We have blended the emerging trends with our 2 decades of experience in working with global and regional banking leaders, to create excellent digital banking operations solutions. They are:
Digital banking is mostly about calibrated accurate and seamless flow of data between specialized systems. With our 20 years of banking we have created ready to use data pipelines between various systems which have embedded ways to validate the data against banking data models. The solutions we provide are specific to the banking process and cover the entire gamut from finding, evaluating, and defining the sources of data to final consumption point. We also ensure reliability of data pipelines through continuous monitoring and telemetry.
To deliver on the promise of great digital outcomes, banks must continuously innovate the processes through which they deliver services. We have created ready to use automated process blueprints for a few digital banking operations on top of industry standard platforms. They can integrate with any front end, core banking as well as CRM applications and deliver fully digitized banking outcomes.
We ensure that your customer experience investments are backed by ability for continuous delivery of software. We provide CI/CD pipeline for your choice of technologies contextual to the banking process for which you are creating the platforms.
Management and SRE
While DevOps may provide the agility for change, the reliable continued service delivery is dependent on the banks’ ability to monitor, review and make necessary corrections to the services rendered. To enable our banking partners on this front, we have created specialized solutions which can proactively manage service platforms on premise or on the cloud. These are fully integrated and with telemetry to detect and cure anomalies to drive extreme reliability of digital services.
To deliver innovative and personalized services to customers, banks have to use embed advanced algorithms in their business processes. Our MLOps closely work with the data scientists and ML engineers from problem identification to agile development of solutions and fully own the production deployment, continuous monitoring, and review of the decision models.