New IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor assessment provides valuable resource as organizations face increased fraud. With fraud scam losses reported to have reached $10bn in 2023*, preventing fraud in today's digital landscape has become increasingly complex. As organizations continue to leverage advanced technologies, fraudsters have also evolved, employing ever more sophisticated techniques. Striking the balance between robust fraud prevention and delivering a seamless digital experience to customers has become a priority for organizations, with customer experience (CX) proving to be a competitive differentiator in a market with high digital expectations. Why real-time detection matters for CX As techniques employed by fraudsters get faster, so does the need for quick and effective fraud detection, making real-time solutions increasingly important during a period of rapid technological advancement. The development of real-time fraud solutions not only minimizes financial losses, but it has also paved the way for frictionless customer journeys, with identity and fraud checks no longer impeding customer experience. Using machine learning to leverage data and enable fraud detection To enable real-time detection, proactive fraud prevention also requires the analysis of vast amounts of data. Deploying static rules to identify anomalies in data does not allow for nuance because the thresholds within the rules are fixed, and therefore real-time patterns cannot be adjusted to within the model. Machine learning not only allows businesses to leverage data more effectively through analysis, allowing for flexibility within the parameters, but it also removes some manual processes, improving efficiency by updating models faster into production. Approving good customers is the number one priority for businesses, and a frictionless digital customer journey is the catalyst for this. To minimize financial losses while reducing the overall number of fraud incidents, organizations are looking to real-time fraud detection, enabled by machine learning. "As fraud risk losses continue to increase, the pursuit of fraud risk management solutions designed to identify, mitigate, and prevent fraud incidents and losses is a topic with increasing focus within financial services.” Sean O'Malley, research director, IDC Financial Insights: Worldwide Compliance, Fraud and Risk Analytics Strategies IDC, the premier global market intelligence firm, released its latest IDC MarketScape: Worldwide Enterprise Fraud Solutions, providing a valuable resource to buyers looking for new solutions in the market. Download excerpt of IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor Assessment The report highlights: Fraud solutions are increasingly moving toward real-time fraud detection and prevention. There are significant enhancements in technological capabilities, particularly with respect to cloud computing. Some newer fraud solutions take advantage of the increased computing power that is available to both expand the data sets being used to identify potential fraud incidents and enhance the models designed to detect, mitigate, and prevent fraud. Experian is recognized as a leader in this report. The IDC MarketScape notes, “In addition to evaluating the transactional data for potential fraud, Experian's CrossCore solution includes identity-authentication tools. The solution uses identity data, device intelligence, email and phone intelligence, alternative identity data, biometrics, behavioral biometrics, one-time passwords, and document verification to confirm identities and aid with identity protection, including synthetic identity protection. Experian utilizes multiple data partnerships in its fraud solution, which often can help provide a more comprehensive understanding of fraud risks and exposures.” To achieve a frictionless and secure customer experience, it is the integration of digital identity and fraud risk that is creating a gold standard for businesses. A siloed approach to fraud prevention not only leaves gaps for criminals to exploit, but it also presents consequences for customer experience too. The ability to layer multiple fraud capabilities together in a synchronized effort to achieve the best analytics-driven output possible can allow businesses to have the flexibility within their user journeys to optimize and control the order in which capabilities are called, removing friction, and ensuring good customers are successfully onboarded. Add in a final layer of machine learning to ensure the deployment of unified decisioning, and businesses are left with cohesive and explainable decisions. At Experian, we are working diligently to stay on the cutting edge of fraud and identity. In addition to our proprietary credit data on over 1.5 billion consumers and over 200 million businesses, Experian leverages a unique curated partner ecosystem to provide a more comprehensive understanding of fraud risks and exposures. Our powerful technology platform enables users to leverage a wide range of tools to combat their customized fraud challenges. Download Report Excerpt More on Crosscore® *IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor Assessment
Lenders prioritise automation above all, according to 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. Research from Forrester on behalf of Experian found that automation is the top priority for businesses, and regardless of the specific industry or region, decision-makers consistently identified it as an important area of focus, and the biggest challenge. Lenders are using automation across the credit lifecycle and intend to invest further in the next 12 months, but there are multiple barriers to enhancing automation. We look at the use cases for automation and address the key challenges lenders face when automating decisions. The automation agenda The interpretation and application of automation vary hugely across the maturity spectrum of businesses in our research. While some companies consider automation as a means of simplifying tasks, such as the transition from manual processes to electronic spreadsheets, others are embracing its more advanced forms, such as AI-powered models. Use cases for automation in lending Customer service chatbots using Natural Language Processing (NPL) combined with Robotic Process Automation system (RPA). Remote verification of customers using machine vision and RPA to cross-check data. Data governance - data cleansing of personal information from within data using RPA and NPL. Operational efficiencies using process mining and AI to identify automation opportunities. Credit and fraud risk decisioning, using machine learning. Automation is about making processes as slick and robust as possible, giving the consumer a rapid journey so they can get processed very quickly, while behind the scenes lenders are making the best possible, compliant decisions, that protect them from losses around both credit risk and fraud.Neil Stephenson, Vice President of Experian SOFTWARE SOLUTIONS CONSULTANCY The changing face of automated decision-making in line with rapid tech advancements makes the use of automation by lenders a more complex opportunity than most. On one side there is the chance to enhance models with AI-powered tools to take away manual and subjective decision-making from processes. On the other, there’s the issue of governance and compliance – how to explain models that remove humans altogether. Introducing automation into some parts of the credit lifecycle isn’t always straightforward. Customer management has benefited from a lot of investment in the automation space over the years, particularly Natural Language Processing (NLP), but according to our research, the priority for business investment for Robotic Process Automation (RPA) in the next 12 months is originations. With onboarding playing such a key role in both customer experience and portfolio growth, businesses are looking to enhance this part of the credit lifecycle with automation. Customer experience is driving growth Automation plays a pivotal role in improving the customer journey and experience. The research showed that enhancing customer experience ranked even higher than growth as a priority for many organisations. As businesses strive to deliver seamless and personalised interactions, automation provides the necessary foundation for digital success, which in turn can strengthen competitiveness while retaining valuable customers. "Strategically investing in automation offers businesses the opportunity to scale operations, with a primary focus on growth. In times of economic uncertainty, more targeted, customer-centric strategies, that encompass more accurate predictive models, built on up-to-date samples and executed rapidly, can help mitigate a higher-risk lending backdrop." says Neil Stephenson, Vice President of Experian Software Solutions Consultancy. "Customer experience is the battleground for businesses, where they compete to deliver the best digital journeys in the market. It's a battleground that isn’t just about increasing revenue – the market perception of an organisation can be as important as growth in some portfolios because businesses have a reputation to protect." Automating decisions can ensure customer experience is truly seamless, but businesses face multiple barriers when it comes to credit and risk decision automation. Reducing referred applications From scoring regression models to the development of machine learning models, better and smarter analytics are critical to drive the processes responsible for making application decisions. Reducing referred applications in turn decreases the need for manual intervention. By minimising the volume of applications in the middle of the credit score, lenders have a clearer and ultimately more automated approach to application accepts and declines. We interviewed decision-makers to understand the numerous challenges faced by lenders when automating decisions: Increasing data sources to allow for a more complete picture of the consumer Improved data quality, and increased volume of data Prevention of model bias The complexity of consumer type attached to some products Redundancy in data input and analytics Training across key roles for a better understanding of automation capabilities Explaining decisions based on machine learning models to regulators Complex fraud referral processes For many respondents, automation is about accuracy and efficiency. By improving automation, there are fewer instances of errors and delays. To ensure scalability can exist in consistent, compliant, and accurate processes that work for both the business and the consumer, here are 10 tips to help tackle the challenges faced by lenders when it comes to automating decisions: Embrace advanced data aggregation tools and technologies that can efficiently collect and integrate data from various sources. Partner with known, trustworthy data providers to enrich datasets. Explore the use of no-code data management tools that allow users to add and remove data sources more quickly and easily. Implement data quality processes. Regularly audit and clean data to remove inconsistencies. Move to cloud-based solutions for scalable data storage and processing of very large datasets. Regularly audit (monitor) machine learning models for bias. Eliminating sampling bias is not yet possible but using a range of datasets (samples) and various sampling techniques will ensure representation across different demographics to help minimise bias. Develop specific models for different consumer segments or product categories. Regularly update models based on evolving consumer trends and behaviours. Conduct a thorough analysis of data inputs and streamline redundant variables. Use feature selection techniques such as correlations, weight of evidence, and information value to identify the most relevant information. Foster a culture of continuous learning and collaboration for all key stakeholders involved in the credit decisioning and strategy process. Develop transparent models with explainable features. Use interpretable machine learning algorithms that allow for clear explanations of decision factors at the customer level. Streamline identity verification processes by using smart orchestration to reduce false positives and prevent fraud. More on automated decision-making from PowerCurve – North America More on automated decision-making from PowerCurve – UK Related content: Digital decisioning
Authorised Push Payment fraud is growing, and as regulators begin to take action around the world to try to tackle it, we look at what financial institutions need to focus on now. APP fraud and social engineering scams In recent years, there has been a significant surge in reported instances of Authorized Push Payment Fraud (APP). These crimes, also known as financial scams, wire fraud scams, or social engineering scams in different parts of the world, refer to a type of fraud where criminals trick victims into authorising a payment to an account controlled by the fraud perpetrator for what the victim believes to be genuine goods or services in return for their money. Because the transactions made by the victim are usually done using a real-time payment scheme, they are often irrevocable. Once the fraudster receives the funds, they are quickly transferred through a series of mule accounts and withdrawn, often abroad. Because APP fraud often involves social engineering, it employs some of the oldest tricks in the criminal's book. These scams include tactics such as applying pressure on victims to make quick decisions, or enticing them with too-good-to-be-true schemes and tempting opportunities to make a fortune. Unfortunately, these tricks are also some of the most successful ones, and criminals have used them to their advantage more than ever in recent times. On top of that, with the widespread adoption of real-time payments, victims have the ability to transfer funds quickly and easily, making it much easier for criminals to take advantage of the process. APP Fraud and social engineering scams - cases and losses across the globe: View map Impact of AI on APP fraud Recent advancements in generative artificial intelligence (Gen AI) have accelerated the process used by fraudsters in APP fraud. Criminals use apps like Chat GPT and Bard to create more persuasive messages, or bot functionality offered by Large Language Models (LLMs) to engage their victims into romance scams and the more sophisticated pig butchering scams. Other examples include the use of face swapping apps or audio and video deepfakes that help fraudsters impersonate someone known to their victims, or create a fictitious personality that they believe to be a real person. Additionally, deepfake videos of celebrities have also been commonly used to trick victims into making an authorised transaction and lose substantial amounts of money. Unfortunately, while some of these hoaxes were really difficult to pull off a few years ago, the widespread availability of easy-to-use Gen AI technology tools has resulted in an increased number of attacks. A lot of these scams can be traced back to social media, where the initial communication between the victim and criminal takes place. According to UK Finance, 78% of APP fraud started online during the second half of 2022, and this figure was similar for the first half of 2023 at 77%. Fraudsters also use social media to research their victims which makes these attacks highly personalised due to the availability of data about potential targets. Accessible information often includes facts related to family members, things of personal significance like hobbies or spending habits, information about favourite holiday destinations, political views, or random facts like favourite foods and drink. On top of that, criminals use social media to gather photos and videos of potential targets or their family members that can later be leveraged to generate convincing deepfake content that includes audio, video, or images. These things combined contribute to a new, highly personalised approach to scams than has never been seen before. What regulators are saying around the globe APP fraud mitigation is a complex task that requires collaboration by multiple entities. The UK is by far the most advanced jurisdiction in terms of measures taken to tackle these types of fraud to help protect consumers. Some of the most important legislative changes that the UK’s Payment Systems Regulator (PSR) has proposed or introduced so far include: Mandatory reimbursement of APP scams victims: A world first mandatory reimbursement model will be introduced in 2024 to replace the previous voluntary reimbursement code which has been operational since 2019. 50/50 liability split: All payment firms will be incentivised to take action, with both sending and receiving firms splitting the costs of reimbursement 50:50. Publication of APP scams performance data: The inaugural report was released in October, showing for the first time how well banks and other payment firms performed in tackling APP scams and how they treated those who fell victim. Enhanced information sharing: Improved intelligence-sharing between PSPs so they can improve scam prevention in real time is expected to be implemented in early 2024. Because many of the scams start on social media or in fake advertisements, banks in the UK have made calls for the large tech firms (for example, Google, Facebook) and telcos to be included in the scam reimbursement process. As a first step to offer more protection for customers, in December 2022, the UK Parliament introduced a new Online Safety Bill that intends to make social media companies more responsible for their users’ safety by removing illegal content from their platforms. In November 2023, a world-first agreement to tackle online fraud was reached between the UK government and some of the leading tech companies - Amazon, eBay, Facebook, Google, Instagram, LinkedIn, Match Group, Microsoft, Snapchat, TikTok, X (Twitter) and YouTube. The intended outcome is for people across the UK to be protected from online scams, fake adverts and romance fraud thanks to an increased security measures that include better verification procedures and removal of any fraudulent content from these platforms. Outside of the UK, approaches to protect customers from APP fraud and social engineering scams are present in a few other jurisdictions. In the Netherlands, banks reimburse victims of bank impersonation scams when these are reported to the police and the victim has not been ‘grossly negligent.’ In the US, some banks provide voluntary reimbursement in cases of bank impersonation scams. As of June 2023, payment app Zelle, owned by seven US banks, has started refunding victims of impersonation scams, thus addressing earlier calls for action related to reported scams on the platform. In the EU, with the newly proposed Payment Services Directive (PSD3), issuers will also be liable when a fraudster impersonates a bank’s employee to make the user authenticate the payment (subject to filling in a police report and the payer not acting with gross negligence). In October 2023, the Monetary Authority of Singapore (MAS) proposed a new Shared Responsibility Framework that assigns financial institutions and telcos relevant duties to mitigate phishing scams and calls for payouts to be made to affected scam victims where these duties are breached. While this new proposal only includes unauthorised payments, it is unique because it is the first such official proposal that includes telcos in the reimbursement process. Earlier this year, the National Anti-Scam Centre in Australia, announced the start of an investment scam fusion cell to combat investment scams. The fusion cell includes representatives from banks, telcos, and digital platforms in a coordinated effort to identify methods for disrupting investment scams to minimise scam losses. To add to that, in November 2023, Australian banks announced the introduction of confirmation-of-payee system that is expected to help reduce scams by ensuring customers can confirm they are transferring money to the person they intend to, similarly to what has been done in the UK a few years ago. Finally, over the past few months, more jurisdictions such as Australia, Brazil, the EU and Hong Kong, have announced either proposals or the roll out of fraud data sharing schemes between banks and financial institutions. While not all of these schemes are directly tied to social engineering scams, they could be seen as a first step to tackle scams together with other types of fraud. While many jurisdictions beyond the UK are still in the early stages of the legislative process to protect consumers from scams, there is an expectation that regulatory changes that prove to be successful in the UK could be adopted elsewhere. This should help introduce better tracking of the problem, to stimulate collaboration between financial insitutions, and add visibility of financial instituitions efforts to prevent these types of fraud. As more countries introduce new regulations and more financial institutions start monitoring their systems for scams occurrences, the industry should be able to achieve greater success in protecting consumers and mitigating APP fraud and social engineering scams. How financial institutions can prevent APP fraud Changing regulations have initiated the first liability shifts towards financial institutions when it comes to APP fraud, making fraud prevention measures a greater area of concern for many leaders in the industry. Now the responsibility is spreading across both the sending and receiving payment provider, they also need to improve monitoring for incoming payments. What’s more, as these types of fraud are a global phenomenon, financial institutions from multiple jurisdictions might consider taking greater fraud prevention steps early on (before regulators impose any mandatory rules) to keep their customers safe and their reputation high. Here are five ways businesses can keep customers safe, while retaining brand reputation: Advanced analytics – advanced data analytics capabilities to create a 360° of individuals and their behaviour across all connected current accounts. This supports more sophisticated and effective fraud risk analysis that goes beyond a single transaction. Combining it with a view of fraudulent behaviours beyond the payment institution's premises by adding the ability to ingest data from multiple sources and develop models at scale allows businesses to monitor new fraud patterns and evolving threats. Behavioural biometrics – used to provide insights on indicators such as active mobile phone calls, session length, segmented typing, hesitation, and displacement to detect if the sender is receiving instructions over the phone or if they show unusual behaviour during the time of the transaction. Transaction monitoring and anomaly detection – required to monitor sudden spikes in transaction activity that are unusual for the sender of the funds as well as mule account activity on the receiving bank’s end. Fraud data sharing capabilities – sharing of fraud data across multiple organisations can help identify and stop risky transactions early, in addition to mitigation of mule activity and fraudulent new accounts opening. Monitoring of newly opened accounts – used to detect fake accounts or newly opened mule accounts. By leveraging a combination of these capabilities, financial institutions will be better prepared to cope with new regulations and support their customers in APP fraud. Identity & Fraud Report 2023 US Identity & Fraud Report 2023 UK Defeating Fraud Report 2023 EMEA & APAC
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, PowerCurve 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 PowerCurve 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
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 favorably 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. Download 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.
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: