Key applications of artificial intelligence (AI) in banking and finance
Can Artificial Intelligence Replace Traders? Exploring The Future
The world of trading has seen significant transformations over the years, evolving from traditional floor trading to electronic, and now to a new horizon where artificial intelligence (AI) plays a pivotal role.
With AI's infiltration into various industries, the finance sector has not been left untouched. This raises the compelling question: Can artificial intelligence replace traders?
The Role of Traders in Financial MarketsTraders are at the heart of financial markets, buying and selling securities, commodities, and other financial instruments. Their roles require not just an understanding of the markets but also quick decision-making, a knack for risk assessment, and often, a strong gut feeling.
Traders analyze market conditions, foresee potential market shifts, and make decisions based on both quantitative data and qualitative judgment.
Can Artificial Intelligence Replace Traders?Artificial intelligence has gradually integrated into the trading sphere, introducing automated systems capable of analyzing large datasets, predicting market trends, and executing trades at speeds no human could match.
AI applications in trading vary from algorithmic trading, which follows predefined instructions for placing trades, to more sophisticated machine learning models that adapt their strategies based on market behavior.
AI excels at processing and analyzing vast amounts of data rapidly, a process that would take humans considerably longer.
This capability allows AI systems to identify patterns and insights from historical data, facilitating more informed trading decisions.
Efficiency and Accuracy of AI in Trade ExecutionAI systems can execute trades more efficiently and with greater accuracy than humans. They can process transactions in milliseconds, capitalizing on market opportunities the moment they arise.
Moreover, AI reduces the potential for human error, executing trades exactly as programmed.
Emotional Neutrality of AIOne of AI's most significant advantages is its immunity to emotional bias. Human traders can be influenced by fear, greed, or stress, leading to suboptimal trading decisions. In contrast, AI strictly follows its programming, making decisions based solely on data and predefined strategies.
Limitations of AI in Trading Technological Limitations of AI SystemsDespite their abilities, AI systems still face technological limitations, particularly in interpreting non-quantitative data.
Human traders can consider news, rumors, and other qualitative factors in their decisions, nuances that AI might not fully comprehend.
The Unique Value of Human JudgementThere remain situations where the intuition and experience of human traders are irreplaceable.
Humans can understand context, make connections between seemingly unrelated events, and think creatively—capabilities that AI has yet to match fully.
Ethical and Misuse ConcernsThe use of AI in trading also raises ethical questions and the potential for misuse. Decisions made by AI could be manipulated if not monitored properly, leading to unfair trading advantages or even market manipulation.
AI and Job Displacement ConcernsThe fear that AI might replace human jobs in trading is a topic of concern. However, while AI can automate certain tasks, there is still a crucial need for human oversight.
AI systems require constant monitoring and refinement, roles that demand human expertise.
The future seems to be leading towards a symbiotic relationship between AI and human traders. As AI technology advances, its role in trading will undoubtedly increase.
However, this doesn't signify the end for human traders. Instead, it suggests an evolution of their roles, where they work alongside AI, leveraging its strengths while contributing human insight and oversight.
Predictive Trends in AI DevelopmentInvestments in AI by financial institutions are growing, indicating a trend towards more AI-driven trading platforms.
These platforms will likely become more sophisticated, capable of handling complex trading strategies and decision-making processes.
The Emerging Collaborative Model of Human-AI Trading TeamsA collaborative model where human traders and AI systems work together is emerging.
In this model, AI handles data analysis and execution, while humans focus on strategy development, oversight, and incorporating qualitative insights.
This collaboration aims to harness the best of both worlds, optimizing trading outcomes.
Frequently Asked Questions Can AI predict stock market movements?AI can perform predictive analyses based on historical data and trends, but its predictions are not foolproof. The market's inherent unpredictability means that AI, like humans, can't always foresee movements accurately.
Will AI create or destroy jobs in the trading sector?AI will likely transform jobs in the trading sector rather than eliminate them outright. As AI takes over more technical, data-driven tasks, human traders will adapt, focusing on strategy, oversight, and areas where human insight is invaluable.
How can traders stay relevant in an AI-driven market?Traders can stay relevant by developing skills that complement AI, such as data analysis, AI system monitoring, and refining trading strategies based on AI insights. Understanding AI and its applications in trading will also be crucial.
Are there trading sectors where AI cannot compete with human traders?AI currently struggles in areas requiring qualitative judgment and understanding of human behavior, such as predicting reactions to unexpected news events. Sectors that rely heavily on these aspects may see less AI competition.
How secure is AI in handling sensitive financial data?Security is a top priority when it comes to AI in trading. While no system is entirely immune to breaches, stringent security measures and constant vigilance are necessary to protect sensitive financial data in AI-driven systems.
ConclusionIn answering whether AI can replace human traders, it's clear there's no straightforward answer.
AI offers significant advantages in data analysis, efficiency, and eliminating emotional bias. Yet, the unique value of human judgment and the ability to interpret non-quantitative information remain vital.
The future of trading likely lies in the collaboration between AI and human traders, each playing to their strengths to navigate the complex and ever-changing financial markets.
Sparse Artificial Intelligence MCU From Femtosense And ABOV Semiconductor Delivers Low-Cost, Low-Power AI-based Voice Processing To The Edge
AI-ADAM-100 AI MCU enables on-device "say what you mean" language processing and voice-cleanup capabilities for home appliances and other products
SAN BRUNO, Calif., July 17, 2024--(BUSINESS WIRE)--Femtosense, in partnership with ABOV Semiconductor, today launched the AI-ADAM-100, an artificial intelligence microcontroller unit (AI MCU) built on sparse AI technology to enable on-device AI features such as voice-based control in home appliances and other products. On-device AI provides immediate, no-latency user responses with low power consumption, security, operational stability, and low cost compared to GPUs or cloud-based AI.
The AI-ADAM-100 integrates the Femtosense Sparse Processing Unit 001 (SPU-001), a neural processing unit (NPU), and an ABOV Semiconductor MCU to provide deep learning-powered AI voice processing and voice-cleanup capabilities on-device at the edge. With language processing, appliances can implement "say what you mean" voice interfaces that allow users to speak naturally and express their intent freely in multiple ways. For example, "Turn the lights off", "Turn off the lights," and "Lights off" all convey the same intent and are understood as such. Voice/audio cleanup processes data before it is sent to the cloud, improving reliability and accuracy while reducing the volume of data sent, thus reducing backend infrastructure costs.
"With sparsity integrated throughout the AI development stack, the AI-ADAM-100 is the first device on the market to fully unlock the advantages of sparse AI," said Sam Fok, CEO, Femtosense. "Our sparsity-enabling technology allows our customers to deliver compact, efficient AI processing to a growing variety of markets and products, including home appliances as well as small form factor, battery-operated devices like high-fidelity hearing aids, industrial headsets, and consumer earbuds."
On top of the AI-ADAM-100, Femtosense provides a highly customizable selection of AI-ADAM-100–based AI software application products—from full turnkey solutions to tool-driven applications or full custom implementations using a manufacturer's own AI models, whether dense or sparse.
The Sparse AI Advantage
Sparse AI reduces the cost of AI inferencing by zeroing-out irrelevant portions of an algorithm and then only allocating hardware memory and compute resources to the remaining nonzero, relevant portions of the algorithm. A system that stores and computes only nonzero weights can deliver up to a 10x improvement in speed, efficiency, and memory footprint. Similarly, a system that computes only when a neuron's output is nonzero can deliver up to another 10x increase in speed and efficiency. Those 10s can multiply. Consequently, sparse AI enables manufacturers to implement deep learning–based AI models of up to 100x the power/complexity of previous MCUs without adversely impacting speed, efficiency, memory footprint, or performance.
Story continues
While many edge applications can benefit from AI, they often lack the price or power flexibility to implement a GPU, cloud connectivity, or the volume to support a dedicated silicon solution. This has limited the adoption of edge AI. With the introduction of the AI-ADAM-100, manufacturers can implement voice language interfaces at the edge even for devices that are not connected to the cloud.
Many existing AI systems are always processing and consuming power even when the task is easy, like when the environment is quiet. Pure, cloud-based voice processing requires continuous throughput, leading to high infrastructure cost. The AI-ADAM-100 resolves tasks on-device to significantly reduce power and backend cloud loading. Specifically, the AI-ADAM-100 enables home appliance manufacturers to implement sophisticated wake-up and control functionality, allowing other system controllers and connectivity modules to drop into sleep mode and consume substantially less power when a user is not interacting with the system. This capability can be used to listen until a user's voice command is received, and then to either process the command on-device or wake the system to send the command to the cloud.
A Product of Partnership
Femtosense and ABOV developed the AI-ADAM-100 MCU in strategic collaboration, leveraging the core strengths of each partner. "The AI-ADAM-100 is the best-optimized AI MCU solution for voice and audio-based AI applications and enables a variety of on-device AI applications for consumer electronics and standalone devices," said Choi Won, CEO of ABOV Semiconductor. "Together with Femtosense, we will continue to develop the most cost- and power-efficient AI MCUs for global customers."
ABOV has verified AI-ADAM-100's top-notch voice command recognition performance under multiple noise conditions, meeting the requirements of leading customers. Global home appliance makers are working to reduce the number of buttons on their devices and streamline the user experience. AI-based voice command can accelerate this trend.
Availability
Engineering samples of the AI-ADAM-100 are available now with commercial mass production targeted for later this year. Development support includes software tools, evaluation boards, and demo AI models, including Smart Home Appliance Wake-up and Control. To learn more about the AI-ADAM 100, visit https://femtosense.Ai/products/.
About Femtosense, Inc.
Femtosense enables real-time, on-device AI using sparse, localized mathematics. The company's products provide efficient, scalable, and affordable AI to mass market electronics that include hearables, appliances, wearables, security, TVs, smart homes, and industrial and automotive devices. Femtosense is based in Silicon Valley and has partners worldwide. For more information, visit https://femtosense.Ai.
About ABOV Semiconductor Co., Ltd.
ABOV Semiconductor is a South Korea–based company that is a leading provider of microcontrollers for the consumer electronics, industrial automation, automotive, and IoT sectors. The company empowers cutting-edge technology that can elevate customer operations to new heights with its high-performance and cost-effective solutions. ABOV Semiconductor has set industry precedents with its robust R&D capabilities, close customer collaborations, and dynamic response to market changes. For more information about ABOV Semiconductor, please visit www.Abov.Co.Kr.
View source version on businesswire.Com: https://www.Businesswire.Com/news/home/20240717558929/en/
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The Automated Race To Use Artificial Intelligence To Screen Job Applicants
"The need is pretty clear," said Steven Skiena, professor and director of Stony Brook University's AI Institute. "For many jobs, businesses get hundreds or thousands of applicants." He is shown in the New Computer Science Building at Stony Brook in June. Credit: Newsday/John Paraskevas
Artificial intelligence increasingly is becoming a go-to tool for human resources departments in the hiring process, even as some professionals raise concerns about potential bias and reliability of the software programs.
With the growth of online job boards and networking sites such as Indeed, Monster.Com and LinkedIn making it easier for job hunters to submit resumes, overwhelmed HR departments are using artificial intelligence tools to screen thousands of resumes and applications within minutes.
However, concerns over the way AI processes data and finds patterns has led some in the tech and recruiting fields to worry about bias against jobseekers.
"Right now, there are about one in four employers [26%] who are saying they are using AI" for some sort of HR purpose, said Clay Lord, director of programs for the SHRM Foundation, the charitable arm of the Society for Human Resource Management. "We anticipate that number is going to go up substantially quickly."
Of the organizations that have been using AI, 64% say they use it for recruitment, interviewing, or hiring, to some capacity, according to a nationwide survey of 2,366 human resources professionals released in February by the SHRM.
In line with the sweeping popularity and interest of AI tools such as ChatGPT, which launched in 2022, more than 62% of professionals said their organization began using AI for HR functions sometime over the past year.
"Employers on average are spending about six and half seconds to assess a resume," Lord said. "Right now, what that means is it's a relatively unnuanced process."
Hence, an increased appetite for AI tools that can speed up the process.
AI screening tools allow hiring managers to quickly sift through an increasing number of online applications and resumes, made larger by the fact that many employers now hire for remote positions.
"Now, they're getting candidates from around the country, not just near the office," said Stacie Haller, chief career adviser for ResumeBuilder.Com. "That has tremendously increased the volume."
Popular job search sites Indeed and LinkedIn recently launched a suite of AI tools for both employers and jobseekers.
Earlier this year, Indeed released Smart Sourcing to help employers identify and screen potential candidates on the business networking site as well as tools for jobseekers.
"Indeed's AI-powered tools analyze the entire resume or application to create a comprehensive summary of a candidate's qualifications," Clint Carrens, career strategist for Indeed, said in an email. "This summary, which is shared with employers, provides a holistic view of the candidate, moving beyond the traditional keyword-based resume screening."
LinkedIn, too, unveiled AI job search tools for jobseekers in June. Although the networking site doesn't have applicant screening technology built into its LinkedIn Recruiter tool set for employers, it does use machine learning to help recruiters rank search results based on factors including work experience and skills.
Machine learning refers to the development of computer systems that can learn and analyze data using algorithms without explicit instructions.
"We firmly believe AI is here to assist with the hiring process — not displace it," said Rohan Rajiv, director of product management at LinkedIn. "By helping with the more arduous tasks, it will help free up hirers' time to focus on more strategic and human work, like speaking with and getting to know the candidates, and interviewing them for the skills they can bring to the job."
Although generative AI tools like OpenAI's ChatGPT have created a wave of intrigue among employers, tools that sort through online resumes and applications have been around for years in the form of applicant tracking systems, or ATS programs, recruiters said.
ATS software long has helped employers and recruiters track and organize job candidates through the screening and hiring process. Many of these systems provide keyword scanning tools that help hiring managers instantly sort resumes into distinct "yes" and "no" piles.
"A lot of the people that we deal with may not be as computer savvy," said Jim Eddings, supervisor of Suffolk County's One-Stop Employment Center. "We have to explain that the companies are using an ATS system to basically weed out or get resumes they deem good or match their algorithm."
Eddings said the days of walking into a business and submitting a resume in person were long gone, and many job seekers — namely those who hadn't been on the job hunt in decades — found the impersonal nature of trying to impress an algorithm frustrating.
"The way you look for work has changed a lot," Eddings said. "You have to almost think differently."
Adjusting to writing resumes to make it past screening software for the chance to maybe advance to the next level of the hiring process can be a headache for many jobseekers.
"This is the new way of the world," Eddings said. "The resume was previously used to get the interview, and now it's to get in the 'yes' pile to potentially get an interview. It's another layer that's been put in there. It is a very frustrating process."
Local experts in the field of artificial intelligence said the use of such tools in the hiring process made sense, though concerns remained.
"The need is pretty clear," said Steven Skiena, professor and director of Stony Brook University's AI Institute. "For many jobs, businesses get hundreds or thousands of applicants."
But Skiena said one of his main concerns was how strict AI could be in its filtering out candidates based on something potentially arbitrary like missing keywords.
"Say if you were a job seeker with a resume that didn't have the magic words on it, and that for some reason the AI system doesn't like your resume, you would get rejected by it every time," Skiena said.
It's possible, Skiena said, that a great candidate who otherwise might have some formatting irregularities in their resume or CV could be effectively locked out of the online application process without them knowing it.
"The advantage of human screeners, to a certain extent, is a degree of variability," he said. "If there's something in the screening algorithm that doesn't like something weird about you or weird about your resume, you basically have no way of figuring that out."
Additionally, Skiena pointed to examples of unintended bias being perpetuated by AI software with large companies such as Amazon.
In 2017, it was discovered by machine learning specialists at Amazon that a secret AI resume scanning tool the company was testing at the time was favoring male candidates. The bias was due in part to the data the specialists were using to train the AI; employee resumes over a 10-year period.
As a result, the AI observed that the bulk of resumes were from men — in line with broader gender disparities in tech — and likely concluded that male candidates were preferable as a result.
Despite concerns about unintended bias from AI in the screening process, the optimistic view is that the technology might help employers reduce bias in the hiring process by bypassing unconscious bias on the part of human screeners and hiring managers.
In that way, AI could play a role in helping employers expand diversity among its employees.
"In some sense, I would imagine that resume screening systems for classic examples of bias may be better than humans," Skiena said
HiBob, an HR software company, is exploring the implementation of AI into its own line of products sometime next year. Company officials say they are taking their time in adding applicant screening tech.
"We are in the very early days of exploring AI capabilities and how we can use it effectively and responsibly to help our customers in leveraging it and becoming more efficient," said Annie Rosencrans, director of people & culture at HiBob's office in Manhattan.
"There are certainly a lot of unknowns, and we don't want to be too quick on this," she said.
Rosencrans said concerns of bias and the data used to train AI were concerns for HR professionals tasked with working with employees.
"That's exactly the reason why we are actively pursuing AI, but not doing it too quickly," Rosencrans said. "There's a lot we don't know yet. A big one is the bias piece. When we're talking about people, it's critical to get it right.
"We want to make sure we implement it in the most responsible and ethical way," she added.
Haller, chief career adviser for ResumeBuilder.Com, says she does worry about HR professionals becoming too reliant on new technologies in pursuit of efficiency.
"It has to find its place," Haller said.
And while many organizations are looking at implementing AI to screen resumes, cover letters or applications, some are going as far as implementing some form of AI in the interview process.
A June 2023 survey from ResumeBuilder found that around 43% of employees involved in their company's hiring processes said their organization planned to start using AI interview software this year, with around 10% having already implemented it.
Haller says she doesn't imagine AI interviewers will take off as quickly as text screening tools.
"I don't believe there's a person on the planet that wants to be interviewed by a robot," she said.
Artificial intelligence increasingly is becoming a go-to tool for human resources departments in the hiring process, even as some professionals raise concerns about potential bias and reliability of the software programs.
With the growth of online job boards and networking sites such as Indeed, Monster.Com and LinkedIn making it easier for job hunters to submit resumes, overwhelmed HR departments are using artificial intelligence tools to screen thousands of resumes and applications within minutes.
However, concerns over the way AI processes data and finds patterns has led some in the tech and recruiting fields to worry about bias against jobseekers.
"Right now, there are about one in four employers [26%] who are saying they are using AI" for some sort of HR purpose, said Clay Lord, director of programs for the SHRM Foundation, the charitable arm of the Society for Human Resource Management. "We anticipate that number is going to go up substantially quickly."
Of the organizations that have been using AI, 64% say they use it for recruitment, interviewing, or hiring, to some capacity, according to a nationwide survey of 2,366 human resources professionals released in February by the SHRM.
In line with the sweeping popularity and interest of AI tools such as ChatGPT, which launched in 2022, more than 62% of professionals said their organization began using AI for HR functions sometime over the past year.
"Employers on average are spending about six and half seconds to assess a resume," Lord said. "Right now, what that means is it's a relatively unnuanced process."
Hence, an increased appetite for AI tools that can speed up the process.
AI screening tools allow hiring managers to quickly sift through an increasing number of online applications and resumes, made larger by the fact that many employers now hire for remote positions.
"Now, they're getting candidates from around the country, not just near the office," said Stacie Haller, chief career adviser for ResumeBuilder.Com. "That has tremendously increased the volume."
Popular job search sites Indeed and LinkedIn recently launched a suite of AI tools for both employers and jobseekers.
Earlier this year, Indeed released Smart Sourcing to help employers identify and screen potential candidates on the business networking site as well as tools for jobseekers.
"Indeed's AI-powered tools analyze the entire resume or application to create a comprehensive summary of a candidate's qualifications," Clint Carrens, career strategist for Indeed, said in an email. "This summary, which is shared with employers, provides a holistic view of the candidate, moving beyond the traditional keyword-based resume screening."
LinkedIn, too, unveiled AI job search tools for jobseekers in June. Although the networking site doesn't have applicant screening technology built into its LinkedIn Recruiter tool set for employers, it does use machine learning to help recruiters rank search results based on factors including work experience and skills.
Machine learning refers to the development of computer systems that can learn and analyze data using algorithms without explicit instructions.
"We firmly believe AI is here to assist with the hiring process — not displace it," said Rohan Rajiv, director of product management at LinkedIn. "By helping with the more arduous tasks, it will help free up hirers' time to focus on more strategic and human work, like speaking with and getting to know the candidates, and interviewing them for the skills they can bring to the job."
Although generative AI tools like OpenAI's ChatGPT have created a wave of intrigue among employers, tools that sort through online resumes and applications have been around for years in the form of applicant tracking systems, or ATS programs, recruiters said.
ATS software long has helped employers and recruiters track and organize job candidates through the screening and hiring process. Many of these systems provide keyword scanning tools that help hiring managers instantly sort resumes into distinct "yes" and "no" piles.
"A lot of the people that we deal with may not be as computer savvy," said Jim Eddings, supervisor of Suffolk County's One-Stop Employment Center. "We have to explain that the companies are using an ATS system to basically weed out or get resumes they deem good or match their algorithm."
Eddings said the days of walking into a business and submitting a resume in person were long gone, and many job seekers — namely those who hadn't been on the job hunt in decades — found the impersonal nature of trying to impress an algorithm frustrating.
"The way you look for work has changed a lot," Eddings said. "You have to almost think differently."
Adjusting to writing resumes to make it past screening software for the chance to maybe advance to the next level of the hiring process can be a headache for many jobseekers.
"This is the new way of the world," Eddings said. "The resume was previously used to get the interview, and now it's to get in the 'yes' pile to potentially get an interview. It's another layer that's been put in there. It is a very frustrating process."
Local experts in the field of artificial intelligence said the use of such tools in the hiring process made sense, though concerns remained.
"The need is pretty clear," said Steven Skiena, professor and director of Stony Brook University's AI Institute. "For many jobs, businesses get hundreds or thousands of applicants."
But Skiena said one of his main concerns was how strict AI could be in its filtering out candidates based on something potentially arbitrary like missing keywords.
"Say if you were a job seeker with a resume that didn't have the magic words on it, and that for some reason the AI system doesn't like your resume, you would get rejected by it every time," Skiena said.
It's possible, Skiena said, that a great candidate who otherwise might have some formatting irregularities in their resume or CV could be effectively locked out of the online application process without them knowing it.
"The advantage of human screeners, to a certain extent, is a degree of variability," he said. "If there's something in the screening algorithm that doesn't like something weird about you or weird about your resume, you basically have no way of figuring that out."
Additionally, Skiena pointed to examples of unintended bias being perpetuated by AI software with large companies such as Amazon.
In 2017, it was discovered by machine learning specialists at Amazon that a secret AI resume scanning tool the company was testing at the time was favoring male candidates. The bias was due in part to the data the specialists were using to train the AI; employee resumes over a 10-year period.
As a result, the AI observed that the bulk of resumes were from men — in line with broader gender disparities in tech — and likely concluded that male candidates were preferable as a result.
Despite concerns about unintended bias from AI in the screening process, the optimistic view is that the technology might help employers reduce bias in the hiring process by bypassing unconscious bias on the part of human screeners and hiring managers.
In that way, AI could play a role in helping employers expand diversity among its employees.
"In some sense, I would imagine that resume screening systems for classic examples of bias may be better than humans," Skiena said
HiBob, an HR software company, is exploring the implementation of AI into its own line of products sometime next year. Company officials say they are taking their time in adding applicant screening tech.
"We are in the very early days of exploring AI capabilities and how we can use it effectively and responsibly to help our customers in leveraging it and becoming more efficient," said Annie Rosencrans, director of people & culture at HiBob's office in Manhattan.
"There are certainly a lot of unknowns, and we don't want to be too quick on this," she said.
Rosencrans said concerns of bias and the data used to train AI were concerns for HR professionals tasked with working with employees.
"That's exactly the reason why we are actively pursuing AI, but not doing it too quickly," Rosencrans said. "There's a lot we don't know yet. A big one is the bias piece. When we're talking about people, it's critical to get it right.
"We want to make sure we implement it in the most responsible and ethical way," she added.
Haller, chief career adviser for ResumeBuilder.Com, says she does worry about HR professionals becoming too reliant on new technologies in pursuit of efficiency.
"It has to find its place," Haller said.
And while many organizations are looking at implementing AI to screen resumes, cover letters or applications, some are going as far as implementing some form of AI in the interview process.
A June 2023 survey from ResumeBuilder found that around 43% of employees involved in their company's hiring processes said their organization planned to start using AI interview software this year, with around 10% having already implemented it.
Haller says she doesn't imagine AI interviewers will take off as quickly as text screening tools.
"I don't believe there's a person on the planet that wants to be interviewed by a robot," she said.
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