The client is a next generation asset intelligence company that works with banks, asset managers and other financial services. The client provides AI-powered customized insights into investment opportunities based on customer transactions, risk-taking ability, circumstances, inferred preferences, portfolio mix, equity performance data and market signals. The client’s vision is to place as much insight into the hands of investors as asset advisors. To do this, the client wanted to develop an AI platform that provides investors and advisors with access to customized institutional-grade research across multiple asset classes while adhering to compliance requirements.
Given the client’s goals, it was necessary to acquire a complete and flawless understanding of the customer’s needs and preferences. For this, Mindtree engaged with the client’s users to develop an AI-powered solution. Simultaneously, a quant model using investment algorithms was built into a third party cognitive platform to deliver market research and insights. An orchestration platform to manage containerized models and APIs to support auto scaling, rolling updates, rollbacks, etc., was put in place. A Single Thread Delivery Framework was used to accelerate speed-to-market and ensure seamless delivery. Ease-of-use and customer experience were improved via a mobile interface, social login and Alexa that were integrated into the solution.
Mindtree’s expertise in AI and its deep domain experience helped craft a cost-effective solution for personalized wealth advisories and reduced time-to-market. By coaxing personalized insight out of customer and financial data using AI, the client created a significant differentiator. The solution was also aligned with regulatory requirements while delivering maximized returns from trading strategies
The engagement comprised 15 on-site and offshore resources of which 50% were cross-skilled in .Net and Angular. The project was delivered with a total effort of ~2,000 person days
The tools and technology environment for the solution included:
- Proprietary cognitive platform
- MongoDB
- Kubernetes
- iOS
- CI/CD using Docker & Jenkins
- Alexa
The other benefits unlocked by the solution included:
- Time taken to analyze customer needs reduced from a week to a few hours, allowing faster time-to-market
- Reduce capex and internal research costs
- Reliable AI-powered decision making to help investors in portfolio allocation and rebalancing
For wealth managers, AI is going to be the primary technology for growth in the coming years. The reason for this is AI’s ability to present reliable data-driven insights while personalizing at scale. Given the numerous use cases for AI, the trend will be for banks to turn their attention to the technology and aggressively use it to improve performance.
