Artificial Intelligence is already on the path of becoming a part of our daily lives, and in the working world, it has brought about a complete transformation in the way things are done. Different industries are using AI to write marketing copy, answer customers’ queries and perform administrative or operational tasks.
AI is designed to vastly improve human talents and contributions, making it a very valuable commercial asset in any sector. And the financial sector is no exception. According to Business Insider, artificial intelligence technologies would save banks and financial organizations $447 billion in 2023. Furthermore, it was recently stated by Forbes that approximately 70% of all financial services organizations are currently using machine learning to estimate cash flow patterns, fine-tune credit ratings, and detect fraud.
The CEO of a boutique financial consulting firm, Leshinsky Finance, where they have experimented with AI as well and was happy to find out just how much it can simplify processes and procedures, automate mundane jobs, and enhance customer service. Implementing AI tools and technologies have significant advantages such as time savings, cost savings, and the flexibility to scale.
Simplifying Processes and Procedures
AI aids in task streamlining and consolidation. Streamlining systems and procedures can help financial industry stakeholders make better investment decisions and capitalize on volatile markets.
The following are some significant financial responsibilities that AI can optimize:
- Loan Risk Evaluation and Risk Management:
Banks and investment organizations can employ considerable automation and near-real-time customer data analysis to make timely lending decisions by assessing loan risks utilizing structured and unstructured data obtained from several known sources. They can also make inexpensive credit available to so-called “credit invisibles” by relying on alternative data sources such as education, job, property ownership, address stability, rent payment history, Internet browser history, and even behavioral information. Companies may also use AI and ML models to automate loan approval procedures and loan pricing.
- Detection, management, and prevention of fraud:
By analyzing vast volumes of data, AI solutions in the finance sector may do everything from recognise unusual transactions to pinpoint questionable and potentially fraudulent activity. Moreover, AI and cognitive ML models can reduce the possibility of false positives and improve with time at stopping all types of cyberattacks. The possibility of fraud may also be predicted by sophisticated AI algorithms.
- Credit determinations:
Artificial intelligence and machine learning are used to give superior financial analytics and credit scoring. This can save several financial institutions untenable scenarios such as defaulters and deadbeat beneficiaries.
- Decisions on Financial Advisory:
An unsupervised machine learning algorithm that runs in the background on a platform for managing personal finances is known as a robo-advisor. Using survey results, the adviser maintains an investor’s account and executes transactions on their behalf. By eliminating time-consuming processes like rebalancing and verifying correct asset allocation, utilizing robo-advisory is more time- and money-efficient than using a traditional advisor. It also offers possibilities that traditional analysis may otherwise miss.
- Algorithmic Trading:
Technical analysis is based entirely on statistical data, market behavior, and historical relationships. AI can deliver consistent and accurate output in market pattern identification, risk management, and general trading in fast-moving markets. The advantages of algorithmic trading include increased accuracy and less human error, improved trading execution by removing payment trigger delays and examining several market situations automatically and concurrently. AI has been used for not just price prediction but also decision-making and risk management tools.
Automating Mundane Jobs
One of the biggest advantages of AI is its capacity to automate regular operations, including data extraction, balance sheet analysis, and reviewing forms, applications, and documentation. AI can completely do away with the need for human involvement by automating repetitive chores. Enhancing data insights and automating repetitive operations enable firms to free up time to concentrate more on high-level, strategy-oriented choices that have a direct impact on the business.
Currently, teams are performing excessive amounts of manual labor in their respective departments instead of innovating and making critical decisions. By utilizing AI, one can streamline workflows, save costs, and lighten the workload.
Enhancing Customer Service
AI has already made significant strides in improving the vital tenets of good customer care in the banking and finance industry with the help of granular-level Personalized banking and providing 24/7 customer assistance.
The need to wait on hold for a customer care agent on the phone has been minimized (and in some cases eliminated) thanks to chatbots and virtual assistants. Users can now check their balance, arrange payments, look into account activity, ask questions of a virtual assistant, and get tailored banking advice whenever it’s most convenient owing to technology and AI.
Customers don’t have to wait to talk with someone and may ask inquiries round-the-clock, and lesser time and effort is spent, as a result, on routine customer inquiries, allowing teams the freedom to problem-solve more complex or unique issues.
Other applications and benefits of financial automation include efficiency gains, higher ROI levels, and quantifiable outputs.
OCR, Transactional Bots, Artificial Neural Networks, RPA, Robo advisors, and Cognitive computing are emerging AI technologies and tools for financial automation that will combine a variety of specialized jobs and decrease the need for many human participants in those positions. By providing quicker analysis/insights, narrative/statutory reporting, increased staff productivity, financial statement preparation and auditing, and effective financial close, it is positioned to become a productivity powerhouse.
Moreover, it will deliver accuracy at previously unheard-of rates by reducing human error and enhancing forecasting, planning, and modeling.
Banks are finding that in order to stay competitive, they must now widely implement these technologies. According to recent surveys, 87% of company executives say that firms that don’t rethink their financial procedures run the danger of falling behind their rivals, producing erroneous reports, and having staff productivity suffer. Late-stage adopters also face the danger of becoming less appealing to the next generation of financial professionals and customers as Gen-Zs have greater criteria for digital proficiency.
Financial consultancy firms and top organizational officers like the CFO will need to have a deep understanding of AI in near future. Only when clever, multi-layered AI implementation is done can the bottom line be improved. While many are panicked over the advent of AI and the potential career risks that are perceived to bring about, what we have come to realize is that far from threatening livelihoods, AI-enabled corporate finance relies on a balanced mix of judgements made by humans and machines. It is more likely to transform or restructure existing organizational roles and prerequisite skill sets.
Developing greater expertise in the creation, testing, and use of AI technologies will be crucial for all financial institutions. Hence, to future proof your company’s success, it is best to adopt early and gain the necessary edge over your contemporaries.