AI in Finance Guide: Benefits, Applications, Future of AI & How Application of AI is Transforming Finance Industry [2024]

In today's rapidly evolving financial landscape, the integration of cutting-edge technology has become not just a luxury, but a necessity for those seeking to thrive in an increasingly competitive industry. Artificial Intelligence (AI) in finance, often referred to as AI & Machine Learning (ML) in the finance industry, is at the forefront of this technological revolution. This comprehensive guide delves into the remarkable impact of Artificial Intelligence in financial sector, its numerous benefits, the myriad of applications it offers, and the promising future it holds.

A recent report by Gartner outlines a clear roadmap for the finance industry's adoption of AI. By 2025, 70% of organizations are projected to integrate AI-related technologies into their processes. The report also anticipates that by 2027, a substantial 90% of financial analytics will be fully automated, and by 2028, 50% of organizations will have shifted to AI-driven forecasting approaches. These predictions emphasize the growing significance of AI in reshaping finance.

In this comprehensive guide, we'll delve into the exciting realm of AI in finance. We'll explore its benefits and applications, examine real-world examples from leading financial firms, discuss how AI is transforming the industry as a whole, envision its promising future role in accounting and financial planning, and even uncover new career opportunities that arise from embracing this cutting-edge technology.

What Is AI in Finance?

Artificial Intelligence (AI) in finance represents a paradigm shift, fundamentally altering the landscape of financial services. The role of AI in finance is to employ cutting-edge technologies to automate and optimize financial processes, leading to more informed decision-making in lending, investing, and risk management.

Artificial Intelligence, often abbreviated as AI, is the simulation of human intelligence processes by machines, particularly computer systems. These processes encompass tasks such as learning, reasoning, problem-solving, understanding natural language, and perceiving the environment. In finance, AI is leveraged to automate and enhance various aspects of the industry, enabling financial institutions to make more informed decisions and improve customer experiences.

PwC's Global AI in Finance Survey 2023 found that 80% of financial services organizations believe that AI will give them a competitive edge over their peers. The report also found that AI is already being used in a variety of financial services applications, including fraud detection, risk assessment, and investment management.

What Is Machine Learning (ML) in Finance?

Machine Learning (ML) is a subset of AI that focuses on the development of algorithms and statistical models to enable computer systems to improve their performance on a specific task through experience, without being explicitly programmed. In finance, ML algorithms are used to analyze large datasets, identify patterns, and make predictions. They play a crucial role in personalized banking, risk assessment, and algorithmic trading, among other applications, offering efficiency and accuracy.

IBM's AI in Finance 2023 Report found that MI is being used to automate tasks, improve decision-making, and create new products and services in the financial services industry. The report also found that MI is helping financial institutions comply with regulations and reduce risk.

What Is ERP Finance?

ERP, or Enterprise Resource Planning, refers to the integration of various financial processes and functions within an organization into a unified software system. ERP systems are instrumental in managing financial data, including accounts payable, accounts receivable, payroll, and financial reporting. In the context of AI in finance, ERP systems can be enhanced with AI and ML capabilities to streamline and automate financial operations, providing a comprehensive solution for financial management.

Gartner's Magic Quadrant for Cloud ERP for Finance 2023 found that Workday, Oracle, SAP, and Microsoft are the leading providers of cloud ERP finance solutions in the USA. The report also found that cloud ERP finance is becoming increasingly popular, as it offers several advantages over on-premise solutions, such as lower costs, easier scalability, and faster time to value.

What are the Benefits of AI in Finance?

Artificial Intelligence (AI) is revolutionizing the finance industry, bringing forth a multitude of advantages that redefine the way financial institutions operate. Let's delve into the top 10 benefits of AI in Finance in 2024:

1. Automation - Pioneering Efficiency

AI in finance can automate many of the repetitive and time-consuming tasks that are currently performed by humans in the industry. This includes tasks such as accounting, budgeting, and forecasting. This can free up human employees to focus on more strategic and value-added activities. A report by McKinsey found that AI could automate up to 50% of all financial services tasks and generate $1.2 trillion in value for the industry by 2025.

2. Accuracy - Precision Beyond Measure

AI can help financial institutions to make better decisions by analyzing vast datasets with unfaltering consistency. This precision is particularly vital in risk assessment, investment forecasting, and fraud detection, where minor discrepancies can lead to major consequences. A report by IBM found that Artificial intelligence in finance is helping financial institutions improve their fraud detection accuracy by up to 30%.

3. Efficiency - Streamlining Operations

AI in finance optimizes processes, streamlining everything from customer service in banking and finance to compliance management. This not only trims operational costs but also ensures a seamless and responsive experience for both clients and financial institutions. A report by PwC found that AI is helping financial institutions to reduce their costs by up to 20%.

4. Speed - Real-Time Decision-Making

AI doesn't just operate efficiently; it does so at lightning speed. In the world of finance, where time is money, AI is indispensable. It powers real-time decision-making in areas like algorithmic trading, enabling financial institutions to capitalize on opportunities that may elude human traders. A report by Gartner found that AI is helping financial institutions reduce their decision-making time by up to 50%.

5. Availability - 24/7 Service Delivery

AI knows no rest; it's available around the clock. This 24/7 availability is a game-changer for customer service in the finance industry. AI-powered chatbots and virtual assistants are always ready to assist, ensuring customers receive support and information whenever they need it. A report by Forrester found that 70% of financial institutions are planning to implement AI-powered chatbots in the next year.

6. Innovation - Pioneering the Future

AI is driving innovation in the finance industry by leading to the development of new products and services. For example, AI-powered investment platforms can help investors to make more informed investment decisions. A report by Accenture found that AI is expected to generate $1.2 trillion in value for the financial services industry by 2025.

7. Personalization - Tailored Financial Solutions

AI's ability to analyze vast customer data empowers financial institutions to provide personalized recommendations for banking products and investment strategies. Customers receive tailored solutions that cater to their unique financial goals and preferences. A report by Celent found that 75% of financial institutions are using AI to personalize their customer experiences.

8. Scalability - Adapting to Growth

AI systems are inherently scalable, making them well-suited for financial institutions experiencing growth. Whether an institution is managing a small portfolio or handling an extensive client base, AI can seamlessly adapt to meet increasing demands. A report by Deloitte found that AI is helping financial institutions to grow their businesses faster.

9. Risk Mitigation - Early Threat Detection

AI's advanced analytics and pattern recognition capabilities allow for early threat detection in risk management. By identifying potential risks before they escalate, financial institutions can take proactive measures to safeguard their assets and minimize losses. A report by IBM found that AI is helping financial institutions reduce their fraud losses by up to 30%.

10. Regulatory Compliance - Navigating the Legal Landscape

AI assists financial institutions in staying compliant with evolving regulations. By monitoring changes in regulatory frameworks and evaluating an institution's practices, AI ensures that financial operations are conducted within the bounds of the law, reducing the risk of legal issues and penalties. A report by KPMG found that 70% of financial institutions are using AI to improve their regulatory compliance.

Future of AI & ML in Finance Industry in 2024

AI is catalyzing a revolution in the finance industry, with tangible transformations evident across various facets. From automating routine tasks to enhancing decision-making, the impact of AI & ML in finance industry is profound. Financial institutions are increasingly leveraging AI to automate customer service, data entry, and risk assessment, allowing human employees to focus on more strategic endeavours.

AI's influence extends to empowering financial institutions with more accurate and timely information. AI-powered models assist in assessing borrower creditworthiness, predicting fraud risks, and forecasting market trends. Additionally, AI is a formidable weapon in the battle against risk. It aids in identifying and mitigating potential threats, including the detection of fraudulent transactions and cyberattacks.

Customer service in finance is undergoing a profound transformation through AI. AI-powered enterprise chatbots provide round-the-clock support and deliver personalized financial advice. The future of finance is shaped by AI, with expectations of greater efficiency, accuracy, security, and personalization. As the graph showcasing the projected growth of AI & ML in finance industry reveals, the AI market in finance is poised to surge from $2.3 billion in 2021 to an estimated $22.6 billion by 2027, driven by factors such as data availability, cost reduction needs, risk mitigation, and heightened competition. AI is ushering in a new era of financial innovation.

Top 10 Applications of AI & ML in Finance Industry in 2024

The integration of Artificial Intelligence (AI) in finance, often referred to as AI in Finance, is reshaping the industry and redefining how financial processes and services are delivered. This innovation spans a wide array of applications, leveraging AI's capabilities to enhance efficiency, accuracy, and customer experiences to integrate conversational AI in BFSI. Let's explore the diverse applications of Artificial Intelligence in finance sector in 2024:

1. Sentiment Analysis - Market Insight at Your Fingertips

AI's sentiment analysis tools scrutinize vast amounts of data, including social media and news, to gauge market sentiment. This provides valuable insights for investment strategies and risk assessment in real-time. AI-powered sentiment analysis tools can be used to identify emerging trends in the financial markets, such as changes in consumer sentiment or investor confidence. This information can then be used to inform investment decisions and reduce risk.

2. Recommendations - Personalizing Financial Services

AI leverages customer data to offer personalized product and investment recommendations. This level of personalization enhances customer satisfaction and drives engagement. AI-powered financial advisors can analyze a customer's financial situation, risk tolerance, and investment goals to provide personalized recommendations. This can help customers to make more informed financial decisions and reach their financial goals faster.

3. Translation - Breaking Language Barriers

In a globalized financial world, AI-powered translation services facilitate communication and understanding across multiple languages, ensuring that financial information is accessible and comprehensible worldwide. AI-powered translation services can be used to translate financial documents, such as investment prospectuses and research reports, into multiple languages. This makes it easier for global investors to access and understand financial information from around the world.

4. Document Processing - Streamlining Operations

AI automated document processing tasks, such as data extraction and validation, making administrative processes more efficient and less prone to errors. AI-powered document processing solutions can be used to automate the processing of loan applications, insurance claims, and other financial documents. This can free up financial institution employees to focus on more strategic tasks.‍

5. Data Science and Analytics - Informed Decision-Making 

AI-driven data science and analytics provide powerful tools for investment strategies, risk assessment, and financial modelling. These insights empower financial institutions to make data-driven decisions. AI-powered data science and analytics solutions can be used to identify investment trends, assess risk, and develop financial models. This information can then be used to make informed investment decisions and reduce risk.

6. Predictive Modeling - Forecasting Market Trends 

AI's predictive modelling capabilities analyze historical data to forecast market trends, enabling informed investment decisions. AI-powered predictive modelling solutions can be used to forecast stock prices, exchange rates, and other financial market trends. This information can then be used to make informed investment decisions.

7. Cybersecurity - Safeguarding Financial Data

AI plays a critical role in cybersecurity by detecting and mitigating potential threats. This proactive approach safeguards financial data and customer information. AI-powered cybersecurity solutions can be used to detect and prevent fraud, data breaches, and other cyberattacks. This helps to protect financial institutions and customers from financial losses and reputational damage.

8. Generative AI - Creating Financial Reports, Portfolios 

Generative AI is employed to create financial reports, market summaries, and investment portfolios, offering a more efficient way to generate financial artefacts. AI-powered generative AI solutions can be used to create financial reports, such as balance sheets and income statements, in real-time. This can help financial institutions to save time and improve efficiency.

9 Fraud Detection & Prevention - Safeguarding Financial Transactions

AI's advanced algorithms are employed for the detection and prevention of fraudulent transactions, protecting both financial institutions and clients. AI-powered fraud detection systems can analyze large amounts of data, including transaction data, customer data, and device data, to identify patterns and anomalies that may indicate fraudulent activity. These systems can also be used to develop predictive models that can identify potential fraudsters before they commit a crime.

10. Customer Relationship Management - Enhancing Client Engagement 

AI-driven CRM systems manage and analyze customer data, improving client engagement and retention. AI-powered CRM systems can be used to identify customer needs and preferences, track customer interactions, and personalize customer experiences. This can help financial institutions to improve customer satisfaction and loyalty.

To know more about use cases of conversational, read our blog on conversational AI examples & use cases.

6 Companies Using AI in Finance in 2024

Below listed are some top companies using AI in finance.

1. App0

App0 is an AI concierge for financial services. AI concierge enables financial services to acquire more customers, close deals faster and provide excellent customer support. The AI concierge helps your customers to start, navigate, and complete applications on any channel to drive more conversion via full-service text messaging.

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2. Upstart

Upstart is a fintech company that uses AI to assess the creditworthiness of borrowers. Upstart's AI model considers a wider range of factors than traditional credit scoring models, such as education, employment history, and cash flow. This allows Upstart to approve more borrowers and offer lower interest rates.

3. Plaid

Plaid is a fintech company that provides a platform for financial institutions to connect with third-party apps. Plaid's AI technology helps to verify users' identities and securely share their financial data with third-party apps. This allows users to easily connect their bank accounts to budgeting apps, investment apps, and other financial services.

4. Kensho

Kensho is a financial technology company that uses AI to help financial professionals make better investment decisions. Kensho's AI platform analyzes vast amounts of data, including news articles, financial reports, and social media posts, to identify patterns and trends. This information can then be used to develop investment strategies and make informed investment decisions.

5. AlphaSense

AlphaSense is a financial technology company that provides a search engine for financial professionals. AlphaSense's AI technology indexes and analyzes millions of financial documents, including SEC filings, research reports, and analyst notes. This allows financial professionals to quickly and easily find the information they need to make informed investment decisions.

6. Socure

Socure is a financial technology company that provides identity verification and fraud detection solutions. Socure's AI technology analyzes a variety of data points, including name, date of birth, Social Security number, and address, to verify a user's identity and detect fraudulent activity. This helps financial institutions to protect their customers from fraud and comply with regulatory requirements.

Future of AI in Finance

The future of AI in finance is poised for significant transformation, offering numerous opportunities and challenges. AI-driven algorithms will continue to shape trading strategies, becoming more adaptive and sophisticated. Risk management will benefit from AI's ability to analyze vast datasets, providing financial institutions with improved tools for risk assessment and fraud detection. AI will also enhance customer service through chatbots and virtual assistants, creating more personalized and efficient interactions.

AI's role in credit scoring will expand, enabling fairer assessments of creditworthiness and broader access to credit. It will empower individuals with personalized financial planning and investment advice, democratizing access to these services. Additionally, AI will play a pivotal role in regulatory compliance, helping institutions navigate complex and evolving regulations.

As AI continues to evolve, the industry will need to address ethical concerns, data privacy, and security. The rise of quantum computing and the ongoing development of blockchain technology will introduce new possibilities and challenges. In this dynamic landscape, collaboration and partnerships between financial institutions and tech companies will be crucial for leveraging the full potential of Artificial Intelligence in finance, ensuring that it remains a driver of innovation and efficiency while navigating the complexities of a rapidly changing financial world.

Conclusion

In the ever-evolving financial landscape, the integration of Artificial Intelligence (AI) is no longer a choice but an imperative. Our exploration of the Artificial Intelligence in Finance Guide has unveiled a world of benefits and applications, showcasing the boundless potential AI holds for the financial realm in 2024 and beyond.

From AI-powered chatbots revolutionizing customer service to machine learning bolstering risk management, AI's advantages in finance are undeniably transformative. It streamlines operations, enhances precision, and introduces tailored solutions, elevating the industry's operational prowess. As we cast our gaze toward the future, AI's profound influence on risk management, regulatory compliance, and customer engagement is set to reshape finance. The projected AI market growth at a compound annual rate of 56.2% reaffirms its indispensable role in finance. AI is no longer merely the future; it is the dynamic force shaping the financial landscape today and well into the future.

If you're looking forward to powering your financial services using conversational AI, we suggest you check out App0.

App0 is a no-code, AI-powered messaging platform that transforms every text notification into a two-way conversation, enabling financial services companies to accelerate their origination timelines, reduce application drop-off, and enhance CX by engaging through text messages.

Operations and origination leaders from equipment finance and other financial services companies have re-iterated on experiencing a few critical problems during originating deals, especially in dealer/vendor-led programs like:

• Communication predominantly happens over the phone and email during the application and underwriting process.
• Collecting sensitive information from end users (lessees), such as SSNs, gets complex and delayed when a personal guarantor is needed.
• Collecting one-off documents such as ID proofs, W2s, etc., during the origination process is time-consuming.

If you are interested in learning more about how App0 can be used, please request a demo. Our team of experts will be happy to show you how App0 can help you streamline your operations, improve customer service, and grow your business.

AI in Finance: FAQs