World

To quote The Rime of the Ancient Mariner, ‘water, water everywhere, / nor any drop to drink.’ I think the same can be true of data. While organizations have more data than ever before, very few are able to capitalize on this resource and actually leverage it for insight. There is no question on the value of data. It is viewed as a key competitive advantage, and in some instances, a strategic financial asset. However, translating data into meaningful insight is a completely different task to storing and managing it from a regulatory perspective. We see many companies investing in all sorts of data initiatives, like analytics, machine learning automation, data governance, customer insight, etc. Yet, most companies still report they are not sufficiently data driven. Each year we conduct a global study of data usage and data management practices. This year, we surveyed over 1,000 practitioners on how they want to leverage data. The research dug into some of the obstacles they face and why so few are able to leverage data for insight. We found three key areas emerge. First, there is a large degree of distrust in information. The average professional looking at data does not understand how that data got there, when it is useful, and what state it is in. While data can lead to increased agility and better decision making, a significant level of distrust often causes leaders to fall back on making decisions by gut instinct rather than by informed data insight. In fact, we have consistently seen over the past several years that people believe almost a third of their data is inaccurate. Second, we are seeing a rising level of data debt. Data debt is a lot like technical debt. You have a set of data assets that aren’t necessarily fit for purpose or have a high degree of inaccuracy. Unless you take the time to fix that information and govern it properly, you are always going to have a suboptimal data operation. In turn, poor quality means many companies are not fully seeing the ROI or expected benefit from some of the investments they are making. Finally, there is a data skills shortage. This doesn’t just mean data professionals, like data analysts, chief data officers (CDOs), and data scientists. There is also a general lack of understanding around data within the broader business. We see a growing number of companies talking about enabling wider usage of data across the business and wanting to do more with data insight, but very few people across organizations are truly data literate. Our survey results indicated a tide changing where now most companies report that data literacy needs to be a core competency of employees over the next five years. To generate the level of insight needed to fully leverage data as a valuable asset, organizations have to start to tackle issues around inaccuracy, trust, and certainly data skills. Without fixing these components, organizations will continue to be surrounded by all of this useful data that doesn’t actually provide them with what they need. To learn more about these challenges and our new study, please download the report at https://www.edq.com/resources/data-management-whitepapers/2020-Global-data-management-research/.

In today's fast-paced markets, businesses of all sizes strive for an edge over competition, especially when it comes to wining over consumers' hearts and minds. Many find that competitive advantage in the way they apply artificial intelligence to improve their customer decision-making for high business performance. Data strategies for high-performance decisioning In today's fast-paced markets, businesses of all sizes strive for an edge over competition, especially when it comes to wining over consumers' hearts and minds. Many find that competitive advantage in the way they apply artificial intelligence to improve their customer decision-making for high business performance.In fact, recent research we commissioned from Forrester Consulting shows that this. The ability to make meaningful decisions that match your customer's context at a given point in time requires a solid understanding of their needs and goals. Having access to relevant data is essential to consistently deliver experiences that matter. Timing and availability of data is equally important to improving your customer-level decision-making; to make those sought-after better, contextual decisions, you need to have the pertinent data available at the right place and time to meet that given consumer's moment of need. For example, in an operational environment, this may translate into accessing the right type, amount and quality of data in real time, so you are able to respond how and when your customer expects. The role of responsible usage of data in building, fuelling, and maintaining your AI-driven business The energy needs of athletes exceed those of the average person. Similarly, in the AI world, data (nutrient) needs for high-performance require consistent markers over a long period of time. Data scientists looking after credit and fraud risk would use the same variables or 'nutrients' that have been traditionally used for conventional scorecard developments to fuel machine learning methods to build predictive models. These are 'proteins' such as application data, any behavioural data your business has on existing customers, credit bureau data, segmentation data, available public information or transaction data. Some trended economic data can be used as input for developing credit risk methods and governance to fit leading financial reporting standards and frameworks (think of IFRS 9 or Basel, for example). Similarly, to assess affordability, you will need to feed your algorithms with disposable income over your customers' lifetime plus data about how they use it. Financial data about customers' savings, and investments allows for more accurate risk management while property related info derived from rental data is useful for extending personalised credit offers. Meanwhile, more and more businesses are using speech and text data obtained through voice recognition to improve the collection process. In fact, recent research we commissioned from Forrester Consulting shows that this 'race for the customer' comes down to who knows them best. The ability to make meaningful decisions that match your customer's context at a given point in time requires a solid understanding of their needs and goals. Having access to relevant data is essential to consistently deliver experiences that matter. Timing and availability of data is equally important to improving your customer-level decision-making; to make those sought-after better, contextual decisions, you need to have the pertinent data available at the right place and time to meet that given consumer's moment of need. For example, in an operational environment, this may translate into accessing the right type, amount and quality of data in real time, so you are able to respond how and when your customer expects. The role of responsible usage of data in building, fuelling, and maintaining your AI-driven business The energy needs of athletes exceed those of the average person. Similarly, in the AI world, data (nutrient) needs for high-performance require consistent markers over a long period of time. Data scientists looking after credit and fraud risk would use the same variables or 'nutrients' that have been traditionally used for conventional scorecard developments to fuel machine learning methods to build predictive models. These are 'proteins' such as application data, any behavioural data your business has on existing customers, credit bureau data, segmentation data, available public information or transaction data. Some trended economic data can be used as input for developing credit risk methods and governance to fit leading financial reporting standards and frameworks (think of IFRS 9 or Basel, for example). Similarly, to assess affordability, you will need to feed your algorithms with disposable income over your customers' lifetime plus data about how they use it. Financial data about customers' savings, and investments allows for more accurate risk management while property related info derived from rental data is useful for extending personalised credit offers. Meanwhile, more and more businesses are using speech and text data obtained through voice recognition to improve the collection process.    

To stay ahead of the competition and on the path of sustained growth, you need clear line of sight to both risks and opportunities through the customer lifecycle. Gaining better insights on customers is critical to achieving that, so you can make all the right decisions, big and small, about your customers and business clients. Based on the conversations we have with our clients, we have noticed that most executives are paying a lot of attention to measuring customer experience and reducing friction across digital touch-points through the lifecycle. For customer acquisition, for example, businesses like yours look at time spent on each micro-step (e.g. data field), dropout rates at each of those steps, and do A/B testing at a very granular level. The idea is to understand all points of friction including points of confusion, frustration, etc., so you can learn from those and improve the experience. But this is not an easy task. The various challenges involved are making sense of the vast quantities of data and the immaturity of that data as well as the construct of that data. Given the fast pace at which data analytics change and evolve, our recommendation is that you invest in tools that are data and/or analytics agnostic. Thinking ahead: leveraging data analytics and cloud-based decisioning platforms to design the right customer treatment There is a largely untapped opportunity to leverage data, analytics, optimisation and decision management solutions - such as cloud-based decisioning platforms - to design the right customer treatment and identify the next best action for that customer. Selecting the appropriate timing, medium, and channel for those actions lead to greater consistency and contribute to having more relevant communications with your customers. The more relevant you are, the more precise you are with the offers and the treatments leading to improved response rates, greater connectivity and interaction with the customer. This results in memorable experiences that enhance loyalty and drive profitability.

We are delighted to have been placed on the inaugural Financial Times’ 2020 Diversity Leaders list, released today and accessible here. The organisers spoke to more than 80,000 employees across Europe to build the list, asking employees to rate their own employers as well as other firms around multiple categorise, taking into consideration areas including age, gender, ethnicity, disability, LGBTQ+ and overall diversity of ideas and backgrounds across the company. Over the last few years we’ve worked hard to focus on inclusion and diversity across our global business. We believe that embracing a truly inclusive culture, one where everyone has a real sense of belonging, is critical to building a diverse workforce and fostering innovation. Ultimately, it’s our ambition for our business to become as diverse as the people we serve around the world. We’re dedicated to encouraging diversity at every level within Experian. That means building our culture, our ways of working and our approach in a way that offers equality of opportunity. Supporting our employees from the moment they join our organisation, at every level. Letting people work flexibly, in the way that suits them and opens the door to new opportunities. One of the five key tenets of The Experian Way is “Value Each Other”. That means that each one of us is responsible for making this a great place to work. We treat each other with respect, trust and integrity. We support and invest in each other to help everyone achieve their potential and aspirations. We promote a culture of inclusivity and value diversity of all kinds, including thinking,  knowledge and experience. Our goal is to embrace and celebrate the diversity of ideas and backgrounds across the company. This diversity of thinking, and the way we harness it at Experian, helps to fuel our innovation and ultimately our ongoing success as a business. Like many companies, we have more to do to be as inclusive as we would like to be. But we are proud of the work we’ve done to date, and we are delighted by the recognition given to us today.

Today, I’m pleased to share another strong set of Half Year results for our FY20 fiscal year. We have achieved 7% organic revenue growth, with total H1 growth of 8% when you include acquisitions. The performance reflects the continued success of our core business new product introductions, as well as rollout of our innovation agenda and the investments we have made in globally scalable products. At Experian we are helping our clients get better at acquiring, onboarding and managing their customers’ needs in the digital world. To do this, they are increasingly relying on data, combined with sophisticated analytics and decisioning capabilities, areas in which we excel. In addition, to helping businesses, we are continuing to expand our direct relationships with consumers. Over 70 million people across our three major markets now benefit from free Experian memberships, accessing information and tools to enable them to take control of their finances. A great example of this is Experian Boost in North America, where we enable consumers to voluntarily add payment histories for things like their mobile phone and utility bills to their credit profile. It’s been a successful year to date, but there is plenty more to come. With a continued focus on people, technology and innovation, we are revolutionising the way our industry operates - using the power of data, software and analytics to improve outcomes for everyone. To find out more, click here.

At Experian we’re committed to creating a culture of continuous innovation, from the way we work to the solutions we create. This commitment has helped us create a workplace where our teams across the world have a desire to help change the lives of millions for the better. Justin Hastings, former Chief Human Resources Officer for Experian North America, recently wrote an article for the Forbes Human Resources Council which highlights the importance of creating an inclusive environment in the workplace -- and demonstrates how innovation, developing new products and services, and providing value are all crucial to a companies’ success. The article, “Deliver Innovation By Embracing Inclusion,” explores what it means to build a culture of innovation, and how to ensure employees feel comfortable bringing their different backgrounds and ideas to their role every day. This is the type of innovative culture we’re building at Experian, which celebrates these differences and works to make employees feel valued and empowered to be innovative and productive. Another concept Justin discusses in this article is “innovating to grow.” It’s important to make employees feel connected to their organization and involved in the creation of new products and services. This has a tremendous positive impact with employees providing valuable feedback, and also creating advocacy among team members. For example when developing Experian Boost, which has helped millions of people raise their credit scores, we first beta-tested and shared the innovation internally and were able to garner valuable feedback and support from employees. As a result, we’ve seen tremendous success since the launch of Experian Boost earlier this year. At Experian we truly believe that inclusion is the key to creating a culture of innovation. You can read the full article here.  

For the second year in a row, Experian Costa Rica has achieved recertification from Great Places to Work in the Central America region. The honor recognizes the inclusive workplace culture that Experian Costa Rica employees and leaders have created, making it a dynamic environment for innovation and high productivity. “Getting re-certified as a Great Place to Work provides and enormous sense of pride. As an organization it validates all the efforts we make to ensure a strong healthy employee culture and as a leader it allows us to come to work knowing that we have a culture that employees enjoy working in,” said Adrian Sibaja, Director of Service Delivery for Experian Costa Rica and Chile. Experian Costa Rica is one of four Global Delivery Centers, strategically located centers of operational excellence that support Experian’s regions. The office is home to nearly 1,000 employees across different business units. This honor reinforces the workplace culture we’re fostering, which our employees are happy to brag about in confidential surveys. Costa Rica leadership is always looking for ways to make the employee culture even better. That’s why recognizing employee accomplishments and encouraging partnership between business units are among their top priorities. Congratulations to our Costa Rica colleagues!

Eva lets out a deeply frustrated exhale as she navigates moving boxes in her new apartment towards a nearby chair. She was just trying to update her address online and take care of some online banking money transfers. Now her accounts are frozen, and she has received a message to call the bank's fraud department. How could she be a fraudster? She was only guilty of taking a job and moving to Chicago. Maybe it's time to start thinking about changing banks... Meanwhile, in the bank's Texas-based fraud department, Robert spots Eva's case in his fraud investigations list. He noticed some suspicious activities and leaves Eva a voicemail, wanting to ask her a few questions to verify her identity or otherwise confirm this is in fact a fraudster infiltrating Eva's account. To prevent this potential risk of fraud from escalating, Robert decides it is better to freeze Eva's accounts while he confirms that it's actually Eva who is trying to change her address and not a fraudster using a stolen password. As both Robert and Eva work to connect and clear up this mix-up, Robert isn't getting to spend his time finding actual fraud and protecting his bank from any potential losses. Fraud hubs bring together advanced authentication technology and risk mitigation systems into a single platform As fraud attacks grow more frequent and complex, new technologies have sprung up to help meet the challenge, using a variety of tactics and tools to detect fraud. This is the case of device recognition, malware detection, identity verification, behavioural biometrics, and document verification, just to name a few. Regardless of their choice of tools and techniques, businesses across banking, retail, telecommunications, healthcare, and services industries need to know that the person interacting with them online is who they say they are. Combating fraud with layered tools strengthens businesses' defenses. But without an intelligent approach to connecting those tools, businesses catch too many good customers (like Eva) in their fraud-mitigation nets. By bringing together different types of fraud mitigation and risk management systems on a single technology platform, fraud hubs provide a solid solution to this challenge. How do fraud hubs like CrossCore help both businesses and consumers? CrossCore brings together into a single platform best-in-class tools and services such as advanced analytics, data consortium, device recognition, endpoint malware, and bot detection, behavioural biometrics, and document verification. Experian has also been named by Gartner as a representative vendor in online fraud detection in their April 2019 Market Guide for Online Fraud Detection, for its CrossCore solution.* Our flagship identity and fraud hub connects various functionalities together in a smart, orchestrated way, leveraging machine learning-driven decisioning to deliver a single fraud decision across multiple tools and enabling businesses worldwide to improve their fraud detection capabilities. CrossCore equips businesses with the most applicable tools to combat the specific fraud threats they face in their organisation. The 100 million cumulative transactions we have run on CrossCore to date show us that while one client may need additional protection against synthetic identity fraud, another may face frequent bot attacks in their account opening application, therefore requiring different approaches. It also means that if one tool can't validate a user's identity, another system can provide evidence that this is, in fact, a real customer. It's precisely the advanced analytics underpinning data modeling what gives our clients greater confidence in their identity and fraud decisions. But let's go back to Eva. In her case, CrossCore's fraud risk engine would have fired rules when she was making a change of address, as this action elevates the potential for fraud. But CrossCore's device intelligence would have shown that Eva was logging in from a known mobile phone. She was also using her phone to type information in a way that a normal user (non-fraudster) would do. In that case, CrossCore would have asked for a step-up authentication where Eva is prompted to take a selfie for biometric authentication. Now, Eva can continue to do her banking and access her accounts as she would normally do. This is a relief as Eva checks off more moving-related tasks and can enjoy her new life in a new city. Back in the bank's fraud investigation office, Robert and his colleagues would have never seen a case for their customer, Eva. Instead, they would have been able to focus their energies on high-risk cases, mitigating any emerging fraud threats. They would have also treated Eva as the good, valued customer she is and helped ensure her business in the long run. Whether it's an automotive client in South Africa, a healthcare organisation in the U.S., an insurance company in the UK, a fintech in Australia or a bank in Brazil, CrossCore is helping to solve one of the greatest challenges in decision analytics today: identifying good customers, while reducing fraud. Download the 2019 Global Identity & Fraud Report. *Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.  

As a member of the Forbes Technology Council, I get to publish articles on some of the latest technology trends and best practices. A recent piece, entitled “Are we comfortable with machines having the final say?”, deals with the sensitive issue of decisions being made by complex algorithms and how it impacts all areas of our lives. The article takes a closer look at high-impact decisions, such as loan determinations and health diagnosis, where the lack of understanding how algorithms may be used is becoming of increasing concern. In this context, it raises the importance of Explainable AI (XAI). This is a concept where technology and science are being used to explain how an algorithm or machine reaches a decision and tries to do this in a way that is transparent to users. However, this approach is still being tested and is only used in certain limited circumstances. As humans, we are taught to explain our decisions but we all know how difficult it is - and science has repeatedly shown how easily biased we are. XAI still has some way to go, but we can inspect, test and pick machines apart in a way we can never do with the human mind. So perhaps one day we will find a way to truly explain a machine’s decision. Whether that would make us comfortable with the machines having the final say, is still to be seen. Check out the full article here.