost savings. Cloud cost for infrastructure of the service, or platform of the service, and even some software of the service is often tied to the business. The less usage, the more savings. When a CIO needs to implement new technologies in 2020, Cloud can offer the most cash flow optimized needs to do so. Less cash is spent upfront to acquire Cloud technology than to buy data center systems or licensed software. Business agility: Cloud technology makes it much easier to keep systems up to date and secure, alongside feature enhancements and new releases. The Cloud minimizes lengthy and costly delivery projects with solutions that can be deployed in weeks, not months and years. Customer journey: Many established market leaders are running digital transformation programs that re-orientate their business away from functional and product silos to focus on customer journeys enabled by Cloud services. Keeping it simple: Simplification is crucial. Simplifying the IT environment with Cloud services that eliminate the need to manage hardware and other infrastructure. Using Cloud-native architecture to support auto-scaling, zero downtime for upgrade. Security is paramount: The challenge to identify and fight fraud by analyzing behavior during the data capture process is ever-present. Software needs to evolve all the time to adapt to threats, and it needs to continuously update with new features to help businesses remain competitive. Businesses need to protect consumer digital accounts from Account Takeover threats while balancing consumer convenience. Cloud-first impacts all layers, from consumer interactions to data sourcing and processing, from fraud detection to identity verification, and at the heart of areas like credit and decisioning. Integrated decisioning, and decisioning that is governed and can be clearly explained to both the auditor and to the regulator is the goal of every business, and it is enabled by the cloud.

I recently had the opportunity to talk to Christian Hubbs and Muhammed Shuaibi from Artificially Intelligent Podcast about the value AI and analytics generate for businesses. We reviewed how a growing number of businesses are seeing a lot of value added in terms of problem-solving when they bring in more sophisticated machine learning models and technology.  The conversation quickly pivoted towards how to determine the analytics and AI that better suit your business needs, as well as understanding what is required to operationalize those promising models. Think of performance, scalability, adoption and trust before embarking on your AI journey Ensuring that AI is right for your business requires a holistic approach, which is fundamentally based on four components:   AI Performance – selecting and framing problems, with a view to demonstrate that what you build outperform traditional methods.  AI Scalability - what starts as an experiment conducted by data scientists needs to be turned into a scalable system that truly impacts the business.   AI Adoption – ensuring that your AI and analytics are embraced and used by consumers and businesses and, ultimately, change the way they make decisions.  AI Trust – explaining decisions in a transparent way so the models and systems you build can be trusted, explainable and stand the test and scrutiny of regulators. Leveraging an outcome-based approach to solve COVID-19 related business challenges At Experian, we are applying this holistic approach to identify and address the most pressing concerns our clients are dealing within the context of COVID-19. The first is helping our clients understand what’s currently happening with different customer segments. We’re creating tools that bring together a series of early warnings and indicators and portraying how different customer segments are seeing various patterns in credit. We’re also identifying those most affected or needing concessions around lending, and understanding what banks are doing in terms of forbearance. Our priority is identifying these needs and quickly get the relevant AI and analytical solutions to our clients.  We are expecting to see a later urge in the industry to recalibrate existing models and to expand the type and volume of decisions they can make. Updating and monitoring them will be also a big area of focus over the next couple of years.  Listen to the podcast

Businesses can leverage technological advances in process optimisation, automation, data analysis and cognitive science to put customers first and truly understand and address their needs.

In this podcast episode of Insights in Action we talk to David Britton, VP of Global Identity & Fraud at Experian Decision Analytics, about how businesses worldwide are driving towards a more consumer-centric approach in both their operations and structure.

Shri Santhanam, Executive Vice President and General Manager of Global Analytics and AI, speaks to Forbes' Peter High on his Technovation podcast about Experian's Analytics and AI solutions. During times of crisis, innovation accelerates. What was once considered innovation, suddenly falls into the realms of the necessary, with businesses seeking quick, smart solutions to emerging challenges. Although this conversation took place before COVID19 reached the levels of a global pandemic, Santhanam discusses how advanced analytics and AI can be a game-changer for businesses. Key topics include how businesses need to bring together data, tech and analytics to formulate best in class products and services using AI in the form of examples such as Experian Boost. What it takes to run the global analytics and AI function at Experian. How high-profile consulting positions within previous businesses have placed Santhanam in an ideal position to problem-solve. And what he considers to be the two stand-out developments in the analytics and AI space. Listen to the podcast, or read the interview.