5 Ways AI Will Transform the Finance Sector in 2021
Artificial intelligence (AI) has been making an impact on various parts of the financial world for years now. As tends to be the case with AI, (and really with technology in general), the significance of that impact is accelerating rapidly. Where we first saw AI creeping into finance awhile back, it is now taking over practices, shaping careers, and altering methods and services of all kinds.
To explore this topic a little bit more closely, we’re going to use this post to look into five specific ways in which AI is poised to transform difference facets of the finance sector, both now and in the future.
1. Improving Risk Assessment
“Risk assessment” is a concept that can be applied to a number of different specific purposes within the financial world. But generally speaking, it is also one of the things most commonly associated with AI and its expanding influence in finance.
A Forbes write-up on AI and financial risk assessment conveyed that this subject primarily relates to auditing processes and fraud detection. As that piece relays, a massive number of people and companies today experience fraud of one kind or another. And this is chalked up to the fact that “if a company isn’t analyzing every single transaction in a dataset, risks will go undetected.” In other words, a company that isn’t analyzing its financial dealings in a comprehensive and exhaustive manner will be more prone to fraudulent dealings or mistakes, by no fault of any specific shortcoming or individual performance.
One solution to this problem that we’re seeing more of in 2021 is the use of AI auditing software to augment typical internal efforts. Automating the process of auditing financial dealings simply expands the breadth of analysis, hastens the analysis, and makes it more likely — if not virtually certain in some cases — that risks will be detected in advance. Companies employing AI in this manner moving forward will therefore be able to avoid financial fraud and mishaps far more frequently. Financial management at the enterprise level will become a more exact and refined process.
2. Precision in Lending
When you consider “risk assessment” more broadly (which is to say not with specific respect to company performance) you might also think of lending. This is a massive industry unto itself within the finance sector, and it’s another one in which AI is playing an increasingly significant role. We actually dove into the nature of that role in a previous post titled “How is Artificial Intelligence Used in Banking?”.
To offer a brief recap, in the post we explained that banks have historically faced a challenge of “unstructured data,” which is to say data that is gathered without a specific purpose, or which is gathered but not organized in a productive manner. Financial firms and banks have long recognized the importance of collecting information, but in many cases — at least until recent years — have not properly understood how to maximize the usefulness of that information. This can be problematic with regard to a number of practices, with lending being chief among them.
As the aforementioned post also explained, banks are now using AI within their credit lending processes. Through this practice, a bank can gain a far more expansive (and accurate) picture of a potential borrower’s creditworthiness by assessing online behavior in addition to raw numbers. This in and of itself is another form of risk assessment, allowing financial institutions to protect themselves by lending only according to concrete, data-driven expectations.
3. Altered Career Paths
As is often the case where AI is relevant, there has been talk of a sort of automated takeover of the financial sector. Back in 2017 for instance, a post on robots in finance by a Sunway University Professor of Finance painted a picture of the year 2030 — positing that by that point there could be “no jobs for finance majors” due to the emergence of robo-advisers.
To be clear, the article was not definitively stating that this is an inevitability. It was making the case for the possibility however, and in doing so made a compelling argument that some jobs will be lost to automation. As much as this may be the case, we would suggest that both in 2021 and moving forward we’re going to see career paths in the financial sector altered rather than done away with entirely.
One argument in support of the ongoing strength of this field is that even beyond traditional university courses like those for the “finance majors” discussed in the article, those interested in pursuing a degree in finance can easily do in online now. This means more students are getting opportunities in this space. And studies from several institutions show that there is still “extraordinary growth” projected in finance-related fields of work. What is interesting though is that this growth is primarily expected for personal financial advisors, financial analysts, and financial services sales agents.
Reading between the lines, those are all finance careers that can coexist (and indeed already do) with AI. We expect to see this evolution progress moving forward, such that AI handles raw financial data and finance careers are shaped to interpret and relay that data through analysis and service positions.
4. Robo-Investing
On a more individual level, AI is also continuing to impact the world of finance by changing investing practices. Once upon a time, the notion of “robo-investing” was reserved for large firms and high-powered hedge fund managers with significant resources. More and more, we’re seeing online tools and apps bringing automation to the masses, so that individual traders have the option of managing their investments with automated assistance.
A few years ago, a Business Insider article on the rise of robo-investing cited a survey indicating that 49% of high-net-worth individuals would consider “letting a robot advisor manage at least some of their wealth.” That sentiment figures to have expanded since, and — thanks to mass-marketed apps like Acorns — spread to individuals who aren’t considered to have high net worth as well. Ultimately, the appeal is simple and virtually guaranteed to continue expanding: As AI grows more sophisticated and people grow more comfortable with it, the notion of data-driven, automated investment tools outperforming human counterparts will become commonplace.
It isn’t unrealistic to expect that in another few years it will be considered strange to manage investment or trading portfolios manually.
5. Personal Financial Management
Expanding on the concept of robo-investing for individuals, we are also beginning to see more general financial management entrusted to automation. What this means is that people are turning to data-driven tech tools to assist them with day-to-day budgeting, analysis of spending habits, financial planning, and so on.
There have been clear stepping stones toward this eventuality, most notably in the form of personal budgeting and financial tracking apps like Mint and its numerous counterparts. Those apps are essentially very well designed organizational tools, meant to make it easier for people to track their own activity and make informed decisions. Now, however, a new generation of apps like Wallet are infusing the same concept with AI. Wallet uses artificial intelligence to draw insights from users’ financial activity, so as to point out noteworthy trends and make suggestions. We expect to see this sort of service become significantly more prominent over the course of the next year or two.
By no means are these the only ways in which AI is impacting the finance sector. But they do convey the influence AI has in 2021, from enterprise-level financial planning, to bank practices, to individual needs.
For information on how AI is impacting the asset management industry, download Accern's AI for Asset Managers E-book.
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