How We Helped SprintMoney to Design & Develop a One-of-a-kind FinTech App for the Indian Market

1. Feature Engineering

We started by conducting a detailed comparison between 5 apps that are similar to SprintMoney in terms of their core offerings. We mapped the features that they were excelling in while paying special attention to gaps and challenges that were left unaddressed by those apps.

An important realization that we arrived at was that when it comes to deciding on the final purchase of a financial product, the end-user usually goes through a step-by-step process. It hardly ever happens in one go. This means that from the point when the first user interaction takes place to the point when she/he finally makes the purchase, multiple touchpoints are involved where the user can lose interest or become demotivated to make the transaction. We have designed SprintMoney in such a way that at each of those touchpoints, we nudge the user gently to return to the application and resume their journey towards financial freedom – right from where they had left off.

To do this, apart from researching the right design elements to keep the user hooked, we also built features and incentives all across the users’ purchase cycle such that the chances of a user returning and eventually making a purchase on the platform are dramatically improved.

Besides, SprintMoney was divergent from other apps in one core area – that is, they were not reaching out to end-users directly but were going through various institutions instead. Hence, we built the app in such a way that the features benefit not only the end customers but are also useful and easy to use for the institutions that serve as distribution partners and channel members for SprintMoney.

This way, we seamlessly aligned SprintMoney’s features with the distribution strategy that the founders had adopted. This was a major element of the entire design and development process since investment companies, banks, insurers, and corporate organizations are the key to maximizing the market penetration for SprintMoney.

FinTech apps don’t function in a vacuum. They need to “talk” with the entire ecosystem encompassing the Finance and the Economics of a country. For example, in the case of SprintMoney, the tech discovery process revealed that a large number and variety of data points had to be integrated and assimilated within the app’s data processing module.

This data was massive, complex, and diverse, coming to SprintMoney at uneven rates from customers as well as third parties like AMCs (Asset Management Companies), Stock exchanges like BSE, rating agencies like Morningstar India, and BSE Star MF, RTAs (Registrar and Transfer Agents), and so on.

For example, when it comes to Mutual Funds (MF), data points like shareholding percentage, valuation (Net Asset Value (NAV)), and current prices are important considerations. Other data points reveal the statutory limitations on transactions, like the specific dates on which MF transactions can happen for a given bank or institution, the nature of MF (lumpsum vs SIP) allowed during a given period, restrictions that decide which schemes are allowed to be under SIP (Systematic Investment Plan), and performance ratings of various schemes and funds.

During the early stages of developing the app, integrating data from such diverse and disparate sources presented a challenge of its own. Some of this data, like pricing-related data, were also time-sensitive and had to be fed to the system in a matter of a few milliseconds. We achieved the same by incorporating a data lake instead of a Relational Database Management System (RDBMS) which was our initial approach. Using the data lake that we specifically architectured for SprintMoney, we seamlessly integrated large volumes of structured and unstructured data and retrieved the same within a few milliseconds to enable spotless financial decision-making and smooth transactions. Using the data lake also substantially reduced the application’s time-to-query and improved the overall efficiency and performance to a great extent.

FinTech apps are susceptible to fraud and data breaches all the time. This makes data validation an extremely critical component of the app development process. In particular, interacting with certain third-party entities like BSE Star MF required interfacing through APIs for aspects like identity verification, payment integration, and transaction processing.

Since it is cumbersome and time-taking for the end-users to keep migrating from one system to another, we decided to make the entire transaction process an integral part of the application itself. Hence, intermediate steps like verification of Personal Account Number (PAN), and verifying the validity of images uploaded by the end-user (like images of self, images of canceled cheques, etc.) all happen within the native application environment of SprintMoney. Further, extracting details like account number, branch name, and IFSC code from uploaded images or documents have all been automated in order to save transaction time and any possibilities of error.

We achieved these by using advanced capabilities like image processing and OCR, and also with the help of external services like Amazon Textract. Apart from auto-validation, back-end users of SprintMoney can also query the data internally to perform supervised validation (for example, they can check if the bank branch details entered by the user match the IFSC number extracted from the canceled cheque or not).

A number of steps like verifying account name, account number, and PAN number happen through auto-validation right at the time of profile creation on SprintMoney. This eliminates the need for independent verification on platforms like BSE Star MF (for example, separate validation is not required outside of SprintMoney for submissions under the Foreign Account Tax Compliance Act (FATCA), which is a rather complex and time-consuming process). At present, we are also working on adding added layers of security like Mobile Money Identification Number (MMID) verification which will further enhance SprintMoney’s data safety and system integrity.

India is a vast country with a highly dynamic and diversified demographic. The fit between a financial product (like an investment product or an insurance product) and the end customer will depend on various factors like the customer’s location, age bracket, employment type, income level, and financial goals. For example, the service class consisting of working professionals between 25 to 45 years of age have a much higher financial risk appetite as compared to those above the age of 45 years.

Further, the usage patterns and financial goals of end customers residing in tier 1 and tier 2 cities are vastly different from those of end customers who are residing in small towns and villages. Based on the geographical location of the customers, the financial products which are popular or more acceptable to the natives in a certain region also vary significantly from those in other regions.

Since 75-80% of end users don’t know this industry, curating a useful and comprehensive recommendation based on the factors listed above along with other factors like investment needs, family background, education, employment status, and income level is a critical accomplishment that we have attained for SprintMoney.

SprintMoney’s mission is to assist even absolute beginners in their financial journey. This hinges on having a sophisticated recommendation engine in place that we have built and integrated within the app. At present, SprintMoney provides access to this feature to all users without any subscription fee, but going forward, they see this as their key selling point and IP (Intellectual Property).

Digicorp undertook a deep tech-discovery process to understand the data architecture needs for SprintMoney. Thereafter, our team selected the technology stack accordingly. Right from the start, we focused on adopting a loosely coupled, modular architecture keeping in mind the extensibility needs that might arise in the future. Our microservices-based architecture has kept the application lightweight while all the functional domains – i.e. Investments, Insurance, and Loans – are kept modular.

This means that each functional domain can be independently deployed on any platform and be hosted on a separate infrastructure without the need to avail of other functional modules. For example, if a corporate only wants to have the insurance module for its employees, it need not avail of the investment and loan modules of SprintMoney.

The deployment has been done on the AWS cloud. By using cloud infrastructure and edge analytics of financial data, we have been able to ensure continuous integration and continuous delivery (CI-CD) in a seamless, hassle-free, and end-to-end manner. SprintMoney can also be deployed natively on institutional servers. Alternatively, a hybrid deployment model can also be adopted based on the users’ needs.

We have built multiple fail-safes so that all user interactions on the app follow the applicable data safety provisions. While many FinTech platforms save the transactional data to prevent transaction failures, we have directly paired SprintMoney with the relevant financial institutions so that transactions can happen on verified bank portals directly. As a result, no financial data needs to be saved on SprintMoney, and nor is it required to leverage escrows to enable the transaction from start to finish.

At present, we are in the process of adding many more features to SprintMoney. Together with the client team, we are on the path to making it a leading FinTech app in the country. Digicorp is your trusted partner to build apps that wins consumers, dominate the market, and grow effortlessly. Our world-class capabilities in design, technology, and product engineering make us your ideal choice for building a new product from scratch or upgrading an existing one. Know more about our projects and capabilities here, write to us at sales@digi-corp.com to boost your journey of product innovation!