We’re delighted to have been named as one of Britain’s ‘Most Admired Companies’ (BMAC) in Management Today’s annual survey, coming 21st in a list of nearly 250 leading firms from a variety of sectors, and taking third place in the ‘Business Support Services’ sector. Our 17,000 colleagues around the world work hard every day to service and power opportunities for our customers and this award is testament to the commitment they bring to our business every day. The hard work doesn’t stop here. We continue to strive for the highest standards across our global organisation, and we remain committed to delivering the very best services that can empower millions of people to stay in control of their finances, and help businesses meet the needs of their customers. For further information on BMAC, the winners and the methodology, please see: https://www.managementtoday.co.uk/bmac
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.
Today, we stand at the forefront of a digital revolution that is reshaping the financial services industry. And, against this backdrop, financial institutions are at vastly different levels of maturity; the world’s biggest banks are managing large-scale infrastructure migrations and making significant investments in AI while regional banks and credit unions are putting plans in place for modernization strategies, and fintechs are purpose-built and cloud native. To explore this more, I recently had the privilege of attending the annual Reuters NEXT live event in New York City. The event gathers globally recognized leaders across business, finance, technology, and government to tackle some of today’s most pressing issues. On the World Stage, I joined Del Irani, a talented anchor and broadcast journalist, to discuss the future of lending and the pivotal role of data and AI in building a more inclusive financial system. Improving financial access Our discussion highlighted the lack of access to traditional financial systems, and the impact it has on nearly 100 million people in North America alone. Globally, the problem affects over one billion people. These people, who are credit invisible, unscoreable, or have subprime credit scores, are unable to secure everyday financial products that many of us take for granted. What many don’t realize is, this is not a fringe subset of the population. Most of us, myself included, know someone who has faced the challenges of financial exclusion. Everyday Americans, including young people who are just starting out, new immigrants and people from diverse communities, often lack access to mainstream financial products. We discussed how traditional lending has a limited view of a consumer. Like looking through a keyhole, the lender’s understanding of the person in view is often incomplete and obstructed. However, with expanded data, technology, and advanced analytics, there is an opportunity to better understand the whole person, and as a result have a more inclusive financial system. At Experian, we have a unique ability to connect the power of traditional credit with alternative data, bringing a more holistic understanding of consumers and their behaviors. We are dedicated to leveraging our rich history in data and our expertise in technology to create the future of credit and ultimately bring financial power to everyone. The future of lending After spending two days with over 700 industry leaders from around the world, one thing is abundantly clear: much like the early days of the internet, today, we are at the cutting-edge of a technical revolution. Reflecting on my time at Reuters NEXT, I am particularly excited by the collective commitment to drive innovative, and smarter ways of working. We are only beginning to scratch the surface of how data and technology can transform financial services, and Experian is positioned to play a significant role. As we look to the future, I am excited about the ways we will create new opportunities for businesses and consumers alike.
The advertising ecosystem has seen significant transformation over the past few years, with increased privacy regulation, changes in available signals, and the rise of channels like connected TV and retail media. These changes are impacting the way that consumers interact with brands and how brands understand and continue to deliver relevant messages to consumers with precision. Experian has been helping marketers navigate these changes, and as a result, our marketing data and identity solutions underpin much of today’s advertising industry. We’re committed to empowering marketers and agencies to understand and reach their target audiences, across all channels. Today, we are excited to announce our acquisition of Audigent—a leading data and activation platform in the advertising industry. With Audigent’s combination of first-party publisher data, inventory and deep supply-side distribution relationships, publishers, big and small, can empower marketers to better understand their customers, expand the reach of their target audiences and activate those audiences across the most impactful inventory. I am excited to bring together Audigent’s supply-side network as a natural extension to our existing demand-side capabilities. Audigent’s ability to combine inventory with targeted audiences using first-party, third-party and contextual signals provides the best of all worlds, allowing marketers to deliver campaigns centered on consumer choices, preferences, and behaviors. The addition of Audigent further strengthens our strategy to be the premier independent provider of marketing data and identity, ultimately creating more relevant experiences for consumers. To learn more about Experian and Audigent, visit https://www.experian.com/marketing/ and https://audigent.com/.
When it comes to cybercriminals and threat vectors, we need to expect the unexpected. Experian’s 12th annual Data Breach Industry Forecast highlights several potential trends for 2025, with AI playing a central role. This year has already seen more data breaches and impacted consumers than 2023, indicating that global data breaches are not slowing down. Some things to watch out for next year includes the potential for more internal fraud. As companies train employees on AI, there is a growing risk that some will misuse their knowledge for internal theft and sourcing sensitive information. Another trend may be cyberattackers targeting large data centers, with the growth of generative AI introducing power as a new attack vector. It’s reported that a single ChatGPT query uses significantly more electricity than a standard Google search, making data centers and cloud infrastructure vulnerable, especially in countries with varying security standards. We expect AI-related attacks to dominate the headlines next year and investments in cybersecurity will increase to tackle this emerging threat, as hackers leverage AI for phishing, password cracking, malware, and deepfakes. Jim Steven, Head of Crisis and Data Response Services at Experian Global Data Breach Resolution in the UK, anticipates that global data breaches will persist at their current rate next year. He notes that ransomware attacks are likely to become even more sophisticated with the integration of AI. Additionally, Steven predicts that threat actors will escalate their tactics to achieve greater rewards, and the misuse of consumer data to damage reputations will increase in 2025. To access the complimentary report, click here.