The Modern Serverless Banking Paradigm Explained in Details

There are numerous background tasks that banks must do on time and others depend on events and the data that is available at that time. For instance, the creation of bank account statements is a scheduled task that operates in the background while the processing of trade data is an event-driven operation.


In the conventional architecture, banks perform these standard processes in specialized on-premise data centers. However, because it can only execute the activities at predetermined times, this infrastructure is underutilized. Moreover, things like dedicated infrastructure, maintenance, configuration, capacity planning, resource scaling, and management must all be done manually.


With the introduction of the serverless banking paradigm, banks now have the option to select on-demand, highly scalable, and cost-effective serverless services provided via the cloud. Developers can execute apps in the cloud using serverless computing without worrying about management and infrastructure provisioning. Instead, a cloud service provider handles the management of infrastructure resources, scalability, patching, and capacity planning. A number of applications under this serverless banking paradigm provide on-demand provisioning of computing resources and charge depending on resource consumption during uptime. Function-as-a-Service is just one component of a serverless architecture. Other constituents include data processing, visualization services, and serverless containers. For instance, serverless assets can be set up to carry out a sporadic scheduled task. All serverless services will be deprovisioned following execution. This lowers the cost of infrastructure and speeds up infrastructure setup.


Let’s examine how the serverless paradigm might help banking institutions control operational costs and abide by legal requirements.


Applications of the Serverless Banking Paradigm


●Using an OTP generating module to handle a spike in high traffic.
●Analyzing reference data in trades to reduce potential fraud and human error.
●Data auto-archival to satisfy legal requirements
●Notice and bill presentation on schedule.
●Ability to automatically pay scheduled bills.
●The creation of monthly reports for users.
●Adjusting proposals based on the information at hand.

The serverless banking paradigm and their potential unlocked can support other game-changing infrastructure innovations, such as the following:


Microservices framework: Serverless operations are a wonderful deployment approach for microservices because of the quick production, lower costs and greater flexibility they offer. Microservices architecture is typically used in the development of contemporary banking apps. In this case, an application is broken into various components that can be individually deployed on a serverless compute platform and expanded depending on usage. The design of serverless microservices comprises handling transactions, web requests, and queue messages. For instance, a message received for processing in a queue may trigger the execution of a validation service.


Serverless services in the cloud can be used to build the backend or middle-tier functions of such an app. Each serverless compute resource used by the application programming interface’s (API) modules is unique, and each one is only produced and activated when necessary. The cloud offers services that let you combine various modules into a workflow or API.


Dynamic application workload: When the workload is not known, serverless services can be utilized to host a new service or application. The program can be dynamically scaled up or down depending on the amount of work being done. Infrastructure will be downsized in cases of inactivity to reduce costs. As an illustration, let’s take the case of a bank that releases a new payment application with no idea of its early popularity. In these situations, a small portion of the application’s modules can be created and hosted on a serverless compute platform, which is resilient enough to scale up and down in response to the application’s consumption. This leads to the efficient and timesaving handling of fluctuating workloads.


Information and analytics: Managed services or platform-as-a-service (PaaS) are two ways to access cloud-based serverless solutions. In addition to reporting, databases, and query processing solutions, it also provides serverless extract, transform, and load (ETL) capabilities. These services can be used to implement many financial use cases, like data collection and ingestion in a data lake.


PaaS models may be used to convert data into multiple forms for use in various business sectors. These serverless services may also be utilized for resource-intensive auditing tasks such as analyzing events and logs, as well as AI or ML-based reporting that analyses unstructured trade data provided via feeds. With the help of event-driven data processing, predictive analytics, and machine learning, the next gen serverless banking paradigm can also find abnormalities and errors in payment or application information to help prepare for potential risks in advance.

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