Financial technology, or fintech, has rapidly disrupted and transformed the financial services industry. In 2022, 80% of consumers surveyed by Plaid Users used a digital financial product, a 22% increase from just two years ago. As users become more comfortable with integrating technology into many aspects of their lives, they are increasingly turning to fintech companies to purchase financial products, apply for loans, and manage investments—all without leaving their homes. Fintech platforms provide products backed by multifaceted distributed systems and integrate information from multiple credit bureaus like Transunion, Equifax, and Experian to create a robust picture of members’ credit. They use artificial intelligence (AI) and machine learning (ML) to power complex, intelligent recommendation systems that can provide members with high-certainty financial products. By leveraging multiple application programming interface (API) integrations with lenders, fintech platforms facilitate and automate every step of the lending process, from application to decision, employment verification, and funding.
How fintech platforms work
Fintech platforms aggregate offerings from different lenders and match users with those that best fit their needs. Lenders receive high-quality leads (interested customers who are likely to make a purchase) while customers are directed to financial products that are more likely to interest them and qualify for. Through fintech platforms, consumers can purchase financial products ranging from personalized credit cards to auto loans and mortgages. Many platforms, like Wealthfront, also offer automated financing and automated trading training, in which AI and ML are used to make decisions for users. This makes it possible to get advice at a much lower cost than a financial advisor. Many fintech platforms do not charge users directly; instead, they rely on interchange fees, in which a lender’s bank is charged a percentage of the transaction amount to generate revenue. Fintech companies can also earn money from processing and transfer fees or receive compensation from lenders in exchange for leads or member-approved product purchases.
Benefits of fintech for consumers
Fintech platforms, many of which operate via mobile apps, allow customers to browse financial products on the go for maximum convenience. They also help customers easily sort and compare offers from multiple lenders while providing personalized recommendations. Fintech can also reduce some of the risks associated with personal finance. For example, a declined loan application can negatively impact a consumer’s credit score. Fintech platforms provide users with access to loan approval odds or provide them with a high degree of certainty Users can access their credit scores from multiple agencies for free through fintech platforms. Credit-building services can advise members on how to strengthen their credit by suggesting steps like automating credit card or utility payments and keeping their credit utilization below 30%. Increasingly, fintech platforms offer their own checking, savings, and trading accounts, and many partner with lenders to offer exclusives like low interest rates, high credit limits, and early paydays.
How technologies support fintech
The future of fintech depends on the development and adoption of new technologies and global digitalization. AI and ML are enhancing the personalization of the fintech user experience. The tools leverage customers’ financial history to provide insights into the products they are likely to use and be approved for. Additionally, AI-powered robo-advisors help customers manage their investments through algorithms that automatically rebalance the user’s portfolio based on their preferences, goals, and risk tolerance. Additional use cases include streamlining business operations, fraud prevention, risk management, and customer service.
Distributed systems, which integrate multiple IT systems with different physical locations, are necessary to scale fintech platforms. Integrating data from multiple sources, including APIs from multiple credit bureaus, is equally essential. Fintech platforms submit customer data to lenders’ APIs to provide chances for approval of offers. credit Credit bureaus may update their information at different intervals. For example, one may be updated daily, another weekly, and another every two weeks, making it difficult to integrate up-to-date information from all sources. Additionally, fintech platforms typically aggregate offerings from many lenders. CreditKarma, for example, partners with 20 to 30 lenders for each type of financial product and manages integrations with ADP payroll and payment app Plaid.
Security complexity increases with the number of partner integrations. Data encryption is necessary to provide a secure experience for customers. A general best practice is to integrate multiple layers of encryption, such as using a Mutual Transport Layer Security (mTLS) handshake to verify a connection and JSON web encryption to encode the payload sent over the network to lenders or via a third-party API. Machine learning can also Detect identity theft and protect against fraud.
Cloud computing is often the foundation of major operations supporting fintech platforms, including online payments. Yet cloud partnerships come with security risksFintech platforms can ensure the security of their cloud environments by avoiding public clouds, conducting regular risk assessments, and using strong encryption technologies. Investing in data loss prevention (DLP) and distributed denial of service (DDoS) attack prevention systems can also help fintech companies protect themselves from attacks and ensure the security of user data.
Fintech and the future of banking
Written by Viswanadha Pratap Kondoju for TechBullion
Traditional banks are often limited by legacy systems when integrating new technologies. Fintechs have an advantage, as many are equipped with the infrastructure to immediately adopt new paradigms. Wealthfront, CreditKarma, and NerdWallet are just a few examples of fintechs using machine learning and AI to provide users with automated personal finance offerings. Increasingly, users of fintech platforms will turn to AI assistants for financial insights, personalized offers, or advice on how to improve their credit. As generative AI advances, more AI products will likely become commercially available, making it easier for fintechs and traditional banks to access AI tools.
Today, fintech companies operate by connecting with lenders. In the future, the entire end-to-end transaction, from browsing to application to approval, will beverification and financingcould be done through fintech platforms, with banks providing only back-end support. While integrating data from multiple sources poses challenges, this merger gives fintech companies their advantage. Since fintech companies typically lack the liquidity of large financial institutions, it will be difficult for them to fully replace banks. Instead, fintech companies and banks can leverage each other’s strengths. Banks can adopt new technologies and proactively partner with fintech companies. To adapt to the changing financial landscape, it is imperative that banks adapt to technological changes and adapt their systems based on user feedback. The future of financial services depends on the industry’s ability to effectively adopt and optimize new and emerging technologies. Through a collaborative effort, financial institutions, application developers, regulators, and other stakeholders can create the future of the financial world with democratized finance.
About the author:
Viswanadha Pratap Kondoju is a CTO with over 14 years of experience in software engineering and seven years of specialization in the fintech industry. He is currently leading a team working on core platforms and services that enable millions of users to access personalized financial products and advice. He also has experience in full-stack development, machine learning, artificial intelligence and cloud technologies. Viswanadha holds a Bachelor of Technology/Information Technology from the Indian Institute of Information Technology and a Master of Science in Computer Science and Data Science from the University of Texas at Dallas. For more information, contact kondojuviswanadha@gmail.com.
