Tag: covid-19

What increasing expectations of the digital customer experience mean for your business and technology investment Economic recovery and waning customer loyalty are creating new opportunities 59% of businesses globally say they’re mostly or completely recovered from the pandemic 61% of customers engaging with the same companies they did a year ago, down 6% in twelve months Data, analytics and decisioning technologies help provide customers with a secure and convenient digital experience Consumers are prioritising security, privacy and convenience when engaging online 75% of consumers feel the most secure using physical biometrics Scalable software solutions give companies of all sizes the ability to better manage risk and digitally transform the customer experience 50% of businesses are exploring new data sources 7 in 10 businesses say they’re frequently discussing the use of advanced analytics and AI, to better determine consumer credit risk and collections 76% of businesses are improving or rebuilding their analytics models “Dwindling customer loyalty along with heightened customer expectations and increased competition could mean potential revenue loss or gain. Businesses must find integrated credit and fraud solutions to improve digital engagement and customer acquisition.” Steve Wagner, Global Managing Director, Decision Analytics, Experian We surveyed 12,000 consumers and 3,600 businesses across 10 countries as part of a longitudinal study that started in June 2020 Read the full report to find out where businesses are focusing their investments

It’s no secret that the pandemic created a level of economic uncertainty that makes it incredibly tricky for lenders to understand their risk on a customer-by-customer basis, and therefore its impact on decision management. It’s no wonder they’re uncertain; the customers themselves are just as unsure. According to the Global Decisioning Report 2021, one out of every three consumers worldwide are still concerned about their finances even as the second anniversary of the COVID-19 outbreak approaches. While some consumers were able to easily work from home during the pandemic, others suffered job losses, cut wages, or increased expenses due to lost childcare or having to care for a loved one. As the impact of the pandemic continues to be felt – especially as government support programs begin to conclude – financial institutions will have to figure out how to navigate the uneven recovery. By leveraging advanced data and analytics, financial institutions can better understand their risk and improve their decision management. In turn, many financial institutions are creating predictive models to target their best customers and reduce exposure to unnecessary risk. However, a model is not always the end-all, be-all solution for reducing risk. Here’s why: a model requires of the right data in order to work effectively. If there isn't a data sample over a long enough time frame, the risk of creating blind spots that can leave businesses on the hook for unexpected losses can be high. Also, there will always be the need for a strategy even with a custom model. A global financial institution likely has more than enough data to create accurate, powerful custom models. However, financial institutions like local or regional credit unions or fintechs simply don't have enough customer data points to power a model. In addition, many outsourced model developers lack the specific financial industry domain expertise required to tweak their models in a way that accounts for the nuances of regulations and credit data. Finally, the pandemic continues to change the economic picture for customers by the minute, which can make a model designed for today outdated tomorrow. When a strategy makes more sense For many financial institutions, it can make more sense to focus on building out a decision management strategy instead of leveraging custom models. While a model can provide a score, it can’t tell you what to do with it. By focusing on a decision management strategy, you can leverage other information and attributes about different customer segments to inform actions and decisions. In an ideal world, of course, the choice wouldn't exist between a model and a strategy. Each has an important role to play, and each makes the work of the other more effective. However, strategy is often the smart place to start when beginning an analytics journey. The benefits of starting with strategy include: Adaptability: A strategy is much easier to change than a model. While models often have rigorous governance standards, a strategy can be adapted with relatively little compliance impact. This helps businesses adapt to changes in goals, vision, or shifts in the marketplace in a bid to attract the ideal customer. In a world that changes by the day, the ability to adjust risk tolerance on the fly is crucial. Speed: A custom model can take weeks or even months to build, test, deploy, and optimize. As a result, this can put businesses behind in analytics transformation while leaving them unnecessarily exposed to risk. On the other hand, a strategy can be developed and deployed in a relatively rapid manner, and then adapted on an ongoing basis to reflect the realities on the ground. Consistency: A strategy helps drive improvement across operations by allowing team members to ‘sing from the same songbook,’. In smaller organizations where work is still done manually by a handful of people, a strategy allows for automated processes like underwriting so businesses can scale decisioning. Strategy or model? Three questions to consider Do you need a strategy or a model? Again, in an ideal world the answer is ‘both’ due to the unique role each plays, but in the real world it depends on the institution. Here are three questions to ask in order to determine where to focus time and resources: “How different are the people I am lending to than the national average?” If the institution is lending to segments that look just like everyone else, leveraging existing third-party data sources will allow the use of generic models. In this case, the focus would be on using those generic models to power the strategy. However, for businesses that serve a niche population, a national average might skew results; in this case, it may make more sense to build a custom model. “What is my sample size?” Take a close look at the number of applications coming in each month, quarter, or year. In addition, compare it to periods dating back years to understand growth rates. This will indicate the if the data inflow required exists to power a custom model. Don’t forget to analyze how many of those applications eventually become delinquent; because some smaller financial institutions have conservative policies, they may have low delinquency rates. While this is good for the institution’s bottom line, it can make it difficult to build a model that will be able to detect future delinquencies. Therefore, even a large application sample size might not have enough variance to create an accurate custom model. “What are my long-term future goals?” This is the most difficult question to sometimes answer, as many financial institutions remain focused on navigating today’s challenges. As market conditions change, goals naturally adapt. That said, some goals might require custom models in order to effectively achieve the business vision. For example, if the plan is to enter new markets, create new partnerships, or offer new products that are different than what has been done in the past, a custom model could provide a more accurate understanding of potential risk. Our research also shows that nearly half of businesses report that they are dedicating resources to enhancing their analytics, with one-third of businesses planning on rebuilding their models from scratch. Rapid changes in consumer needs and desires means there’s less confidence in consumer risk management analytics models that are based on yesterday’s customer understanding. By focusing on a decisioning strategy, businesses can be empowered to effectively leverage analytics today to take action while creating a steppingstone for more sophisticated model-based analytics tomorrow. Stay in the know with our latest research and insights:

In a recent interview, I had the opportunity to talk to Chris Preimesberger of eWeek about the latest Global Identity and Fraud Report. We discussed some of the business challenges executives face in the increasingly complex space around fraud mitigation while reflecting on how and why the pandemic has shifted the fraud landscape. Market movement – more of us were online than ever before With so many of us at home during the pandemic, access to digital services and the purchasing of goods online increased dramatically. According to our research, businesses responded by investing in supporting services to accommodate the increase in traffic. We saw a lot of action from businesses around how to improve the customer experience while getting a better understanding of who the customers are and how to get their online problems resolved. Our January research wave showed that with all this investment into customer experience and enablement, there were some key areas of investment. Analytics – the use of automation and AI to help make smoother, better decisions for customers – ranked highly in business priorities, but this approach does not exist in isolation. Businesses are also doubling down on support staff to ensure that consumers have a way, if there’s an anomaly in the process, to be able to respond. Whether that’s password resets or call centre staffing, there’s a desire and there’s an intention by businesses to increase staff on digital support. A shifting sense of recognition We also surveyed consumers on their preference for passwords versus other security methods. Security remains the top consideration for consumers when online, above others such as convenience, but interestingly, for the first time in four years password protection did not appear in the top three preferred security methods, favoring instead a more friction-less approach to authentication. This shift in consumer attitudes towards what we call invisible security paves the way for businesses to start to adopt more sophisticated or nuanced approaches to authentication and security. They can start to leverage behavioral analytics or device intelligence recognition without intruding on the user experience. Normalizing biometrics and the importance of a layered approach Customer attitudes around traditional biometrics are very positive – it’s one of the top-rated preferred security methods thanks to the providers that have popularised it through the mobile devices we all use every day. However, the challenge with pure biometrics is always at the point of enrolment – how do you ensure that the right person is assigning their biometric to a device? This is why a layered approach to security that incorporates traditional identity verification or authentication processes along with more advanced technical elements like behavioral analytics, device intelligence, network access, and transactional context is so important. For example, “Is this device associated with David’s account? Is this actually David or a bot? How does David hold his phone?” This includes layers of security that are considered privacy-safe, and may not even require traditional identity data but have anonymous attributes that can be associated with how someone interacts. This will be pivotal in allowing businesses to enable a more comprehensive, pliable, and flexible approach to security rather than relying on rigid but easily broken mechanisms that we’ve been using for a long time. Why the types of fraud will change as the world seeks normality Over the last year, fraudsters focused their energies on stimulus funding and many other forms of low-hanging fruit that they could easily go after, pulling back from their activities in traditional financial services or e-commerce. As the pandemic eases off in many parts of the world, fraudsters are likely to increase their activity in these areas once again as stimulus programs close down, and as consumers increase their spending. Fortunately, we found that more than half of businesses will continue to invest in fraud prevention solutions over the coming year. Fraud trends to watch in 2021 As we look at the direction in which fraud is moving, we know there is an increase in several types of fraud as we navigate what is becoming the post-pandemic world of 2021. Account takeover fraud is set to be on the rise again this year. This is when stolen credentials are used to gain access to systems. Account origination or new account opening fraud will also be on the increase, where fraudsters use stolen identities to create brand new accounts, including a rise in synthetic identity fraud. Card not present online transactions is something we will see in huge volumes given the explosion of online traffic over the last year, which will undoubtedly include an increased volume of fraudulent transactions. Stay in the know with our latest insights:

The pandemic has enabled something close to a digital revolution, but how can businesses keep up with shifting consumer behaviors while ensuring fraud prevention is top of mind? Our latest Global Identity and Fraud Report takes a look at key consumer trends online and how businesses are responding.  

As consumers shop, bank, and pay online during the global pandemic, steps are being taken to return to more business as usual. But, what should businesses expect around consumer digital preferences post-pandemic? Steven Wagner, Global Managing Director of Decision Analytics, recently spoke with Jill Malandrino of Nasdaq Trade Talks about recent survey findings and overall trends to watch out for. Here are highlights of that discussion: Research trends indicate a continued and persistent surge in online transactions and digital payment mechanisms The current environment has been a tipping point for consumer trust in online transactions A secure environment through continuous and passive authentication is key to meeting online consumer demand There is a direct correlation between consumer trust in their online environment and their willingness to provide data to secure a transaction Businesses need to invest in AI that provides a good consumer experience -- from chatbots to machine-learning models that impact consumer treatment in real-time Watch the full episode now: Related stories: New research available: 2021 Global Insights Report Parting ways with old forms of managing credit risk online Why the new era of customer experience includes passive authentication

The world is still grappling with the mental, emotional, and financial toll of the Covid-19 pandemic but there are clear signs of hope and resolution ahead. Consumer concerns about their personal finances have started to ease for the first time since June 2020. And there’s a groundswell of opportunity for businesses to serve the growing ranks of “connected customers”—putting the consumer truly at the heart of the relationship. Download Global Insights Report – January/February 2021 issue Key insights: 60% of consumers are using a universal mobile wallet - for online and/or in-person contactless transactions Top 2 activities among consumers online are personal banking (58%) and ordering groceries and takeout food (56%) 90% of businesses have a strategy in place related to the digital customer journey; 47% of businesses put this strategy into place since Covid-19 41% of businesses intend to use AI to acquire and onboard new customers 55% of consumers say security is the most important factor in their digital experience – this is highest in the UK (65%), followed by Japan (64%) Fraud is the biggest challenge among businesses; 55% of businesses plan to increase fraud management budgets In this report, we continue our examination of consumer behavior and business strategy throughout the pandemic. For our third wave of insights, we surveyed 3,000 consumers and 900 businesses in January 2021. Our respondents span 10 countries, including Australia, Brazil, France, Germany, India, Japan, Singapore, Spain, the United Kingdom, and the United States. Over the past 12 months, we’ve observed consumer demand for the digital channel increase at a rate that few could have predicted. The most recent survey shows that these trends are persisting. Looking ahead, we expect that as people get more comfortable with the security and convenience of the digital channel, it will become the preferred—if not permanent—way to bank and shop. Part of what’s driving the continued demand: Positive digital experiences. Most consumers report they’ve been satisfied with their online transactions, especially when they secure and their financial information is protected. This is remarkable, given the challenges businesses faced to meet online demand while simultaneously adapting their employee and customer operations to the crisis. Businesses rose to the occasion and there’s opportunity ahead. Our latest report reveals that consumer expectations for digital experiences continue to rise. For example, even as consumers enjoy the ease of online banking and shopping, security is top-of-mind. In response, businesses are renewing their focus on preventing and mitigating account takeover fraud, transactional fraud, and digital takeaway fraud (e.g. buy online and pick up in-store). And they’re looking for solutions they can use throughout the digital customer journey, not just account opening. Consumers are also looking for greater customer support across digital channels. For example, when a customer is engaging with a business digitally, access to customer service is essential. It’s also an area where many businesses are falling short. However, businesses have made redefining the customer journey a priority and they're investing in capabilities, such as artificial intelligence and automation, to deliver on customer expectations. Consumers and businesses have embraced the digital channel— and the promise it offers is only growing. Now as we move toward a new, post-pandemic era, organizations that re-imagine the customer journey and create digital experiences that place customers at the center stand to win. find out what businesses are using to help improve the customer journey across digital channels, as they prepare for post-Covid customer engagements.

Don't miss out on the top January headlines, including the latest coverage from our global experts, including the digital identity landscape,  impacts of pandemic fatigue, protecting users and their experience, Covid-19 impacts on businesses in India, and consumers' digital experience expectations. Experian selected as leading provider of digital identity This MarTech Series article looks at Juniper Research's Digital Identity: Technology Evolution, Regulatory Landscape & Forecasts 2020-2025 report. David Britton, Vice President of Industry Solutions, offers his perspective on providing both convenience and security. In 2021, loyalty shouldn't be assumed Destination CRM covers findings of the recent Experian Global Insights report, which indicates that consumers might not be as patient with businesses for much longer. The impact of "pandemic fatigue" translates to an end in consumer acceptance of the pandemic as an excuse for poor service. Establishing and protecting user identity in a digital world Eric Haller, Executive Vice President & General Manager, Identity, Fraud & DataLabs, speaks to the rise of digital and the impact on the need to be able to identify an individual. Relying on technology to help deliver a good user experience is key to avoiding too much friction in the process. 99 percent of businesses in India implement digital online strategy to recognise customers; highest in APAC: Experian Report#TradeTalks: Increasing consumer demands and expectations Business Standard looks at recent global research findings on consumer and business economic outlooks, financial well-being, online behavior, and more. Most prominently, the vast majority of Indian businesses implementing strategies to recognize customers across platforms. The top three reasons people abandon online transactions In this Global FinTech Series article, Chris Fletcher, SVP Decision Management & Cloud Services, explores the current environment of online transaction explosion and what it means for businesses to accommodate this lasting preference for digital. It will be key for each transaction to align the need for security with the right level of friction to the consumer. Stay in the know with our latest insights:

In a world drastically and constantly changing, industries and technologies are being transformed at a rate never before experienced. Recently, I had the opportunity to speak with Roy Schulte, Distinguished VP Analyst at Gartner, about trends in the evolving world of big data, advanced analytics, and decision intelligence — trends that are powered by advancements in cloud technology, machine learning, and real-time streaming. Below, I will share a summary of key highlights. The growth of decision management More businesses are implementing decision management. They want to make more automated decisions to accelerate outcomes while improving applicability. In tandem, decisions are becoming more complicated with regulators increasingly expecting decisions to be explainable and with audit trails built-in. Equally, the combination of machine learning and decision management has placed greater focus on the importance of avoiding bias. Bringing all of this together promises continuous decision improvement; updating models and strategies in days or even hours rather than weeks and months. Essential in responding to the rapidly changing environments, none more so than the impact of Covid-19. As businesses are implementing decision management, they are putting the new systems into the cloud. Based on a Gartner survey in mid-2020, 67% of respondents said their digital business platform will be cloud-native application architecture. It’s the primary criteria for the architecture of many of these new systems. Migrating to the cloud The reason decision management is going to the cloud is the same reason other areas of business are taking this step. Organizations are highly motivated not to run their own systems. There is no competitive advantage to doing so. They want to entrust it to others so they can focus on what the business does best. The migration will continue gradually to the cloud, with a current acceleration based on Covid-19. In a recent Gartner survey, 65% of respondents said the pandemic accelerated their plans and funding for doing digital business. Most models and strategies will be built in the cloud, and the actual runtime decisions will be distributed with some on the cloud, some on-premise in a data center, and some out in the edge in a mobile device. Real-time streaming In the past, traditional business information was done on static, snaps of data from the past. Today, much of this is going real-time, depending on the kind of decision that is being made. For example, when a customer is visiting a website, there are mere seconds to generate the next best offer. This is a real-time decision. However, some decisions do not require real-time, such as the strategic decision to acquire another company or not. That is why it’s important to align the decision speed and cadence with the actual business problem. If real-time data will be used, such as for an e-commerce situation, some of it must be streaming data. With the increase in factors taken into account when making decisions, you need data that is connected, contextual and continuous. The data must come for your entire ecosystem, not a single department, but across your company, business partners, your customers, or market data. Streaming examples for e-commerce might include location, what the person has been doing on the web recently (clickstreams), and records of contact with your business such as calls and emails. A real-time lookup is involved with inventory and external factors like credit rating through an API, and customer data will include historical and real-time. With these factors, real-time decisions for e-commerce will be more effective, with higher yield rates and lower fraud rates. Machine learning in model building and execution Machine learning (ML) is making predictions, not decisions. When a prediction is made and a score is provided, a rule must be applied to determine outcomes based on the score. If considering rules or analytics, the truth is that in most cases, both are needed. The goal of ML in decision management is to have applications that are easier to develop, faster to develop, and lead to more accurate outcomes. To achieve this objective, a process covering all stages of a decision cycle is needed — Observe: Getting connected, contextual, continuous intelligence. Governance is key at this step to know where data is coming from and that it will be used in authorized ways. ML models and strategies must avoid bias and alternative data sources and lending criteria should be considered to expand the business without incurring increased risk. Orient: The next step is putting the data in context. When dealing with models at scale, it’s important to be able to track outcomes through tools such as performance dashboards. Eventually, this will lead to the hyper-personalization of models. Decide: Once models are built, strategy, rule authoring, and approvals are needed. Workflow and collaboration mechanisms help manage the process and accelerate the pace of developing new decisions. Act: Next comes the deployment of models. Using logic to make decisions across multiple applications accelerates deployment, often referred to as centralized management or reuse of decision factors. Feedback: Finally, continuous logging of decisions and effects of decisions. Tracking provides the ability to audit past decisions, explain what was done, and accurately post hoc remediate. Ongoing feedback also enables continuous decision improvement at an accelerated pace. The future of decision management includes decision intelligence In summary, there are five considerations for the future of decision management — A systematic approach to decision making, including a lot more automation and decision intelligence, is clearly on its way. Migration to the cloud is well underway with acceleration thanks to Covid-19. Equilibrium will be reached where some decisions are made at run time at other locations, but most of the development of decision-making, modeling, and strategies will be based on cloud platforms. Data science ML vendors have not focused on decisions. Some may come to realize the reason you do analytics is decisions and broaden the scope of what they do, or they may stay focused and instead partner with other vendors to enable end-to-end decision making. For certain kinds of logic, graph databases and graph analytics can be very powerful. Likely this will become a big part of decision intelligence going forward. Finally, there is huge untapped potential in optimization technology to improve decisions either at development time or even at run time by applying optimization techniques. This could lead to achieving the full vision of artificial intelligence. Related stories Insights in Action Podcast: Identifying the core capabilities your business needs to get MLOps right New Tech Talks Daily Podcast: Machine learning and AI in business — investment trends pre- and post-pandemic In digital transformation, small wins lead to big outcomes

As the world witnessed, the Covid-19 pandemic led to a swift and dramatic digital explosion. As lockdowns began, our day-to-day quickly shifted to a virtual environment. Now, on the back of this widespread response, businesses are forced to rethink their customer engagement model. And, with new digital-first customer journeys, there must be a shift to recognize customers in a predominantly digital way as well. The concept of identity – even digital identity – must evolve. Digitally observable information Recently, I spoke with Juniper Research about this imperative. After analyzing the global digital identity market, they’ve offered insights on current dynamics and trends shaping its future in their Digital Identity Report 2020-2025. Importantly, as we progress digital identities, we must consider more than what a user might typically provide about themselves. We must include digitally observable information, which forms part of a consumer's digital identity. This data includes their device (what they use), and behavioral insights (how they use the device or interact with an app or website). It even includes the specific context of their efforts (what they are doing), such as signing up for an account, moving money, making a payment, virtual window shopping, etc. Related story: View digital identity market trends infographic Intelligent data processing Of course, pulling these kinds of observations together in a meaningful and useful way requires intelligent data processing. This need leads to the use of technologies such as advanced analytics and machine learning to help make sense of the broad streams of data. The double benefit of understanding how to use this aggregated data is that, given the transparent and passive nature of observing data of this nature, it can be used without requiring the consumer to "do" anything other than going about their business. So, businesses can achieve multiple benefits by adopting a forward-looking stance to identity, including reduced risk of fraud, improved customer experience, and stronger consumer/business relationships, which ultimately leads to increased top-line growth. Consumer privacy preferences Finally, to maintain consumer trust as we progress, it's important to acknowledge consumer privacy preferences. Given consumers' concerns around privacy and security, this is an important element within the path forward. Businesses that are transparent around the use of data have been shown to garner greater consumer trust than those that don't offer that transparency. So, any reimagining of digital identity must also have "privacy by design" as a foundation to the approach – not only to meet growing regulatory demands – but, more importantly, to manage consumer expectations. “[It’s] estimated that in 2024 over $43 billion will be lost due to online payment fraud. As we carry on into an unknown future, disrupted by the pandemic, this interwoven nature of identity-security-privacy will play a vital part in making sure our internet, workplace, government services, and banking are safe havens.” -Digital Identity Report 2020-2025, Juniper Research Learn more about: Importance of the evolution of digital identities, including the ability to manage and access the growing volume of online accounts. Advancement of the identity space occurring through the simplified transmission of information via APIs, but the challenge remaining to ensure data is valid, authentic, and from an authorized person. Government attempts at digital identities have faced many challenges, but these use cases continue to progress the development of the digital identity landscape. Benefits to fraud management through the adoption of digital identities can be tremendous – decreasing risk by decoupling identities from transactions, making them more secure from both ends. Usability is king – a good customer experience underlying the use of digital identities will be critical to adoption, and therefore success. Maturation of identity offerings is currently occurring and what’s likely to be successful includes solutions that simplify identity services and those that rely on broader ecosystems. Remote working changes the enterprise approach, with the adoption of Zero Trust Architectures and relevant supporting technologies continuing to emerge to create a safe, yet flexible working environment. The digital identity competitive landscape is evaluated, including vendor analysis and Juniper’s leaderboard. Related stories: Fraud trends during a very pandemic holiday Digital Identity and Blockchain: What lenders need to know Why consumer trust in the digital experience is so important in a pandemic era

Get the latest from our global experts with these top December headlines, including meeting the demand for digital, increasing consumer expectations, women leading artificial intelligence, and protecting against fraudsters over the holiday shopping season. Investment priorities to meet consumer demand for digital banking In this BAI Banking article, Chris Fletcher, SVP Decision Management & Cloud Services, explores the investment required of financial institutions to transform their use of data and analytics and deliver on credit risk strategies. What’s the proper path for better payments? In context to consumers’ digital expectations post-Covid-19, Progressive Grocer considers the future of payments in food retail and beyond – with contactless payment options already rolling out at a large drug store chain. Wisdom from the women leading the AI industry, with Laura Stoddart of Experian Authority Magazine speaks with Laura Stoddart, Data Scientist, about her career path, her experiences working on ethical AI and using emerging datasets to evaluate risk as well as her thoughts on the future of this industry. #TradeTalks: Increasing consumer demands and expectations Steve Wagner, Global Managing Director of Decision Analytics, joins Nasdaq’s Jill Malandrino to discuss recent research findings on increasing consumer demands and digital expectations, and ongoing considerations for a post-Covid-19 world. A holiday season like no other: What to know to guard your company against fraud Itay Levy, Forbes Councils member and CEO and Co-Founder of Identiq, provides his perspective on the increased preference for online shopping and the need to strike the right balance between customer experience and efforts to mitigate fraud. Stay in the know with our latest insights:

In this Tech Talks Daily podcast, Shri Santhanam, Executive Vice President and General Manager of Global Analytics and AI, speaks with podcaster Neil C. Hughes. Santhanam discusses trends based on data from our recent Global Insights Report, which found that nearly 70% of businesses have used either machine learning or AI in business management and almost 60% of businesses are increasing their budget for analytics and customer creditworthiness in the next 12 months. Here are highlights from this 21-minute podcast: Covid-19 disruption has become a catalyst for breaking largely mindset-based transformation barriers, leading to unprecedented digital disruption and adoption of advanced technologies Experian global research confirms a fundamental change in the way businesses and consumers think about digital adoption and experiences Businesses will continue to increase budgets to grow data science resources to align their intent with their capacity Consumers have high expectations and little patience through their digital engagements, with 1/3 of customers only willing to wait 30 secs or less before abandoning an online transaction The greatest success from analytics and AI in business is realized when teams are focused and agile in their approach Listen now: Get more insights from these podcasts featuring Shri Santhanam: New Podcast from AI in Business: The evolution of the data business in the age of AI What is the right approach to AI and analytics for your business? Four fundamental considerations Forbes Podcast: Looking to Data, Analytics and AI to plan the way forward

Explore these November headlines to stayin-the-know. Coverage includes forward-looking fraud prevention, International Fraud Awareness Week, and consumer and business research takeaways from our global experts. Fraud prevention strategies to prepare for the future Chris Ryan, Senior Fraud Solutions Consultant, provides tips on proactively combatting fraud risks to be positioned for success in a post-Covid-19 world — including categorizing fraud and using advanced analytics and technology to keep pace. #IFAW2020 Interview: David Britton, VP of Industry Solutions, Experian For International Fraud Awareness Week, David Britton, Vice President of Industry Solutions, speaks with Infosecurity Magazine about the current fraud landscape, common fraudster tactics, and best practices for preventing fraud. Only 30 seconds to impress — meeting APAC consumers’ online expectations Sisca Margaretta, Chief Marketing Officer for Experian Asia Pacific, explains why speed, seamlessness, and a thoughtful user experience are no longer nice-to-haves, but musts in today's environment. Pandemic entitlement: Consumers demand more online, Experian finds This MediaPost article explores business sentiment verse consumer expectations for their digital experience in the wake of Covid-19, with insights on how businesses can win from Steve Wagner, Global Managing Director of Decision Analytics. Are APAC banks equipped to help consumers in financial distress while juggling credit risk? Ben Elliot, CEO, Experian Asia Pacific, discusses the impact of Covid-19 on consumer financial wellbeing and spending power, and what the financial services and insurance industries can do to help those in financial distress while effectively managing credit risk. Stay in the know with our latest insights: