• Successfully selected a network level risk engine for Zelle®, (through various POCs), to scan each Zelle® transactions and interdict the fraudulent ones, using AWS (Kinesis, KMS, S3, Splunk, IAM, Lambda), Vendor SaaS Risk Engine (on AWS), Kafka, Spring Boot APIs, Stream Sets, with an expected ROI of 10 million/year• Forged an architecture for a fraud-prevention-product that will identify bad actors in the entire Zelle® network (through a patented entity resolution process), and remove them proactively before they commit frauds and also stop any bad actor from entering the system, using Spring Boot API, Oracle, Kafka, Stream Sets, HDFS, Universal Controller, with an expected ROI of 2 million/year.• Curated the architectural layout of migrating Zelle® Applications from both on-premise and AWS cloud to a more matured AWS Cloud setup with better monitoring, scalability and security postures, using Spring Boot APIs, AWS Services (numerous), with an expected intangible (non-dollar) short-term returns and long-term cost savings through infrastructure cost transparency and predictability• As part of regulatory mandates, Rakesh led a POC to identify solutions to modernize the Process Integrity Control system used in Zelle®, using AppDynamics, Splunk, Kafka, SQL Server, with an expected intangible benefit in terms of improved resiliency, preserving brand reputation and regulatory compliance.• As an Enterprise Architect responsible for managing frauds within Zelle®, Rakesh has to keep architecture documentations updated, key decisions captured, managing target-state architecture, managing non-functional requirements (as part of Software Development Life Cycle) and managing tech-debts (to name a few), using LeanIX, Confluence, Jira, LucidChart.

• Successfully migrated the Business Rules Management System from On-Premise to AWS, using Elastic Kubernetes Service (EKS), RDS, Route 53, Certificate Manager, Application Load Balancer, EC2 instances, with 6 times better performance (15 in AWS vs. 97 milliseconds in On-Premise).• Led a team to design and create a Single-Page Application (Thin Server Architecture), using AngularJS and Node JS (API), Kubernetes, Dockers and GitOps, resulting in 50% improvement in operational efficiency.• Conceptualized, designed and built a UI web-application to mitigate an Enterprise Level Risk, using a mature Continuous Integration/Continuous Delivery (CI/CD) pipeline, Java Spring Boot framework, Splunk, Dynatrace, NIQS, Checkmarx, Snyk, JUnits and Selenium (for automated testing). Thereby, improving the overall resiliency of State Farm while saving millions of dollars in operational cost.• Provided a resilient and innovative solution for a complex problem to rectify discrepancies in Enterprise Master Datastores, utilizing Data Virtualization Manager, SQL, Mainframe technologies, Control-D, ServiceNow. Achieved the goal to match risk accurately to price by identifying 100s of claim-discrepancies every week, resulting in higher revenue and improved customer satisfaction.• Built and maintained a Business Rules Management System (BRMS), hosting thousands of complex underwriting rules, with a goal to surpass 45% overall automation, using IBM’s ODM, Splunk, ServiceNow, IBM’s Dependency Based Build pipeline, Jenkins, GitLab, UrbanCode, Mainframe, Pivotal Cloud Foundry (PCF). • Data Analytics:- Created a Blog using Content Marketing, Web-Analytics and SEO.- Conducted a thorough Data Mining and Predictive Modelling research study to find some key patterns in the profile of the students, using the XL Miner platform of Microsoft Excel.- Built a Predictive Model to forecast Airlines Delay using R, Python, Tableau and SAS Enterprise Miner.

• Led a team to implement regular legislative and voluntary changes in rules, regulations, and rates made by Actuary, utilizing Mainframe technologies.• As part of an enterprise-wide effort to integrate and modernize the policy-administration system, built a point-of-sale system for Auto Insurance policies using IBM’s CICS technology, resulting in significant operational cost reduction.