Technology has enabled companies and businesses to have multiple points of contact with target customers, create transparency around operations, streamline overall processes, and reduce manual, repetitive efforts.
One of the most significant and revolutionary technological developments in the last few years has been AI or Artificial Intelligence. AI is focused on the development of programs and systems which are intelligent and capable of replacing humans in various tasks. AI-powered systems are programmed in such a way that they are able to make changes to their functions and correct errors, without the help of human intervention. They are capable of recording and understanding basic patterns, and this has made machine learning an essential aspect of AI.
The importance of Financial Technology
Innovations in Fintech, have enhanced or improved the quality of financial services. There is still a constant need to make other financial processes such as banking, loan management and applications, insurance, investments and others more evolved, and that is where fintech helps. Finance technology makes it easier for companies, financial institutions, and business owners to effectively manage their financial processes and other operations.
Artificial Intelligence and Finance Tech
Both AI and Fintech have individually created a significant impact on the global economy, and so, it is only understandable that together, they would bring about nothing short of a massive transformation. When it comes to AI and Fintech working together, AI has become the means to digitalize the finance industry more than fintech has. AI can help eliminate many human errors. So for instance, when it comes to banking procedures, AI can make it easier for banks to actually understand customer needs and demands, eliminate the need for any kind of physical payment means such as cards, and can improve the overall quality of all banking functions.
Top AI-Powered Fintech Platforms Redefining Finance Tech
According to the CEO and co-founder of CreditMate, a leading tech company, Artificial Intelligence isn’t only the future of the Fintech industry but is also the present, emphasizing the significant impact it has had on the various financial services such as banking, payments, insurance, etc. There are many Fintech companies that are using AI to enhance their services and operations.
Here are a few Fintech platforms that are using AI to strengthen their data analysis and to improve their decision making capabilities:
- Capital Float/Walnut: It primarily makes use of AI technology for risk assessment, marketing as well as collections. It integrates artificial intelligence with human insight when deciding on which customers should be given loans to, how much, and when. Credit Float has managed to designed hybrid processes that depend on both human involvements as well as AI to determine which loan could be a bad loan and to improve customer targeting. Walnut, a personal finance management app acquired by Capital Float, uses AI to monitor the user’s spending behavior and patterns.
- Coverfox: Coverfox uses Artificial Intelligence to provide customers with the possibility of comparing as well as choosing from a wide variety of top insurance companies. AI has made it easier for their data analysts to collect as well as comprehend data pertaining to consumer interactions to predict critical trends. Not only this, in order to simplify sales and post-sales services, but it has also integrated AI with endorsements, policy issuance, inspections, and claims process with insurance companies.
- Lendingkart: Lendingkart has over 10,000 variables to determine whether customers are worthy of credit, with the help of proprietary algorithms. On average, it can analyze over 800 applications on 10,000 data points, by processing about 7,000 leads every day. Credit evaluation, product interaction, quality lead scoring, etc. are some of the functions that are being handled with the help of Artificial Intelligence. Not only that, when it comes to collections, but they can also predict the approximate amount which is likely to go, delinquent, which helps foresee manpower needs for the team. In terms of marketing front, they are able to analyze how much revenue each channel brings in, and then they manage to spend across different channels accordingly.
- RenewBuy: RenewBuy uses Artificial Intelligence for collection of data, figuring out combinations and permutations of insurance premiums and for data analytics, which helps create smart underwriting rules. Besides this, AI is also used for partner and customer service such as endorsements, co-creation of products, pre-sales, and post-sales, quote generation, etc. Within its app, AI is used to either approve or reject cases in real-time, when it comes to insurers’ underwriting logic engine since it has a self-inspection tool. Essentially, RenewBuy makes use of open source technologies to build flexible systems, and its infrastructure is primarily supported by cloud computing.
- ShubhLoans: Given the fact that there are still millions and millions of people that are not part of the formal credit system, ShubhLoans aims to democratize loans for such borrowers; it has made an effort to ensure the widespread availability of fair and transparent credit. It uses Artificial Intelligence along with data analytics to develop advanced credit assessment, lending, and risk management and enables lenders to gain access to market segments.
- mPokket: Another platform that works towards providing credit to underserved people that are not part of the traditional credit systems is mPokket. With the help of AI, it gathers as well as harnesses data points across demographics, social, financial, behavioral, and transactional factors to determine patterns, through proprietary credit-scoring algorithms. It makes use of AI in different manifestations for other processes such as user acquisition, customer support, user onboarding, collections, and others.
Finance tech has drastically transformed the finance industry as a whole, the addition of AI has further enhanced the efficiency of various financial operations. In the coming years, this integration will be witnessed on a greater scale, further improving the working of the financial services industry.