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This article was very insightful for me as it gave me reasons why AI is so beneficial in finance. It taught me that AI helps banks and customers in different but equally beneficial ways. Banks can save money by using AI and give customers more options through personalizations features and reduce traffic to the branches.

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This source is a popular source because it was uploaded to forbes and doesn't include a citations page or references page. It also doesn't include any specialized language that is difficult to understand.

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Joe McKendrick focuses on AI in finance but more specifically in banking. He explains that AI for banks allows for there to be a reduced amount of branches while still allowing for personalization for customers and small business owners. He also explains that AI can help the banks themselves avoid "financial disasters" by making better financial decisions about risks and capital allocation. Another benefit is fraud detection and prevention services provided by AI. The AI can recognize unusual or irregular purchases and protect customers and businesses from fraud. McKendrick also adds that the implication of AI needs to keep humans in the loop so that AI empowered decisions won't "ignite the risk of prioritizing profit while ignoring social impact."

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Source 2:Artificial Intelligence Opens Up The World Of Financial Services

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Source 2:Artificial Intelligence Opens Up The World Of Financial Services

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By: Joe McKendrick
Source: News Article

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If you're running a financial services firm, and you want to promote digital transformation, you need to decide what exactly needs to be transformed. "In all honesty, what areas aren't there?" says Teddy Flo, general counsel at Zest AI. "The financial services industry is vastly behind other consumer-centric industries in a lot of ways."

Any and all transformations should have one goal, and one goal only: delivering to the customer - ultimately enriching their relationships with banks and nonbanks alike. "You can't change anything for the better if everyone doesn't have equitable access to capital," Flo says. "The way we make decisions on credit should be fair and inclusive and done in a way that takes into account a greater picture of a person."

Here are the ways AI can help assure more equitable access to financial services:

Personalize without branches. While banks keep scaling down their in-person branch locations, AI may help keep things personalized. "Ironically, artificial intelligence can help redefine and restore personalized experiences that build trust for consumers and small business owners," says Charlene Coleman, senior managing partner and head of the modern finance sector of Launch Consulting Group. "An example is AI-powered personalized conversational interfaces and biometric profiles that have shown promise in helping vulnerable consumers avoid debt traps fueled by late fees and inflexible payment schedules."

Make more informed risks. AI can help prevent financial disasters, thanks to current abilities to "make appropriate, informed decisions about risk and capital allocation," says Dr. Lewis Z. Liu, CEO and co-founder of Eigen Technologies. "By leveraging AI, financial institutions are better equipped to really transform the decision-making process to be more accurate, efficient, and successful." Many financial institutions "make risk, capital allocation and underwriting decisions, based on as little as 10% of the data available to them," says Liu. "This is normally because it is simply too expensive or too difficult to access the data they need. Introducing AI into this process plays a major part in improving outcomes. Through the use of AI, a wide range of organizations have been able to access and utilize previously inaccessible 90% of relevant data, enabling them to make more informed and better decisions."

Reduce or prevent fraud. AI also "opens up a new world of opportunity to tackle and reduce fraudulent activities such as money laundering," Liu continues. "This allows institutions to validate transactions, bolster security, and respond to threats." As an example of AI in action, "companies are leveraging AI to monitor large number of credit card and e-payment transactions daily, detect changes in our purchase behavior, and provide a more streamlined process to deal with any fraudulent activities to protect us," says says Vrinda Khurjekar, senior director at Searce.

Line up new industry players. AI could shift the balance between traditional banks and faster-moving FinTechs. "Big banks and financial corporations should be wary of ceding ground to AI-first institutions, neo-banks and big tech looking to enter banking as their next adjacency," Coleman cautions. "Traditional finance has an opportunity to block these disrupters with sector expertise and deep capital, but have shown a reluctance to truly embrace advanced technology." As a result, AI-first companies and FinTechs "are certainly gaining ground and disrupting traditional financial services," says Liu. "However, many of these FinTechs haven't invented anything new. Instead, they're increasing the standard of digital service for an existing concept." For example, he continues, "Think about how Venmo transformed the mobile payments space, or how Klarna changed the game for short-term financing. It was less about bringing something new to financial services and more about changing the actual way it was done."

Speed up services. "Since the applications have not fully scaled with the new age technologies, there are a lot of processes which are still being done manually since seamlessly automating them is a challenge for most of these institutions," says Khurjekar. For example, "loan processing, customer onboarding or check deposit processes are not very well integrated by majority of the banking systems. If you are trying to get a mortgage loan it could still take a long time for you to complete all the steps which can be reduced drastically if the banks had less technical debt and were able to adopt new age cloud solutions faster."

Leverage human-AI partnerships. While AI solves a lot of problems faced by financial institutions, successful banks have developed processes that keep humans in the loop. "Deploying AI to democratize the financial system requires bold, human-centered leadership willing to invest in technology and talent." says Coleman. "Credit underwriting decisions made only by an algorithm designed without humans in the loop will ignite the risk of prioritizing profit while ignoring social impact," Coleman points out. "The algorithm might then learn to discriminate against specific population segments, resulting in unfair decisions."

The rise of AI in financial services is raising expectations from banks and FinTechs alike. Banks "are fundamentally rethinking all their net new investments into their technology stack," says Khurjekar. "If data center leases are expiring, there is a very active effort to evaluate what portions of those applications need to be re-written or moved to the cloud for better scalability. Banks are using AI and machine learning to predict consumer behavior, understand their purchase preference, and even outlier fraud detection to better card and transaction management."

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Artificial Intelligence Opens Up The World Of Financial Services

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If you're running a financial services firm, and you want to promote digital transformation, you need to decide what exactly needs to be transformed. "In all honesty, what areas aren't there?" says Teddy Flo, general counsel at Zest AI. "The financial services industry is vastly behind other consumer-centric industries in a lot of ways."

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I think that the implications described along with the benefits of AI from this article show that a future driven by AI will make finance more efficient as well as simpler for both customers and corporations. I think that this article gives a nice and brief overview of what AI in finance looks like and was very helpful to expanding my knowledge on the subject.

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This source is a trade source because it is under the Hewlett and Packard website and it includes some specialized language but thoroughly explains what the author is saying.

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This article explains what AI and Machine Learning implications in finance look like. "With AI as part of their infrastructure, banks, investment firms, and insurance companies can use it to perform real-time calculations to forecast performance, detect anomalous spending behavior, or maintain compliance, among a plethora of other applications." Another example of AI use in finance is risk management which can help companies reduce risks related to fraud, money laundering, and improve their overall security. The article goes on to explain some of the benefits of AI like accelerating and automating manual and time consuming tasks and improving customer experiences.

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By: author unknown
Source: Article/Advertisement

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How is AI powering the future of financial services?

AI in finance is modernizing the entire industry by streamlining traditionally manual banking processes and unlocking deeper insights from generated data, helping dictate how and where investments are made. AI is also changing the customer experience by creating faster, contactless interactions that include real-time credit approvals and improved fraud protection and cybersecurity.

How does AI impact the finance industry?

AI is a large driving force for how financial organizations conduct risk management, which includes security, regulatory compliance, fraud, anti-money laundering (AML), and know-your-customer (KYC) guidelines. With AI as part of their infrastructure, banks, investment firms, and insurance companies can use it to perform real-time calculations to forecast performance, detect anomalous spending behavior, or maintain compliance, among a plethora of other applications.

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AI in finance is modernizing the entire industry by streamlining traditionally manual banking processes and unlocking deeper insights from generated data, helping dictate how and where investments are made. AI is also changing the customer experience by creating faster, contactless interactions that include real-time credit approvals and improved fraud protection and cybersecurity.

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I think that this article is very helpful in helping me understand how a new technology or system would be integrated into a company. I think that AI will definitely need to have a slow implementation with different training opportunities for employees to learn how to work with it effectively. I think that the integration of AI in finance will be a bumpy road but a road that could lead to success for a company if the system is used properly and is properly programmed. This article explains 13 very useful tactics that could help developers of AI train employees to use AI. I think that it could lead to a very successful transition from whatever systems and services that are now being used to the future of technology in AI.

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This source is a popular source because it is not published under a specific webpage that is written for a specific group. It is a forbes article that seems to be just general information for integrating new systems at work. The article doesn't include any sources within the article.

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This article takes a step back from the implications of AI and covers technics that companies should use when implementing new tech to their employees. Its seems that the tactics that show the most support for employees of extended periods of time seem to work best when transitioning into new technology. The article claims that creating a sandbox style of the program can help employees practice with the new tech while not feeling that they are under pressure of losing their job if they mess up. It also gives an area for employees to take risks and be more ambitious which could ultimately help the company succeed. The article also states that a slow implementation will allow the employees to ease into the new tech and become more comfortable using it once the system is fully integrated. The last point that i think would be most useful for integrating new tech would be offering a ton of training. The article stresses that there should be multiple training services offered such as online, in person, videos, and readings that will help employees make adjustments going forward with new tech and systems.

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Source 4: 13 Practical Ways To Help Employees Adapt To New Technology

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Source 4: 13 Practical Ways To Help Employees Adapt To New Technology

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By: Forbes Human Resources Council
Source: News Article

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Tech continues to play a larger and larger role in businesses and industries of all stripes. As companies bring on more and newer technology to help improve productivity, employees who were initially trained on older systems or who are new to a higher-tech workplace may struggle to keep up or even resist using the new tech at all.

Giving your team the support they need to learn and leverage new tech is a win-win situation for everyone. Below, 13 members of Forbes Human Resources Council share tips for effectively introducing new tech tools to your team members.

Members of Forbes Human Resources Council share smart strategies to help your employees learn and adopt new technology.
Photos courtesy of the individual members.

1. Take a multi-pronged approach.
Implement a range of training systems, from written instruction to live video training, to accommodate different work styles and preferences. It's important that executives lead by example by using the technology themselves and reminding employees of support and resources available on a regular basis. - Neha Mirchandani, BrightPlan
2. Create a sandbox for employees.
The one important strategy in any major wave of change is the willingness to create a sandbox for the employees. For any new tech-or non-tech-strategy to succeed, an appetite for and acceptance of failures and mistakes are required. People learn when they know their mistakes won't cost them their jobs. They are more open to bigger challenges if there is an allowance for a learning curve. - Ruchi Kulhari, NIIT-Technologies
3. Implement annual skills evaluation.
Annual skills evaluation programs are a great way to keep employees engaged and motivated. Digital transformation requires core competencies for virtually any job to evolve. By evaluating skill levels and skill gaps, your organization can easily identify ways to ensure employees are keeping up with the competition. Employers must constantly update employee skills to match the pace of innovation. - Sameer Penakalapati, CEIPAL Corp.
4. Blend incentives with guidance.
Offer a stipend for technology adoption. Bookend it with some guidance so it is easier to manage across the enterprise-for example, here are the two tools for X, the three for Y, and so on. This ensures there's some consistency in the process. - Megan McCann, McCann Partners
5. Share the 'why' and 'how,' and seek input.
Gather employee input early and often in any major technology change. They will readily adapt to the change when they see why the current platforms aren't serving the needs of the business. Communicate the "why" and the "how" as much as possible to gain accelerated adoption. - Keri Higgins Bigelow, LivingHR, Inc.
6. Provide multiple training options.
For employees to successfully adapt to new technology, we must offer the content in different formats, as everyone learns differently. Additionally, repetition is important. Our strategy includes several tactics, such as both online and in-person training, on-demand how-to videos, skilled employees acting as tutors for other employees, and a help center that is available for questions after the training. - Tobin Cookman, ON Semiconductor

Forbes Human Resources Council is an invitation-only organization for HR executives across all industries. Do I qualify?
7. Encourage self-service training and follow-up questions.
Adopting and adapting to new technology requires repetition. The most effective way to enable this for employees is through self-service training. In addition to the initial live training, create video resources employees can refer to. In addition, ensure it's clear whom the employees should go to with questions, and communicate that those questions are encouraged. - Natalie Rast, stensul
8. Teach employees how to be adaptable.
Organizations should focus less on the technology itself and more on training employees to be more broadly able to adapt to change. Technology will always be changing, and so will our workplaces. Organizations need to focus on helping their people develop the skills to deal successfully with change, become more resilient, unlearn old behaviors and adopt new ones. - Philip Burgess, C Space
9. Pair new users with a mentor.
From a practical standpoint, I am not supportive when learning that new technology is an immediate requirement for successful performance in a role. Working with leaders to structure co-ownership for deliverables with a super-user or mentor is key. Training is often generic, and employees will need help converting knowledge into specific workplace solutions until they can master the technology. - Erin Adkins, Sony Interactive Entertainment
10. Incentivize employees to become 'technology champions.'
Think of out-of-the-box ways for employees to find joy and significance in the adoption. One way is to offer incentives to employees to serve as "technology champions." A technology champion is a promoter of change who learns the new software in depth and serves as a knowledge source for other employees who will learn and utilize the technology as well. - Nakisha Griffin, Virtual Enterprise Architects
11. Create a series of quick how-to videos.
Create access to bite-sized learning opportunities both at the time of launch and on an ongoing basis. These how-to videos should be five minutes at most and easily consumable. Also, continue to push these out to people, especially aligning them with cyclical activities such as pay reviews, compliance training and bonus payouts. Take advantage of opportunities to improve the employee experience. - Paul Phillips, Avanade
12. Leverage fun and experiential learning platforms.
Making it fun and rewarding for employees to learn new technologies is the key to growth and adaptation. Employers should provide access to learning experience platforms that incorporate gaming, the ability to earn badges and micro-credentials, a sandbox environment for practicing as you learn, and so on. New features and functionalities are often incorporated into these platforms, which makes learning fun. - Heide Abelli, Skillsoft
13. Enable employees to take part in managing the change.
Applying a robust change-management strategy to all tech initiatives is extremely helpful. It is more than just communication-you should allow employees to ask questions and have workshops to facilitate the change. Empower employees to provide feedback early and often. Anything that the organization can do to enable employees to be a part of the change is always beneficial. - Susie Long, Bridgestone Americas, Inc.

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Council Post: 13 Practical Ways To Help Employees Adapt To New Technology

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As companies bring on more and newer technology to help improve productivity, employees who were initially trained on older systems or who are new to a higher-tech workplace may struggle to keep up or even resist using the new tech at all.

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I think that the use of AI and Machine Learning in this context seems helpful for companies that are in an employee deficit but have concerns about it replacing employees in companies that aren't in need of workers. This implication of AI almost seems to replace employees by doing the grunt work for them and I could see it taking the jobs of many people. I think that companies will have some decisions to make regarding to their loyalty to their employees and the future of how they want to operate the business. I hope that there is a way to use this technology without jeopardizing the jobs of numerous people around the world.

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This source is a trade source because it comes from someone in the field of corporate finance and is written in a way that uses specialized language while remaining readable for someone outside of the field. This article was also featured on CFO which is a news source for the finance community.

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I think that is very scary that some AI can change override the programmers wishes by coming up with its own plan. The AI can really influence the stock market and can completely control the fate of companies based on its investments. I think that the implication of AI in business needs to be taken very slowly because these risks seem to big to take.

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This is a scholarly source because it is peer reviewed and includes over 70 sources many of which are also scholarly sources. This source also includes specialized language for people in the finance world and was very hard to understand at some points.

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Possible implications of financial AI systems could lead to systemic risks involving herding and "disastrous resonance" for companies. The AI being used could develop it's own trading policies and investment rules that may override those of their programmers and users. The AI may also find certain information such as social media posts and news trends to be more helpful than the information it is programmed to use when making business decisions. "...systemic risks may arise when actors and their AI algorithms start following similar strategies and thus moving markets in the same direction (herd- ing), increasing the risk of severe market disruptions." When multiple companies use the same AI it will cause them to act similarly and try to achieve the same outcomes by doing the same things which will make the market unstable. The AI can also drive the prices of stocks down or up and can ruin relationships between companies and customers.

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Source 6: AI ethics and systemic risks in finance

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Source 6: AI ethics and systemic risks in finance

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By: Ekaterina Svetlova
Source: Original Paper

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This source was a big help in my research of discovering more about the complications with using AI for finance. I thought that there was a lot to unpack about the way Machine Learning can make up biases or generalizations about someone which seem to be irrelevant to their credit score. I believe that this isn't the fault of the AI but perhaps might have been from a gap in the algorithm that is being used for this technology. I think that the coders and engineers involved might have overlooked possible factors that could sway an AI's decision making process and need to spend more time preventing things like this from happening.

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This source is a scholarly source because it includes many outside sources that are focused within the field it discusses. This source is a conference paper that has been peer reviewed and includes specialized language for engineers that are within the AI community.

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The future of business involves AI and there are some concerns about the ethics and transparency of using it. There are some cases of bias when using AI in personal finance including sex, religion, race, marital status, disability, and age which can hinder life altering decisions stemming from credit scores and mortgage lending. Both credit scores and mortgage lending can be decided by Machine Learning which is a form of AI that is used to retain data that it is given and use patterns from this data to make decisions. Although not directly stated in this article, I believe that this form of AI might be making generalizations from the list of biases above and use the data it has been given to make decisions that might not be representative of the user. Some skepticism has risen against Machine Learning in finance because of the lack of transparency for the algorithms being used to make these life altering decisions for people. in the future, when AI is being used to make financial decisions, experts would like to see more transparency in the algorithms being used and for explanations on why the AI makes decisions based on the data it receives.

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Source 5: Artificial Intelligence in Finance: Possibilities and Threats

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Source 5: Artificial Intelligence in Finance: Possibilities and Threats

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By: Opeoluwa Tosin Eluwole, Segun Akande
Source: Conference Paper

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What risks or consequences come from using AI?

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What risks or consequences come from using AI?

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People who hold corporate finance positions at companies that are adapting to the new technology being made using artificial intelligence and machine learning are receiving an elevated role. With these advancements in AI and Machine Learning within finance, the employees will be able to better analyze data within their department to make better decisions for their company. The AI will reduce the amount of mundane manual work so the employees can focus more on improving their company's financial status. The AI can be very helpful for automating tasks such as payments to and from vendors and customers which will ultimately reduce the amount of time it takes for companies to make payments. The Machine Learning can learn about transactions being made through a company and help provide automated digital payments which will allow the employees to focus their time on making improvements to their company in the long run. The AI and Machine Learning will help the finance team make market predictions and forecasts based on the data it collects.

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Source 3: How to Future-Proof and Modernize the Finance Department

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Source 3: How to Future-Proof and Modernize the Finance Department

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By: Cameron White
Source: News Article

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Amidst economic uncertainty and rising costs, organizations are looking for effective ways to ensure their future. And if leaders have learned anything from the challenges of the past few years, it's that agility is often the key to survival.

One of the most effective strategies for creating agility is through digital transformation. According to IDC, companies around the world are projected to spend $1.8 trillion this year on digital transformation, an increase of 17.6% over 2021. These investments are expected to sustain a pace of growth for the next five years, primarily attributed to the benefits of digital transformation efforts, such as resiliency and cost-cutting efficiencies.

As for for organizations considering tech investments to fortify operations and reap the benefits that digital transformation promises to provide, they must keep in mind that the finance department is always in need of modernization.

The benefits of automating paper-based, error-prone financial processes and digitizing financial data extend far beyond the department alone, providing efficiencies and better visibility to help future-proof the entire organization.

Here's a closer look at what's needed for finance teams to reimagine their workflows and how the right technology can provide transformative relief during these troubling times while also helping organizations prepare for whatever lies ahead.

A Reimagined Finance Department

The pandemic kick-started a long-overdue modernization of the finance department, compelling organizations to adopt cloud-based technologies and automation to free up their teams from paper dependencies, as well as better enable them for remote work.

Today, an unrelenting labor shortage and a volatile economy intensify the need for modernization. Under-staffed and often overworked, finance staff are under intense pressure to manage their organization's cash flow and keep a watchful eye on an unpredictable future. They can't afford antiquated workflows such as entering invoice data, chasing approvals, and mailing paper checks to slow them down or drain their budget.

Many finance professionals have come to expect automated workflows and may look elsewhere if organizations are digital laggards.

According to Workday's CFO Indicator Survey, finance leaders are automating manual tasks, adopting machine learning (ML), and creating data-driven strategies to face future challenges. Furthermore, the report shows that nearly 60% of CFOs are investing in the cloud and deploying artificial intelligence (AI) and ML solutions.

Technology reduces friction by automating tasks around processing invoices and making payments, which can save significant time and money while freeing teams for more strategic work when their organizations need them most.

Teams who haven't already started to automate costly manual processes may be looking at end-to-end invoice solutions that offer e-payments in lieu of costly and fraud-prone paper checks. As organizations fight to hold onto talent and attract new hires, many finance professionals have come to expect automated workflows and may look elsewhere if organizations are digital laggards.

Elevating the Finance Team's Role

Part of the allure of a modernized finance department is that automation technology not only streamlines mission-critical processes and reduces mundane manual work, but also elevates the role of the department. It does this by providing newfound visibility into data, which is especially valuable to organizations as they fight to manage cash flow and mitigate risks.

Advanced technologies including AI and ML empower finance professionals to better analyze the wealth of data within their department and wean valuable insights from it to make better decisions for the business. For instance, they can detect behavioral patterns of vendor payments and invoices to predict the likelihood of those behaviors continuing. Based on those insights, they can then make necessary fixes, such as offering a vendor a more convenient, faster e-payment option. The fix ultimately protects the organization's bottom line while nurturing and strengthening a valuable relationship to ensure future business.

Technology also empowers the finance team to make market predictions, forecast future spending increases or decreases, and detect the statistical probability of invoice anomalies and fraudulent checks. This helps the organization manage risks, better budget, and create more accurate financial forecasts.

Future of Digital Transformation

While the future remains unpredictable, it's clear that change is inevitable, and preparing for evolving circumstances is paramount to both success and survival. Organizations can better prepare for what lies ahead by ensuring their finance teams have the tools and support they need to act as strategic business partners.

Innovation promises to create efficiencies, free the finance team from higher-level work, and empower them to guide important decisions that can protect the business and drive bottom-line results.

Cameron White is senior vice president of finance at AvidXchange.

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How to Future-Proof and Modernize the Finance Department

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Amidst economic uncertainty and rising costs, organizations are looking for effective ways to ensure their future. And if leaders have learned anything from the challenges of the past few years, it's that agility is often the key to survival. One of the most effective strategies for creating agility is through digital transformation.

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How are Corporate Finance employees being forced to adjust to the new technology being used?

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How are Corporate Finance employees being forced to adjust to the new technology being used?

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In what ways is artificial intelligence being used in finance?

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In what ways is artificial intelligence being used in finance?