How Niyuj helped a niche startup company democratize financial planning services bringing their customers and vendors on a single platform

Executive Summary

The ability to access, analyze, and manage their finances is critical to most end consumers.

Our customer provides products and services that ensure reliable and secure gathering of demographic and financial data, along with overall financial objectives and uses that information to deliver a personalized financial strategy to their end users.

Niyuj worked with this customer, to help them create a new service offering that generated additional revenue, and address ongoing operational management inefficiencies to reduce operating costs.

This paper presents a specific use case. However the approach and guidance offered is the by product of dozens of projects and highlights the choices that Niyuj customers faced and the decisions that they made leveraging Niyuj’s experience and expertise across many industries.

Key Business Challenges

Our customer being well entrenched in the financial services vertical for several decades has access to data from a variety of sources. This data includes but is not limited to financial product information and typical market trends. They also have pre-existing agreements and partnerships with vendors of financial products sand services like mutual funds, equity trading houses, banks and other financial institutions.

However the sheer volume and variety of data made traditional approaches to capturing, reporting and analysis ineffective to scale.

As a result, some data feeds are either not utilized at all, or need to be manually processed from time to time to keep it manageable and consumable to the end customer. Moreover, as new instances and different products emerge, the data volume and variety increase exponentially making it an even larger problem.

Our customer has a clear strategy to create a single platform to cater to a diverse user group with diverse financial objectives, and provide them with the right product and strategy to meet those objectives.

A propriety rule engine to analyze and score different financial products for a diverse group of end users with different financial objectives, delivered using a state of the art cloud based platform.

Information gathering wizard

The product gathers information by way of a wizard, in four easy steps starting with understanding the financial objectives, the user profile, specific nuances and then ending with generating the formal paper work as per different compliance standards.

The Goal

Each of the above steps is detailed out without losing the intuitive nature of the process. It starts with understanding the financial objectives, which may range from savings and capital preservation to growth and capital expansion. It also caters to tax planning strategies. All of this data is captured in the form of different hacks to the end users current modus operandi.

The End User Profile

The next critical input in order to provide a personalized financial planning strategy was to capture user demographic and financial profile information in a non-intrusive and secure fashion. Once again Niyuj employed a wizard approach with simple widgets as shown above, to gather information about gender, age, earnings, and experience.

The Results

The above information was analyzed and scored by a propriety rule engine creating a personalized financial strategy, comprising of specific products and services for that customer. This was also made actionable by third party integrations with backend systems of these products vendors.

The Solution Architecture

Given the legacy constraints Niyuj came up with an architecture that addresses the most urgent need of being able to intuitively capture the volume of data, a personalized scoring algorithm that is accurate and independently scalable, and mechanism to deliver this in a plug and play model with a cloud based technology stack that can scale, while also being extensible in the future for more advanced predictive analytics, forecasting and other such features.

Increased revenue and reduced operating costs through a common technology platform for all stakeholders that’s independently scalable.

Database

The combination of relational and non-relational features drove the choice for using Postgres as our choice for the data store. This resulted in allowing us to scale write throughput while maintaining the same level of read performance and resilience to changes in data structure.

Mobile application

Since we were dealing with large volumes of data that need to be visualized and processed, and multiple different interactions possible we needed a mobile UI framework that can scale. This requirement drove our choice of a mobile app as well as a WebUI framework. This framework has features that allow data to be asynchronously changed without requiring the refresh of the whole page.

Scale Analytics

The combination of Jasper reports and Postgres made it possible to provide richer analytics on significantly larger volume of data. This made it possible to leverage existing reporting templates that were carefully designed with the end users.

3rd Patry integrations

With the availability of large volumes of data that can be retrieved efficiently, it was possible to integrate with other 3rd party financials institutions to make the recommended strategy actionable. This made it possible to monetize data through advanced analytics and new use cases.

Increased Revenue

The combination of the Big data infrastructure, advanced rule engines, and a start of the art web UI, allowed us to provide a personalized experience for all stakeholders allowing our customer to scale their business without the need to increase processing staff to keep up with the growth in business.

Client's Perspective