Migrating to a new fraud solution doesn’t need to be a difficult process, but it can turn into one without proper planning. With all the moving parts, intricate technologies, and often diverse groups of stakeholders involved, it’s all too easy for things to go awry. When certain crucial elements slip through the cracks, it leads to unexpected setbacks, prolonged processes, and increased costs. Here are some of the common pitfalls that organizations face during the migration to a new fraud solution and how to steer clear of these traps. 1. Poor Internal Communication The first thing that goes into migrating a fraud solution is identifying the key stakeholders. The next step, equally as important, is getting them all on a good cadence of communication. When the right people aren’t involved from the start, it becomes one of the most significant obstacles to a successful migration. Internal communication is key to avoiding this pitfall. Set up the right internal channels and involve engineers, data scientists, and other key stakeholders from the start to keep everyone aligned and informed throughout the process. 2. Not Including Fraud Teams Throughout Migration Speaking of key stakeholders, fraud strategy, fraud ops, and all fraud teams are crucial to a smooth migration. Their insights and expertise are invaluable, plus they will be the ones most closely using the new fraud solution on a daily basis. At each step, your fraud teams should be giving input and sharing their requirements, processes, and experience. This will ensure your new solution functions the way its main users need it to. 3. Engineering and Integration Challenges Your engineers’ role in setting up schemas and integrating them into the new system cannot be overstated. In addition to technical expertise, they need to facilitate internal communication with the fraud team. This collaboration is essential for a seamless migration. If data schemas aren’t in the right format or not using relevant information, they become less reliable and affect your detection overall. Engineers need to be hands-on when setting these schemas up and backfilling the data once they are created. 4. Not Deciding on Real-Time vs. Batch Processing Setting up your fraud solution correctly depends in large part on how you process transactions. If you offer any real-time capability at all, you need real-time processing. If you don’t implement real-time monitoring at the outset during migration, it will be expensive and time-consuming to add later. With the world of finance going strongly in the direction of real-time, it’s advisable to set up real-time processing and detection if you have any plans to offer it as an option. The detection process differs significantly for batch compared to real-time, and if you choose batch processing you may not be protected against emerging real-time threats. 5. Time-Consuming Schema Development Schemas are a critical aspect of setting up a machine learning fraud solution. The data you use in them builds out essential information to detect fraud patterns. But creating these data schemas and adding all relevant information can be a time-intensive process. It’s essential to allocate sufficient time and resources for this stage to avoid delays. Again, if you fail to properly create the schemas during integration, you’ll be spending more resources and capital to fix them later. You’ll also pay the price in lost detection while you fix them. Make sure you backfill data once the initial schema setup is complete to ensure that historical data is accurately integrated into the new system. 6. Non-Alignment of Decision-Makers and Implementers Sometimes, the individuals who sign the migration documents are not the same people responsible for executing the migration. Similar to poor internal communication, if these two parties aren’t in lock-step, their disconnect can lead to confusion and delays. When communication between decision-makers and implementers is lacking, the provider, the implementers, and the teams who will be relying on the new solution will all be mixed up. It can be easy to have decision makers drift out of the integration process, as these are most often C-level executives with many other priorities and responsibilities to handle. But implementers and the new provider need an open line of communication with decision-makers from the outset of integration if things are going to go without a hitch. 7. Bridging the Gap Between the Provider and Implementers After a new solution contract is signed, there’s often a need for effective communication between the fraud solution provider and the individuals responsible for the migration. Failing to bridge this gap can result in wasted time and misalignment. Just like a breakdown in communication between relevant teams or decision-makers and implementers can derail in integration, poor communication with your new provider is a sure way to set the migration up for failure and accrue more expenses and correction costs down the road. How to Migrate Your Fraud Solution Without a Hitch Migrating to a new fraud solution is a mission-critical undertaking for organizations looking to stay ahead of emerging fraud threats. By addressing these common mistakes and following the recommendations outlined above, you can navigate this complex process with confidence and ensure a smooth, cost-effective, and successful transition to a more robust fraud prevention system. Stay proactive, communicate effectively, and invest the necessary time and resources into data preparation and alignment to make your migration journey a seamless one. Moreover, you should evaluate your fraud scenarios and choose a solution that addresses all of them. Which fronts present the most sophisticated or evolving fraud challenges? Determine the areas where you can improve your process through a new platform, and you’ll be set up to start your integration with the right information and process for all teams, decision-makers, and providers involved. If your institution is ready to make a switch to a real-time-ready fraud platform with award-winning features and best-in-class detection and integration speed, then you’ll want to talk with our team at DataVisor. View posts by tags: Related Content: Digital Fraud Trends How to Stop Check and Deposit Fraud with AI Product Blogs Introducing AI Co-pilot: Your New Generative AI-Powered Fraud-Fighting Companion Quick Takes How to Bounce Back from a Major Fraud Attack about DataVisor DataVisor is the world's leading AI-Powered Fraud and Risk Platform. about DataVisor DataVisor is the world's leading AI-Powered Fraud and Risk Platform. View posts by tags: Related Content: Digital Fraud Trends How to Stop Check and Deposit Fraud with AI Product Blogs Introducing AI Co-pilot: Your New Generative AI-Powered Fraud-Fighting Companion Quick Takes How to Bounce Back from a Major Fraud Attack