The finance industry has long been edging to make full use of Artificial Intelligence (AI).
The use of machine learning, a subset of AI, has exponentially increased in the global financial landscape. Its benefits include the creation of new business models, cost cuts, and the availability of customized services.
Today, machine learning and AI are helping financial institutions in:
- Delivering exceptional customer service
- Making well-informed decisions
- Improving productivity and efficiency of operations
With AI, financial experts expect significant improvements in customer service, increases in profits and facilitated the introduction of new products.
Here are some of the ways AI can change the finance industry for the better:
Early Identification of Potential Defaulters
A record number of Americans are behind on settling their debts. American households have added $26 billion in credit card debt. Moreover, around seven million Americans are at least three months behind on their car payments, according to an FRB press release.
It is vital to have an accurate system in place for banks to assess whether if a borrower can pay off the debt in a given time frame. Fortunately, it is possible to streamline this task with AI.
The use of AI not only provides lenders with an analysis of one’s credit score but also offers enough information to distinguish credit-worthy borrowers from those with a high potential to default.
Unlike humans, machine learning applications do not form emotional connections with people, ensuring unbiased decisions. This is why many industries now use AI to monitor and handle their finances.
Moreover, AI can be used for loan-issuing applications. For instance, it can be used to analyze sources other than credit scores, including mobile phone data, ensuring the candidate is worthy of a loan.
Risk Aversion is Now Possible
Business owners and managers often have a lot to worry about. Making budget forecasts and well-informed decisions requires a considerable amount of time and expertise. AI helps finance industry professionals by lowering the risks of human error.
With AI applications, you can store, organize, and analyze massive data sets in a short period of time. Additionally, machine learning and cognitive computing help decipher structured, as well as unstructured data.
Past cases, trends, and other variables could be analyzed for risk assessment. This helps in deducing any potential issues and preemptive measures to be taken for desired results.
Reduction in Fraudulent Activities
Consider this: in 2018 alone, global credit-card fraud losses have amounted to $24.26 billion. With the prevalence of online shopping, cases of data breach have picked up. Moreover, cases of identity theft and credit card fraud are also at an all-time high.
Therefore, it is important to prevent such activities by reinforcing security measures. After all, end-users want assurance that their transactions are channeled through a secure platform.
With AI applications, people’s behavior, purchasing habits, location, and other variables can be analyzed to ensure credibility.
If something seems out of place or contradicts a buyer’s routine behavior, a red flag is raised, and the transaction is halted immediately.
Moreover, banks can prevent crimes such as tax evasion and money laundering with the help of AI. These advanced algorithms can detect unusual behavior and uncover alleged schemes when assessing current and past transactions.
Stock Trading Will Become More Lucrative
With AI, trading stocks has also become much easier. Data-driven investments by brokerage houses are on a consistent incline — all thanks to AI and its credible judgments.
The ability to accumulate, organize, and analyze structured or unstructured data (news, social media, etc.) from a variety of sources facilitates decision making.
The stock market is highly dynamic, and there is little to no time to waste: calculated decisions need to be made instantly.
With proper use of machine learning in your decision-making process, this type of analysis takes little time, eliminating human error.
With AI’s innate capability of being scalable, its applications can be used in other operations as well. Essentially, the more AI is used the more it learns.
AI systems recommend the best portfolios to stockbrokers based on:
- Investor behavior
- Short-term goals
- Long-term goals
- Past activity on the portfolio
Therefore, it is not surprising that 56% of investment firms are eager to start making more use of AI to expedite their processes, while 40% want to set more budget aside for AI.
The Bottom Line
Recent advancements in AI technology are uncovering numerous opportunities for business leaders. With time, AI will redefine our interactions and the way we carry out our daily operations.
Being among the forerunners in adopting AI, financial institutions are creating better solutions to improve customer experience and transparency, and above, all increase profits. Moreover, the solutions offered by AI have widespread applications in other industries.