Quais são as estratégias eficazes para integrar sistemas legados com novas soluções Fintech?

Enable Discovery Workshop with the key stakeholders Create a list of the legacy systems (AS-IS) Create a list of the future state (TO-BE) Create a GAP Analysis Create a Risk management plan Create a FRD document Etc...

This step is pivotal in the process, as everything else relies on the quality of assessing goals and challenges. It is common for legacy platforms to have inferior capacity, concurrency, and integration capabilities compared to modern stacks. Fintech value chains experience heavy traffic due to their real-time and interactive nature. Thus, it is imperative to comprehend the business requirements, agreed SLAs, and, most importantly, the integration's impact on both legacy platforms and the current stack. Another frequently overlooked aspect is the short- to medium-term capacity requirements as the usage and popularity of the value chain increase.

Integrating legacy systems with new Fintech solutions has its trade-offs. Replacing the system offers the latest tech and enhanced features but is costly and requires a significant investment. Wrapping the legacy system is budget-friendly and quick, maintaining operations with minimal disruption, yet it may not fully utilize new tech capabilities. Bridging with APIs or middleware improves efficiency and data flow without a full overhaul but adds complexity and potential security risks. Each method balances benefits against drawbacks, from financial implications to operational impacts, making the choice dependent on specific needs, budget, and risk tolerance.

Overloading legacy platforms can be highly counterproductive, potentially impacting operations and ultimately affecting service levels and business continuity. It is crucial to assess the integration's impact on these legacy platforms and determine the operational costs from a technological standpoint. The ideal integration strategy is one that minimizes both impact and cost. Data governance is another critical aspect to consider. Depending on the requirements and security of receiving systems, one must analyze whether personally identifiable information (PII) data and other sensitive data need to be withheld or can be withheld without adversely affecting the use case while still meeting regulatory requirements.

For successful legacy systems and Fintech integration, stakeholders across business, IT, and Fintech must be involved for alignment and feedback. Ensure clear, frequent communication about the process, challenges, and outcomes. Document and test all integration aspects, including design, architecture, data, and functionality. Prioritize security and regulatory compliance throughout. Continuously monitor and audit the integration to prevent breaches or violations. These steps ensure a smooth integration, better collaboration, minimizing risks, and enhancing system performance and compliance.

There are various methods for achieving integration and interoperability between applications, whether through APIs, messaging, PubSub, custom solutions, and so forth. In all cases, it is crucial to document the Rules of Engagement and certification guidelines to ensure that the sequence and data being transacted are well understood. Other key aspects to consider are : 1. Integration should not adversely impact or overload legacy platforms. 2. Traffic needs to be throttled to prevent the formation of bottlenecks. 3. A clear DevOps strategy needs to be outlined to ensure the service level and availability of the platform.

Post-integration, evaluate and optimize performance by measuring key metrics aligned with your goals (defined in the TO-BE document). Address any gaps and solicit feedback from customers and employees for improvements. Stay updated with Fintech trends to refine your integration. This process enhances your financial institution's competitive edge, effectively discarding legacy systems with innovative Fintech solutions.

Monitoring is crucial for evaluating and optimizing any platform. Fintechs are agile enterprises; their goal is to capitalize on potential gaps in the market, which requires frequent updates. This agility adds complexity to both downstream and upstream integrations. Additionally, traffic could be erratic, leading to sudden peaks that overwhelm systems. Data-related issues may also arise, resulting in exceptions. Dashboarding KPIs, monitoring logs, and hardware usage using platforms like AppDynamics, Splunk, etc., are effective ways to gain situational awareness and ensure efficient management.

For successful legacy-Fintech integration, focus on user training, iterative improvement, and strong vendor partnerships. Ensure data integrity, manage change effectively, and design for scalability. Continuous performance monitoring is crucial. These steps enhance integration, ensuring a smooth transition and long-term value.

It is important to outline the end-to-end use case or value chain, as well as how the traffic is likely to be distributed throughout the day to ensure overall success of the integration. A prime example is a Fintech company requesting transactions of retail customers, which they manage in batches using open banking APIs during peak hours all at once, potentially creating unnecessary bottlenecks. This places strain on transactional systems, including downstream core banking platforms, affecting the performance of actual transactions for customers. Without caching enabled, there is also a risk of data re-computation or reprocessing, and so forth.