Artificial intelligence is almost in every industry worldwide, and it's fair to say that it's the topmost factor in many changes in the industries that incorporate them. From entertainment algorithms in different websites across the web to more personalized services like your everyday delivery of food to your house, all of them have utilized AI technology to further enhance and make their services faster.
However, while most people see it as a way to use the current technology to their advantage, some are against it because of the risks involved in AI technology being used in the finance industry.
We're going to talk about how AI technology affects the finance industry's current state and how it will impact it further in the near future.
Application of AI tech in the finance industry
Generally, there are two main categories of AI: unsupervised and supervised. In supervised AI, the programmers will feed it a set of rules that will sort out the data it will be given according to those rules. With this, the AI will learn how the lender works, like learning its underwriting rules, including the borrower's experience, collateral, credit score, etc.
Unlike humans that work a long time to process all of the clients' profiles, the AI can do it quickly in a matter of seconds, which usually works by sorting the clients by their risk and profitability. Moreover, supervised AI is mostly utilized by big banks because of their vast clientele. However, it is less common than its unsupervised sibling.
With an unsupervised AI, a data scientist will feed it a huge amount of data and just essentially flip the switch to let the AI identify different patterns across millions of variables. Confusing, isn't it?
In simpler terms, imagine an AI analysis that shows that people who use Twitter (News - Alert) during the night tend to post more than in the morning.
Of course, there are a lot of possible reasons as to why that is. But the most important thing is that now we know that there are possible reasons people tend to post during the night, and it's up to the scientist to find those reasons.
That said, using this analogy, we can assume that unsupervised AI is more relevant to lending companies since they sort out massive data while still retaining control as to which people are more to a particular loan service.
That said, it can also be used to calculate a person's credit score using the same analogy. The data scientist will feed the AI data representing a person's spending habits, loan balances, credit utilization, etc., to calculate that person's credit score.
However, many people are not into the idea of a machine calculating their scores since there might be new biases that will surface with the use of AI tech.
AI as a long term option
Analysts predict that with AI, companies will save at least 1 trillion dollars over the next 10-15 years. However, this number is only attainable by incorporating AI to bolster the efficiency of front and back-office services like data gathering and data processing. One trillion dollars is surely a huge number. Still, it doesn't really tell us anything about how AI can improve the services of financing companies.
That said, analysts broke down the 1 trillion dollars saving with these numbers:
- 30% increase in sales conversion rates
- 34% revenue increase
- 22% operating costs reduction
Just imagine how these numbers will do if they become the norm for your company. Truly, AI will be a catalyst for how all companies who adopt AI in their services will be prepared for the future. That said, currently, 70% of the world's banks have already implemented AI in their systems to make these numbers come true.
Unmet financing needs for profit
According to a joint report made by the International Finance Corp. and the SME Finance Forum, there are at least 65 million businesses, including micro, small, and medium businesses, that have unmet financing needs that all amount up to $5.2 trillion.
Not only that, but this number also represents the amount of financing that can be met if the businesses in developing countries also have the same credit access as first world countries.
Most lending companies have considered going into the area of down-market for a long time now, but it isn't possible because it costs tons of money, not to mention too time-consuming for most. However, with the emergence of AI, assessing risk, credit processing, and virtual transfer of money has made this possible for lenders to move down-market.
This is mainly because of smartphone apps that make it easy for people to access lending company services everywhere they go. With smartphone penetration, along with AI tech, it will be easy for lending companies to offer their services like giving their money paid in to your account almost immediately or requirements processing to people and businesses across the globe.
Takeaway
AI is a catalyst of change in a lot of industries right now. Not only does it save time and money for operating costs, but it also gives access to a lot of people for a chance to build clientele and gain much-needed revenue. However, the only downside of AI is its access is limited, as there aren't a lot of businesses who are willing to save time and money to incorporate AI in their systems. If this hurdle is passed, a lot of industries shall follow suit.
