What are lenders prioritising when it comes to Gen AI? We take a look at five transformative use cases in lending, and organisational priorities for integrating Gen AI into customer lifecycle processes. Although Generative Artificial Intelligence (Gen AI) only launched publicly in the form of Chat GPT last November, adoption has been widespread and rapid. Even in typically risk-adverse industries like financial services, our research shows that there is widespread recognition that Gen AI could deliver a range of benefits across business functions. We identified five areas of focus for lenders based on our research. In a study conducted by Forrester Consulting on behalf of Experian, we surveyed 660 and interviewed 60 decision makers for technology purchases that support the credit lifecycle at their financial services organisation. The study included businesses across North America, UK and Ireland, and Brazil. The qualitative research showed that lenders are already using a type of Gen AI, Large Language Models (LLMs), in their operations, with a focus on testing across areas such as customer service and internal processes before deploying to credit operations. We look at the potential use cases, and how businesses are using Gen AI now. 1. Personalised customer experience Customers today expect a personalised lending experience that is tailored to their unique needs and preferences. GenAI can leverage customer data to generate personalised loan offers, recommendations, and repayment plans. This helps lenders improve customer satisfaction and loyalty, leading to increased customer retention and revenue growth. This is an area that is front of mind for the companies in our research – nearly half of businesses surveyed are planning to implement or expand technology capabilities to either upsell or retain customers in the next 12 months. Furthermore, 50% of companies believe that offering more tailored underwriting and pricing is a top priority in their credit operations, followed by 44% who also aim to increase personalisation in marketing, products, and services to their customers. According to the research, some organisations have formed alliances with technology providers like OpenAI and Microsoft to investigate and further explore the use of LLMs. These partnerships involve analysing customer data to identify opportunities for cross-selling. 2. Enhancing models with new data sources With new data sources emerging all the time, Gen AI is one of the technologies that will most likely accelerate the opportunity for businesses to incorporate them into models. Lenders could include sources such as social network data into their models by using LLMs. This unstructured data, including customer emotions and behaviours on social networks, would be treated as an additional variable in the models. According to the research social media data and psychometric data is already used across financial services, to varying degrees. It showed that 35% of retail companies use social media data, while 29% of FinTechs use psychometric data. Auto finance companies sit at lower end of the adoption scale, with only 12% using social media data and 15% psychometric data. 3. Operational efficiencies Gen AI can help bring operational efficiencies to customerjourneys across the entire lifecycle, offering lenders theability to automate and streamline various processes,resulting in improved productivity, cost savings, andenhanced customer experiences. One of the top challenges for businesses surveyed isimproving customer journeys during onboarding, and thiswas particularly significant for credit unions / buildingsocieties (53%). 4. Detecting and preventing fraud Gen AI can play a crucial role in fraud detection by analysing patterns and anomalies in vast datasets. By leveraging machine learning techniques, Gen AI models can proactively identify potentially fraudulent activities and mitigate risks. The ability to detect fraud in real-time improves the overall security of lending operations and helps protect lenders and borrowers from financial losses. Detecting and preventing fraud is a constant challenge for lenders. 51% of retailers and 47% of credit unions/ building societies surveyed said that reducing fraud losses is a key challenge for them. 5. Customer service Driven by advances in the machine learning and AI space, the world of customer service has benefited hugely from the adoption of virtual assistants and chatbots in recent years. This looks to continue, with businesses saying that LLMs are being tested for customer service purposes, allowing lenders to identify customer issues and automate actions. What's next for lenders? The research found that lenders are utilising various machine learning techniques like regression, decision trees, neural networks, and random forest, along with LLMs. Businesses are in the early stages of exploring how they can use LLMs in credit risk models, but it will undoubtedly involve a blend of existing and new capabilities. As with any emerging technology, it’s important to look at potential risk. The research indicated that organisations see challenges and concerns when it comes to the use of LLMs in their models. It is crucial to ensure the models are trusted, validated, and properly understood to avoid reliance on outsourced solutions and maintain control and visibility over the models’ functions. The ability to explain decisions in Gen AI to avoid bias can be difficult, and businesses will be watching the regulators to understand how best to proceed. There is no doubt, however, that Gen AI will optimise the credit customer lifecycle, creating vast opportunities for lenders. Download PDF More on Gen AI

In a study conducted by Forrester Consulting on behalf of Experian, we surveyed 660 and interviewed 60 decision makers for technology purchases that support the credit lifecycle at their financial services organisation. The study included businesses across North America, UK and Ireland, and Brazil. More on Gen AI

Fraud prevention is a critical concern for businesses today. To help combat this ever-present threat, the consortium approach has emerged as a powerful tool in the fight against fraud. By pooling resources, expertise, and creating visibility, consortium members can be more effective in detecting and preventing fraudulent activities. con-sor-tium noun: A group of people, countries, companies, etc., who are working together on a particular project. What is a consortium? Within business, consortiums are a global concept and can operate under multiple categories, including finance, marketing, and tech. A well-known, successful example is Star Alliance. They are a group of airlines, whose agreement enables their members to share and benefit from flights, airport lounges, and frequent flyer programs. All Star Alliance members are working towards the same goal, which is to offer their customers a seamless travel experience. Key benefits of the consortium approach Resource sharing: Pooling resources like funding, expertise, and infrastructure can lead to cost savings and efficient resource utilisation. Risk mitigation: Shared risks make it easier for organisations to tackle ambitious projects or ventures with reduced individual exposure. Access to expertise: Members can tap into the collective knowledge and skills of the consortium, enhancing their capabilities. Market influence: Consortiums often have more influence in negotiations, regulations, and standards-setting, benefiting all members. Innovation: Collaboration can foster innovation through cross-pollination of ideas and technologies among members. Economies of scale: Consortiums can negotiate better deals on purchases or services due to their combined purchasing power. Reduced competition: In some cases, members can reduce direct competition among themselves by coordinating efforts. Market entry: Consortiums can facilitate market entry, especially in foreign markets, by leveraging each other's networks and knowledge. Shared infrastructure: Access to shared facilities or infrastructure can save costs and accelerate projects. Brand recognition: Being part of a reputable consortium can enhance an organisation's credibility and market presence. However, consortiums also come with challenges such as coordination issues, conflicts of interest, and shared decision-making. Successful consortiums require effective governance structures and clear agreements among members. Consortiums in fraud detection and prevention The success of a consortium relies on the collective commitment of its members to a shared goal. In the context of fraud prevention, this means maintaining consistent and high-quality insights across all members. To achieve this, consortium members adhere to an agreement that covers elements such as data quality and data frequency. These agreements ensure that all participants contribute their best insights and information. By fostering a culture of cooperation and sharing, consortiums create an environment where valuable insights can be harnessed to combat fraud effectively. However, it's crucial to emphasise that the success of consortiums ultimately depends on the active participation and contribution of all its members. Consortiums can only thrive when every member is dedicated to making their quality insights accessible to the group. Read more about how consortiums can revolutionise fraud detection and prevention by sharing data on fraudsters across different product types and industry sectors with Hunter.

With an ever-growing number of data sources, businesses must be able to rapidly access and integrate them into decisioning processes using no-code tools to stay ahead of the competition. Today’s customer journey has become increasingly sophisticated. As most firms that interact with customers can attest, this journey is a dynamic process shaped by a range of decisions. Businesses need to decide what is the most compelling offer to deliver to a new customer. Should you approve their loan application? Could the customer gain more from sustainability-linked loans or greener mortgages? What is rich data? These diverse decisions are ideally informed by rich data. This is all the available data, including new data derived from analytics using advanced techniques such as Machine Learning and using rules to make predictions and to calculate scores. While most firms have this data, it is difficult to gather, prepare and integrate into the decisioning processes. Multiplicity of data sources Data types and sources are growing. With regulatory bodies gradually approving the use of more data globally, businesses are faced with an opportunity dressed up as a challenge. Speedy integration of different data sources gives organizations a competitive edge, so finding vendors that can enable firms to utilize available data will positively impact them from a cost efficiency perspective, while also creating the potential for revenue growth. The future is to empower business users with no-code data management No-code data management capabilities add a whole new meaning to self-sufficiency for businesses. It will enable teams across organizations to rapidly change data-driven strategies without much vendor involvement. Gartner estimates that by 2025, 70% of new applications developed by enterprises will use low-code or no-code technologies, up from less than 25% in 2020.   Moving towards client self-service with no-code capabilties is the goal of most businesses. These capabilities are already allowing teams supporting clients to rapidly integrate data sources into their solutions, providing the perfect test ground for business user enablement. If a decision strategy requires changes and a new data source, Experian Decisioning users can quickly adapt. They can now gather and prepare the right data and deliver it to the system within days. These changes can be instantly published through secure and easily adjustable APIs that support the latest industry standards and frameworks such as OpenAPI and OAuth. An effective customer journey relies on informed decisions and these decisions rely on the right data and advanced analytics. While Experian's Decisioning platform is well known for automating a range of decisions across the customer lifecycle, it is the data integration capabilities that ensure these decisions are informed by rich data and insights. Creating a harmonious relationship that produces superior and trustworthy results for businesses. No-code data management enables businesses with easy and rapid data source access to deliver rich and insightful data to decisioning processes.

With heightened consumer demand for an improved customer experience online, and the increasing threat of fraud, how can organizations ensure secure and efficient customer onboarding in today's digital landscape? Onboarding the highest number of customers while maintaining compliance and security Digital account opening is in demand. Businesses are competing to create the most effective onboarding experience, while managing the need to draw on multiple sources during account opening. The onboarding stage of the customer lifecycle plays a pivotal role in establishing trust between the customer and the business. Friction during the digital account opening process can lead to customer dropouts, resulting in lower growth for organizations. Moreover, the ever-present threat of fraud necessitates organizations to be vigilant and enhance customer journey with an added layer of verification and protection. Liminal, a leading market intelligence firm specializing in digital identity, cybersecurity, and fintech markets, recently recognized Experian as a market leader for compliance and fraud prevention capabilities and execution in its Liminal Link Index on Account Opening in Financial Services. Download report The report highlights that solution providers in financial services are focused on delivering high levels of assurance while maintaining regulatory compliance and minimizing user friction. Access to real-time verification data, risk analytics and decision-making strategies make it possible for clients to verify identities, detect and prevent fraud, and ensure regulatory compliance. Experian’s identity verification and fraud prevention solutions, including CrossCore® and Precise ID®, received the highest Link Score out of the 32 companies highlighted in the report. It found that Experian was recognized by 94% of buyers and 89% identified Experian as a market leader. “We’re thrilled to be named the top market leader in compliance and fraud prevention capabilities and execution by Liminal’s Link Index Report. We’re continually innovating to deliver the most effective identity verification and fraud prevention solutions to our clients so they can grow their business, mitigate risk and provide a seamless customer experience.”Kathleen Peters, Chief Innovation Officer for Experian’s Decision Analytics business in North America The report offers valuable insights into the market overview, demands, challenges, purchasing criteria, vendor landscape, landscape analysis, and buyer opportunities. Access full report

In today's fast-paced digital landscape, businesses are inundated with an unprecedented amount of data and information. Making informed decisions with the data quickly and effectively has become a crucial factor for success. Enter digital decisioning—a transformative approach that harnesses the power of data, analytics, and automation to drive reliable and expedited decision-making. This article delves into the world of digital decisioning, exploring its significance, components, and benefits.  The Essence of Digital Decisioning  At its core, digital decisioning is the process of leveraging software solutions that use digital decisioning platforms or custom-built engines to author decision logic; use decision intelligence technologies such as machine learning and AI; use digital decisions in vertical and horizontal use cases; and manage the full decision logic lifecycle, including feedback loops, to continuously improve decision logic. It enables organizations to make well-informed choices by automating and optimizing complex decision processes. By amalgamating data from various sources in real-time, including credit data, user behavior, market trends, historical data, and external factors, digital decisioning ensures that timely decisions are not only data-driven but also contextually relevant.  Components of Digital Decisioning  Continuous Data Feed: This is the lifeblood of digital decisions. Organizations normalize data from disparate sources to form comprehensive and accurate datasets. Customer data might include income, credit history, transactional data, bill payment, or digital footprint data; however, regardless of the sources, it’s critical that data is coalesced into a single, virtualized view.   Advanced Analytics and Machine Learning: Analytics and machine learning algorithms are deployed to extract meaningful insights from the collected data. These insights are used to model decision scenarios, predict outcomes, and uncover hidden patterns.  Decision Models: Decision models are created based on the insights derived from data analysis. These models define the rules and logic for making decisions, incorporating factors such as risk tolerance, business goals, and regulatory compliance.   Direct Feedback Loop: Every decision has an outcome. For example, an automated loan offer is either accepted or declined by the customer. These outcomes — good and bad — automatically feed into the decisioning model, which enables the machine learning technology to “learn” which decisions are optimal, given the circumstances and customer profile. This enables the model to adapt and grow more accurately and precisely over time.  Automation: Automation engines execute the decision models in real time, allowing for rapid and consistent decision-making without human intervention. This enhances efficiency and minimizes the risk of errors.  According to a 2022 Gartner poll, the CIO Agenda, more than 80% of companies plan to keep or grow their investment in automation solutions.  Benefits of Digital Decisioning  Enhanced Accuracy: Digital decisioning eliminates human biases and inconsistencies, resulting in more accurate and objective decisions.  Improved Efficiency: Automation reduces decision-making time from hours or days to milliseconds, enabling organizations to respond swiftly to market changes and customer demands.  Hyper Personalization: By considering individual preferences, behaviors, and history, digital decisioning facilitates the creation of tailored experiences for customers, leading to higher satisfaction and engagement.  Scalability: The automated nature of digital decisioning ensures that it can handle a high volume of decisions seamlessly, making it ideal for businesses experiencing rapid growth.  Regulatory Compliance: Explainable decision models can be designed to incorporate regulatory guidelines and compliance requirements, reducing the risk of legal complications. Use Case: Respond faster to credit card applications and personalize cross-sell offers  Customers apply online for a credit card from a bank. As they’re being pre-qualified, digital decisioning will instantly analyze the customers’ accounts with the bank including disclosed and undisclosed cash flow. A digital decisioning software solution enables the bank to assess risk exposure and anticipate the customer’s immediate need(s), thereby automating the application assessment and approval steps to reduce approval times from weeks to minutes. Based on the bank’s comprehensive understanding of that customer at that moment, it triggers a personalized cross-sell offer for another relevant financial product, automatically boosting incremental revenue.  Conclusion Digital decisioning marks a pivotal advancement in how choices are made in business. By harnessing the power of data, analytics, and automation, organizations can make faster, more accurate decisions that are aligned with their goals and market realities. As this technology continues to evolve, it will reshape industries and empower individuals to navigate the complex digital landscape with confidence.   Experian’s decisioning management platform allows clients to operationalize the power of rich data, advanced analytics, and automated decisioning software to support the customer lifecycle. Its key differentiators include credit risk, fraud risk, and strategy expertise, fast deployment of strategies into test and production, empowerment of business users, and proactive monitoring of strategy performance by users. Its key use cases include reducing acquisition costs, credit risk, and fraud risk, and improving acceptance rate and the customer journey.  Experian has been named a Technology Leader in the August 2023 SPARK Matrix on Digital Decisioning Platforms report published by Quadrant Knowledge Solutions.  The report highlights the growth of decisioning platforms and the changing market trends that are driving adoption, including the role machine learning and AI are playing in the technology market. This placement is proof that Experian offers best-in-class capabilities through market-leading data, orchestration and automation, advanced analytical models, decision performance, and reporting. Our cloud-based infrastructure enables a scalable and modular platform that allows our solutions to be suitable for customers of all sizes.   Read the report Experian’s Decisioning Management Platform: Accelerating analytics, decisioning, and fraud detection automation Continuous improvement loop: Advanced machine learning models improve decisioning quality 

As economic uncertainty continues to loom, the threat of fraud continues to grow and is becoming more sophisticated. It’s only going to get worse. Due to intensifying inflationary pressures, prices and costs have been increasing which has led to financial hardship impacting individuals and businesses. This provides an opportunity and motive for bad actors to figure out new ways to commit fraud. Federal Trade Commission data shows that consumers reported losing nearly $8.8 billion to fraud in 2022, an increase of more than 30 percent over the previous year. PwC’s Global Economic Crime and Fraud Survey 2022 shows 51% of surveyed organisations say they experienced fraud in the past two years, the highest level in their 20 years of research. Additional investments in fraud prevention technology are a priority for businesses to combat these evolving threats, according to Experian's Sept. 2022 Global Insights report, which states that 94% of businesses report it as the top priority. Since fraud is becoming more sophisticated, part of the challenge that businesses face is to constantly evaluate multiple solutions so that they can continuously improve their fraud detection and prevention capabilities. Investments that can deliver the highest ROI are the solutions that are integrated and orchestrated in a comprehensive fraud reduction intelligence platform. This gives businesses the flexibility to manage evolving strategies and mitigate threats with real-time decisioning. Experian’s CrossCore is an integrated digital identity and fraud risk platform. It offers global solutions to help protect businesses from fraud and maintain compliance with regulatory requirements, using real-time risk analytics and decision-making strategies. The platform aggregates various fraud and identity verification sources to consolidate risk and trust decisions for Experian clients throughout the consumer journey.   Experian’s CrossCore has been recognized as an Overall Leader, Innovation Leader, Product Leader, and Market Leader in KuppingerCole’s Fraud Reduction Intelligence Platform Leadership Compass 2023. This recognition highlights Experian's comprehensive approach to combating fraud. It validates that CrossCore offers best-in-class capabilities by augmenting Experian’s industry-leading identity and fraud offerings with a highly curated ecosystem of partners which enables further optionality for our clients based on their specific needs.  Read the report CrossCore's Capabilities

Latest Global Insights Report: How supporting consumers in a time of uncertainty can help businesses adapt and grow A changing economic landscape needs a new approach The new digital consumer is here to stay and they expect businesses to support them with the products and services they need to navigate the rising cost of living, in a secure digital world personalised to them. Find out how: Our latest research reveals how economic uncertainty is evolving the experiences and expectations of digital consumers. From increasing the demand for credit options and financial inclusion, to deepening the need for trust, security and being seen. Read the report to find out how businesses can benefit from responding to changing consumer needs - including the additional tools and resources consumers and businesses may need to maintain financial health: What do digital consumers want? The global economy is under pressure with inflation raising prices across the world. In response, consumer behaviour is shifting, as people tackle the increased cost of living, and the prospect of an economic downturn. Digital consumers are continuing to manage their lives online and are expecting businesses to take the lead on improving the digital environment. A quality online experience is paramount, or consumers will move on. 1 in 4 businesses lost more than 10% of their customers in 2021, due to “suboptimal” digital experiences. A range of payment options including BNPL As prices rise, consumers are expecting to spend more online and are looking for varied credit options to help manage their finances. The demand for buy-now-pay-later (BNPL) options is also growing, with more consumers using BNPL to buy household staples. Consumers look favourably on companies that offer BNPL, but companies will have to find the right balance between supporting customers and managing credit risk. 32% of BNPL purchases were for groceries, up from 27% in March. Financial inclusion Economic uncertainty is accelerating the need for greater financial inclusion. Businesses need to find more creditworthy consumers and support them with responsible and sustainable products and services. 1 in 3 businesses is in the process of rolling out financial inclusion initiatives Security and trust As consumer need increases, so does fraud, including cost of living scams. Security is now a top priority for consumers around the world, alongside privacy, convenience and personalisation. 50% of consumers say they’re concerned about their online transactions. However, trust in emerging customer recognition tools is increasing, with consumers’ top three including physical biometrics, PIN codes and behavioural biometrics. Personalisation Consumers who trust businesses are more willing to share their data, enabling companies to create more personalised experiences, which in turn, improves consumer trust. 46% of consumers say that personalisation (receiving offers that fit their needs) is the most important aspect of their online experience. Read our report to discover the challenges and opportunities facing consumers and businesses and the tools, resources and strategies that can help your company get ahead. The survey results represent 6,000 consumers and 2,000 businesses across 20 countries, including Australia, Brazil, Chile, China, Columbia, Denmark, Germany, India, Indonesia, Ireland, Italy, Malaysia, Netherlands, Norway, Peru, Singapore, South Africa, Spain, UK, and US.   Read our report

The survey underpinning these insights encompasses 1,849 business respondents and 6,062 consumers from 20 countries, including Australia, Brazil, China, Chile, Colombia, Denmark, Germany, India, Indonesia, Ireland, Italy, Malaysia, The Netherlands, Norway, Peru, Singapore, South Africa, Spain, UK, and US. We’ve also included interviews with consumers from Brazil, Germany, the UK, and US.

The survey underpinning these insights encompasses 1,849 business respondents and 6,062 consumers from 20 countries, including Australia, Brazil, China, Chile, Colombia, Denmark, Germany, India, Indonesia, Ireland, Italy, Malaysia, The Netherlands, Norway, Peru, Singapore, South Africa, Spain, UK, and US. We’ve also included interviews with consumers from Brazil, Germany, the UK, and US.

Our latest Global Identity and Fraud Report reveals that fraud has been of high concern for consumers over the past year. In fact, more than half of consumers report that they are worried about online transactions, and 40% say that their concern has increased over this period. Data breaches, well-publicised scams, and direct first-hand experience with fraud have all contributed to these higher levels of concern. Our study shows that 77% of consumers had increased concern after experiencing online fraud, with more than half of consumers surveyed having had a close encounter with fraud: 58% of consumers say they have been a victim of online fraud, know someone who has been a victim, or both 57% of consumers say they have been a victim of identity theft, know someone who has been a victim, or both 53% of consumers say they have been a victim of account takeover, know someone who has been a victim, or both As a consequence, it makes sense that consumers rank security and privacy above convenience and personalisation when evaluating their online experience and expect businesses to take the necessary security steps to protect them online. We look at the main factors that play a role in the high levels of fraud concern among consumers and what businesses should do to address challenges in their fraud strategies. Three contributing factors to increased fraud concern among consumers Identity fraud has increased  Our research also unveils that identity theft has overtaken credit card theft as consumers’ biggest security worry across all age groups. Furthermore, a recent report from the UK showed that recorded cases of identity fraud have grown by 22% over the past year. Fraud prevention and security professionals have been trying to educate consumers for a long time on this topic. Stealing identity data and using it in multiple fraud schemes can be significantly more harmful than criminals having access to someone's credit card numbers, where transactions can be traced quickly and revoked or charged back. While many factors contributed to an increase in concern about identity theft, the most impactful over the past two years were the numerous cases of unemployment and benefits fraud. Multiple countries reported cases where criminals applied for loans in the name of genuine consumers or through synthetic identities, created by combining real stolen information with fake data. The cost of these scams is yet to be discovered, and it could take years to see their full effect, with fraud losses well into the billions (if not trillions) of dollars worldwide. Criminals can access stolen data and fraud tutorials beyond the dark web To commit many types of fraud, criminals need Personal Identifiable Information (PII) that is stolen through techniques such as hacking attacks, credential harvesting, credential stuffing, phishing, or other types of social engineering. For years the knowledge of how to do that, along with the stolen data available after a successful attack, was available mainly on cybercriminal forums accessed through the dark web. However, over the past year, it has become easier than ever to obtain not only PII data but also valuable information on how to bypass some of the security and fraud features in place for a certain institution. Criminals no longer need to go to the dark web to do that - it's available on platforms like Telegram, just a few clicks away, where other fraudsters are selling tutorials (often called 'Sauce') on how to commit fraud, as well as PII data (called 'Fullz') to achieve it. As a result, the entry level for those that want to commit fraud has been set lower than ever before - both in terms of skillset and accessibility. Phishing and scams are at all-time high Another contributing factor to the increase in consumer concern is the number of scams resulting in authorised push payment fraud, which totalled £583.2 million in the UK alone during 2021. Criminals continue to seek out consumer vulnerabilities and use a variety of tactics to apply pressure on their victims and convince them to transfer money out of their bank accounts. This could take many forms - from various types of impersonation scams, romance scams, and investment (fraud) opportunities, to scams related to utility bills and easy loan offers among other types. This wouldn't be possible without numerous phishing/smishing/vishing attempts and the amount of data available through data breaches. One other factor that helps criminals is the direct access to potential victims given by social media and the sheer volume of personal information available in the public domain. These types of scams sometimes get high publicity (and rightly so) which can also contribute to the increased level of concern among the public while also applying additional pressure on financial institutions to improve their fraud screening and transaction monitoring capabilities to protect consumers. How businesses can improve fraud screening capabilities and increase consumer trust To restore consumer trust, businesses need to look for ways to improve their capabilities both at account opening and login to prevent criminals from gaining easy access to their services. There are multiple ways to do that, from introducing online identity document verification or phone-centric identity verification capabilities at the account opening stage, to adding behavioural biometrics, device intelligence, or fraud data sharing capabilities during different stages of the customer journey. By introducing some of these capabilities businesses also can improve the digital customer journey for genuine consumers and increase trust. Online identity document verification and phone-centric identity verification solutions both offer pre-fill capabilities. These tools can streamline registration processes and thus contribute greatly to a positive consumer outlook of the company that offers them. While behavioural biometrics, device intelligence, and fraud data sharing tools are invisible to both fraudsters and genuine consumers creating a more frictionless experience. Businesses should look carefully at the fraud they are experiencing along with fraud trends shared by similar businesses. This should help inform whether to introduce new capabilities as part of the existing strategy. It's common that companies might need a mix of capabilities to mitigate fraud issues, with additional support from machine learning models to blend them into one cohesive output while limiting the number of false positives and building consumer trust. Stay in the know with our latest research and insights:

Did you miss these July business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Digital experience is a key priority for the post-covid consumer TechWire Asia reports on data from Experian’s latest Global Insights Report to look at consumer expectations and the digital experience businesses can offer as consumers spend more time online. Experian CIO on digital identity, personalization and building trust with consumer data Kathleen Peters, NA Chief Innovation Officer, speaks with Finovate in this interview discussing the 2022 Global Identity & Fraud Report and thoughts on digital identity and how financial services companies can use consumer data to their advantage 91% of Indians prefer online payment methods Business Today India reports on findings from the Global Insights report, with digital payments having overtaken credit cards with 91 percent of Indians preferring online payment methods. Spain, the second country most concerned about online fraud CSO Computer World explores the findings from the 2022 Global Identity & Fraud Report from a Spanish consumer perspective, revealing that Spain is the second country most concerned about online fraud globally. Stay in the know with our latest research and insights: