Download the report People’s changing behaviors to safeguard their health during the ongoing global Coronavirus pandemic has fueled a massive shift to digital channels. As people’s day-to-day routines and behaviors shift, so too is the attention on businesses to find new ways of staying relevant to their customers. Two-thirds of consumers are staying loyal to the businesses they preferred prior to Covid-19. 20% increase in overall online transactions – a 41% increase in online grocery shopping, 40% increase in applying for loans online, and a 22% increase in food delivery or takeout. 50% of consumers surveyed expect to increase their online transactions even more in the next 12-months. Uncertainty for what the next 6-12 months will hold has people and businesses vacillating between optimism and pessimism.  Some likely contributing factors could be public health gains and setbacks for containing the virus, some businesses opening only to close again, and the prospect of some students returning to school in-person and while others go remote – and what all of that means for economic recovery. At the time of our study (June 30 -July 7, 2020), some lenders and retailers are demonstrating more confidence than others, while consumers - many already feeling depleted - are expecting and bracing for an expected second wave of Covid-19.  Consumer financial hardship 65% of people believe their country has not yet recovered from the economic impact of the pandemic. 30% of consumers reported a decline in household income; India saw the largest household decline at 43%. The number of people having difficulty paying their bills has doubled since Covid-19 began. Businesses operational challenges 53% of businesses believe their operational processes have mostly or completely recovered since Covid-19 began. The U.S. (80%) is the most confident and Germany (27%) is the least. Top challenges faced by most businesses globally are the health and safety of their employees and customers, adjusting operations to support customers, and managing increased demand across channels and functions. 1 in 5 businesses surveyed lacks confidence in the effectiveness of their credit risk and collection decisions since Covid-19 began.  Beyond their intense focus on the safety and security of their employees and customers, our research shows that businesses are making strategic investments – to give consumers greater access to goods and services, and to better manage their customer relationships. They’re also exploring automation and cloud technology to relieve operational constraints. Whether it’s a lender providing financial assistance to small businesses and loan re-payment options to customers or it’s a retailer providing essential supplies and services to people who need it most, helping people and delivering on expectations for secure, relevant customer experience is top of mind. Top areas of investment: strengthening the security of mobile and digital channels, new credit risk analytics, and the creation of artificial intelligence (AI) models and increasing digital customer acquisition and engagement. Top 3 solutions businesses believe will improve operational efficiency when supporting customers’ financial needs are automated decision management, cloud-based applications, and artificial intelligence. 60% of businesses plan to increase the budget for analytics and credit risk management. Businesses in the UK, U.S., Australia, and Spain have already increased the adoption of AI and advanced analytics. To solve for the lack of economic precedent, 51% of businesses say they’re asking customers to contribute more information/data and 49% say they’re exploring new or alternative data sources. Download Experian's Decision Analytics Global Insights Report July/August 2020 and learn more about the impact of Covid-19 on consumer behaviors and business strategies

In a recent interview by Irene Ang from Identity Engineering at Microsoft, our own Marika Vilen, SVP of Platform Commercialization, discusses the importance of identity verification solutions and how to seamlessly integrate those across the digital user journey. We are very excited to be working with Microsoft. Identity verification allows organizations to confirm the person they are dealing with online is who they say they are. In light of the ongoing global pandemic, we see an uptick in digital activity and therefore an increased need for organizations to better verify who they are interacting with online, all while minimizing customer friction. Marika Vilen, SVP of Platform Commercialization, Experian Since COVID-19 started, there has been a 20% increase overall in consumer online transaction activities, our recent proprietary research shows. Consumers cite security as the most important factor in their online experience, particularly in regards to managing their financial data. So, what does this digital shift mean for businesses? Identity verification is an important step to take in digital interactions, and some level of friction can invoke a sense of security, but too much for too many customers can have a negative impact on the bottom line. So, while benefits are evident for identity verification, the process must also factor in the impact on the consumer. By taking a holistic approach that integrates across all stages in a customer relationship, customer friction can be minimized – and customer satisfaction and security maximized. We are proud to be working with Microsoft, integrating solutions that provide rich identity data assets and help inform real-time decision making. Related articles: Are traditional online identification methods becoming obsolete?  Q&A: Biometrics as the catalyst for trust in a socially distanced world  Getting to grips with the shifting fraud landscape 

We've compiled the top global July headlines you need to stay in-the-know on the latest hot topics and insights from our experts. 1. Accelerating forward: How Covid-19 has changed banking foreverChris Fletcher, SVP Decision Management & Cloud Services, covers how Covid-19 forced banks to deliver a convenient, engaging, relevant and secure digital experience, and how this fundamentally changes how banks operate and deliver value to customers. 2. Q&A: Importance of fraud trends as businesses open upDigital Journal recently spoke with EK Koh, SVP of Global Identity & Fraud Solutions, on what businesses need to do to be prepared for issues around cybersecurity and fraud as they open back up the economy. 3. Businesses need to modernize their approach for delivering digital experiencesBirger Thornburn, CTO of Decision Analytics, shares how the rapidly changing environment has greatly accelerated the shift from offline to digital interactions. 4. Experian’s 2 latest moves to combat fraudAuto Fin Journal addresses Experian ramping up efforts to curtail synthetic identity fraud, a significant challenge for lenders and finance companies, and strengthen solutions to help businesses more quickly respond to rising fraud threats due to the Covid-19 global health crisis. 5. AI at Experian with Shri SanthanamShri Santhanam, our Head of Global AI & Analytics at DA, participated in the Artificially Intelligent podcast discussing ways to approach AI in a holistic way, always with a view to realizing the desired business outcomes and strategic impact. In this dynamic environment, stay up-to-date with our latest Research:

Due to Covid-19 , the focus on analytics and artificial intelligence (AI) has significantly increased. However, while companies have made significant investments in AI, many are struggling to show a tangible impact in return. One executive commented, “We have data science teams and a data lab where advance techniques like neural networks, GANs, etc. are successfully being used. However, less than 10% of our actual operational decisions and products are powered by AI and machine learning (ML). I would like us to be driving greater measurable impact and Covid-19 is exposing some of our execution gaps.” And, he’s not alone. Despite the investment, the true impact is elusive, and many businesses are not getting the desired effect from their efforts. Achieving the results needed to justify continuous investment will take a holistic approach. So, what can companies do to achieve this impact? The four pillars of holistic AI: performance, scaling, adoption and trust Achieving impact from AI requires taking a more holistic approach across four pillars — beyond just the delight of the data scientist producing a better performing model. 1. AI performance — outperforming the status quo and quantifying the impact This pillar is where most data scientists and companies tend to focus first, for example using modern AI techniques to create an underwriting model that performs better than traditional models. The so-called ‘data science moment of truth,’ where the data scientist declares that he has built a model which outperforms the status quo by 10%. However, it’s important to note model performance alone is not sufficient. We should look beyond the model to understand business performance. What quantifiable business impact does the 10% improvement deliver? How many more credit approvals? How much lower will the charge-off rate be? This reasoning provides the important business context around what the incremental performance means. 2. AI scaling — having the right technical infrastructure to operate models at scale This area is often ignored. The risk with data science teams is they can see their job as being completed with creating a better performing model. However, that’s just the beginning. The next important step is to operationally deploy the model and setup the operational infrastructure around it to make decisions at scale. If it is an underwriting model, is it deployed in the right decisioning systems? Does it have the right business rules around it? Will it be sufficiently responsive for real-time decision making, or will users have to wait? Will there be alerts and monitoring to ensure that the model doesn’t degrade? Are there clearly defined, transparent and explainable business strategies, and technology infrastructure and governance to ensure all stakeholders are aware? Is the regulatory governance around this model in place? Does the complexity in the model allow it to scale? Too often we see data scientists and data labs create great models that can’t scale and are impractical in an operating environment. One banking executive shared how her team had developed 5 machine learning models with better performance, but were in ‘cold storage’ verse in use, because they didn’t have the ability to scale and operationally deploy them effectively. 3. AI adoption — ensuring you have the right decisioning framework to help translate business decisions to business impact With better performing predictive models and the right technology, we now need to present the information in a way that is ‘human-consumable’ and ‘human-friendly.’ At one bank, we found they built a customer churn ML model for their front lines, but no one was using it. Why? They didn’t have the contextual information needed to talk to the customer — and the sales force didn’t have faith in it — so didn’t adopt it. Subsequently, they built a model with a simpler methodology and more information available at their fingertips — where decisions could be made. This was immediately adopted. This pillar is where the importance of decisioning tools is highlighted. The workflow and contextual information to allow a decision to be orchestrated and made is critical in driving AI adoption. 4. AI trust – having governance, guardrails and the appropriate explainability mechanisms in place to ensure models are compliant, fair and unbiased This final pillar is probably the most important for the future of AI — getting humans to trust it. In recent times we have seen numerous examples like the Apple Card, where the underlying principles and models have been called into question. For scalable AI impact, we need an entire ecosystem of people who can trust AI. To achieve this effect, you need to consistently apply the right principles over time. You also need the right decisions to be explained — like adverse action calls. Explainability capabilities help manage communication and understanding of advanced analytics, contributing to established AI trust. And, when fairness and bias issues come up, you need to provide good answers as to why decisions were made. AI is poised to fundamentally change the way we do business, and studies show that $3 to 5 trillion in global value annually, up to $15 trillion by 2030, is likely to be created. We believe the four pillars highlighted above will be key to accelerating the journey to driving positive results and capturing this value. At Experian, we are making investments to drive impact for our clients by delivering against these four pillars. Related articles: What is the right approach to AI and analytics for your business? Four fundamental considerationsHow rapidly changing environments are accelerating the Need for AI What’s new in online payment fraud Part 2: How AI and evolving regulation are driving change

Chris Ryan, Senior Fraud Business Consultant, talks to Nick Zulovich at the Auto Remarketing podcast about the new ways we are seeing fraud surface as the global pandemic evolves. "The pattern of activity that we're seeing that has really attracted my interest is this notion of human farming. A human farm is a pool of paid labor who research information on potential fraud victims using data that's been stolen through data breaches and using information that people publish through social media and other outlets. The objective of a human farmer is to be able to assemble a detailed profile of a potential fraud victim so that the perpetrator can better impersonate them and navigate around potential security measures and other obstacles that would normally be in the way." Chris Ryan, Senior Fraud Business Consultant Why the opportunity for human farming? People are out of work so there's a recruitment opportunity for those in need of an income. There is a flood of people into the online space who might not ordinarily engage digitally. This demographic may not be tech-savvy and maybe more susceptible to fraud methods such as phishing. Resources that typically screen for fraud are suffering due to office closures. The combination of high tech fraud to find potential victims plus skilled human intelligence makes these methods highly effective. New trend amidst new circumstances - the rise of synthetic ID Remote transactions combined with the high-value nature of the auto industry makes it a very attractive prospect to fraudsters. Even though purchases are down, the fraudsters are still active. Synthetic identity fraud, in particular, continues to be attractive because the identities are not real and therefore not suffering from the same downturn as genuine profiles. Listen to the full podcast here. Related articles: Getting to grips with the shifting fraud landscape Infographic: Top Global Fraud Trends 2020 Covid-19 as a Gateway to Fraud: Top 5 Global Fraud Trends to Watch Out for in 2020

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 this episode of the Insights in Action podcast we talk to Neil Stephenson, Vice President of Strategic Client Development, about how businesses can address a lack of data. Following an earlier episode tackling business data challenges, we discuss getting value from the data your organization already has access to, tackling legacy software issues, the accelerated shift to customer-centric technology stacks, and an increase in industry partnerships to solve common challenges. Nearly a third of senior business leaders say they don't have enough data to get insights they need, or that the quality of the data they have access to is poor. We take a look at the three steps businesses need to take to address this challenge, starting with the quality of data already in the business. "We see a number of organizations that have pretty powerful data within their own business but don't leverage it as well as they could, so matching data together and making sure they've got a really strong view of their 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 that be through an online channel or face to face." Neil Stephenson, VP, Strategic Client Development Listen to the full episode here, and look back at the previous in the series, Solving key business data challenges - with Bill O'Connell, Experian Global Decision Analytics

The first of a two-part series on our Insights in Action podcast, Nick Maynard, Juniper Research, and David Britton, our VP of Industry Solutions for Global Decision Analytics, discuss the latest developments around online payment fraud, and what the implications look like for consumers and businesses. Following the publication of the latest report on online payment fraud from Juniper Research, this episode takes a closer look at how the mobile revolution has created both opportunities and risks when it comes to online payment. "We're seeing a massive digitalization of existing payment methods and retail, which is being driven for a number of reasons. Convenience is a massive driver, and mobile wallets in particular offer a very convenient solution for payments, and they're being used very widely around the world. Other drivers include the ongoing Coronavirus pandemic, which is having a role in driving the increased usage of the online channel."Nick Maynard, Juniper Research Topics covered in part 1 include: The online payment revolution has been led by mobile, with half of the world’s population estimated to use mobile wallets in the next four years. How this transformation is shaping the new online payment experience. ​ Covid-19 has pushed organizations to prioritize their digital transformation. We look at what the implications will be as a result of the rush to digital. With higher convenience, normally comes a higher risk of fraud – what we can expect to see as a part of this shift to mobile. ​ What businesses can do in the short term to mitigate those rising types of fraud, and what their key operational and strategic considerations should be for the future. ​ Listen to the full podcast here, and look out for what’s new in online payment fraud Part 2: How AI and evolving regulation are driving change

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.

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.

In this episode of Insights in Action, David Britton, Vice President of Global Identity & Fraud Solutions, discusses how the Covid-19 pandemic has prompted a massive shift to online for both consumers and businesses, and examines what implications have emerged across the online fraud landscape because of this. "As with any moment like Covid-19, fraudsters are very quick to pick up on possible areas of vulnerability that they can exploit in the market and in the ecosystem. And fraudsters always like to go where the weakest point is in the ecosystem or the weakest link in the chain. So fraudsters are absolutely taking advantage of this."David Britton Phishing is on the rise - fraudsters are impersonating key institutions and their communication channels to manipulate consumers Account takeover fraud - fraudsters are hiding in the traffic peak, posing as consumers using their credentials How businesses can counter the trend: Keeping online fraud at baySecuring our digital identitiesEnsuring a secure, transparent and meaningful treatment of data "The first thing to do is to ensure businesses are pulling together soft signals to define a better risk strategy and authentication strategy because then you can immediately identify if there's an anomolous actor that's trying to impersonate that 'known' good customer."David Britton Listen to this episode of the Insights in Action podcast