When fraud changes and adapts, the old way of doing things to secure evolving payment methods is not enough. It’s time to improve your customer service, reputation and operations by acting with superior insight and agility aided by machine learning. Outthink the bad guys.
The nature of fraud is changing due to evolving volumes, methods and criminal sophistication
The volume and nature of financial fraud continues to change radically due to the increase of electronic banking, mobile payments and instant settlements. New exploitation channels have opened for ever more organized and technologically sophisticated cyber criminals. These have made it nearly impossible for banks and financial institutions to ignore security threats. As the payments industry evolves faster with mobile payment alternatives and innovations, fraudsters are adapting their techniques to the changing field and sharing those techniques with their own ecosystems.
Organizations are falling behind with their current ability to outthink fraud
Even though financial frauds are an everyday concern, according to IBM’s 2015 Fraud in Financial Institutions Study only 56 percent of executives believe their organization is in reasonable control of fraud threats and a significant number believe their fraud operations organizations are in need of a substantial overhaul. The same study shows that only 16 percent of banks already have the capability to use the technologies needed to detect fraud before near-instantaneous transactions have actually moved money.
Early fraud detection & management delivers brand, operational and reputational benefits.
Detecting fraud at an early stage offers significant operating savings, making it an important boardroom issue. With customers becoming more conscious about fraud issues, brand reputation and customer retention are affected as well, driving up costs. Even where direct personal fraud is not involved, the reputational damage and cost through compliance related fines for the non-detection of money laundering affects the business. In 2013 Harris Interactive estimated that 71% of customers will switch banks due to a fraud or a cyber-attack and, according to Edelman (2012), 46% will leave or even avoid companies with a security breach, which means that fraud is more than a boardroom issue, it concerns chief marketing officers (CMOs) as well. Organizations must continuously evaluate the best ways to safeguard their systems, their data and ultimately, their clients. By being able to successfully tackle fraud issues, prevent wasted effort and save customers’ time from unnecessary false positives, companies can gain a competitive advantage and create a better customer experience.
Making payments safer through machine learning.
The good news is that much can be done to improve counter fraud and financial crimes performance with the help of machine learning, high-speed processing, big data and analytics. In December 2015 IBM acquired IRIS Analytics, an expert in safer payment solutions, which are aimed at decreasing the number of false positives, and thus increasing customer retention. IRIS offers a near real-time and dynamic fraud detection solution for mobile payments, which utilizes machine learning to help identify new fraud patterns, rapidly generate anti-fraud models and support the creation and modification of ad-hoc models. Learning the patterns behind frauds takes a lot of human effort. Sometimes it is even impossible, as frauds don’t always follow the same pattern or evolve. Combining artificial intelligence and cognitive techniques with human experts, on the contrary, helps analysts act quickly to detect and deter fraud.
Act with superior insight and agility.
The fight against fraudsters requires better, continuous communication across different payment channels outside of those being used. The Safer Payments method expands a bank’s observation space this way, across managerial silos. It also enables sharing fraud patterns across multiple banks in a multiple tenancy situation. This means that banks don’t have to exchange sensitive customer data with each other, and customers can be assured that their data is stored securely. What also matters in fraud prevention is speed and agility – detecting the fraud in near real-time and adapting quickly to different situations so that preventive actions will happen before the money moves. With IBM Safer Payments, the potential frauds can be detected with an average response time of less than five milliseconds per transaction, even during peak periods, and without adding any notable overhead to normal service. Also the capability of responding to newly identified fraud patterns, by deploying new countermeasures in hours, not weeks, without taking down the system, is a huge advantage. IBM Safer Payments enables customer friendly service, managing the balance between risk and service by differentiating between low and high value transactions and acting accordingly.
The cognitive approach delivers real benefits.
The cognitive approach, to create a new paradigm in fighting fraud, appears to provide dramatically lower false positives, radically faster scale and speed, and more control and transparency, which improves the customer experience and prevents negative feedback and press publicity. IBM’s target is to industrialize fraud handling and offer an integrated security solution for companies by which they can create more business value and ultimately improve their customers’ experience.
Find out more. Listen to the podcast – Is it Your Analytics or Your Clients Who Alert You to a Fraud Problem?