Introduction:
The evolution of technology has brought about ease of operation to all sectors. Such that goods and services are now produced with speed of operation. For example, how long it takes to communicate using letters compared to the wireless calls that we have today, business transactions can go on easily from miles, thanks to technology. Among the many evolutions of technology today, a recent innovation is the rise of Artificial Intelligence (AI).
What is Artificial Intelligence(AI)?
Artificial Intelligence, commonly known as AI, refers to the imitation of human intelligence in machines, enabling them to perform tasks that require human intelligence. In other words, AI is a photocopy of human intelligence. AI was created to assist humans with their tasks, not to replace them. A man known as FEL-FEL-HI once said that “Artificial Intelligence is not a substitute for human intelligence; it is a tool to amplify human creativity and ingenuity.”
AI steps out of its place when it tries to replace humans because its intelligence is not self-sufficient but a compilation of human contributions to it. Can AI perform some human tasks? Yes, it can. But because its intelligence originated from humans, the tasks it can perform are quite limited. When it comes to rendering services to prospective customers and clients, AI cannot perform the following:
1. AI cannot show empathy: When dealing with clients, AI cannot connect with people on an emotional level. Beyond performing tasks and production, AI cannot relate with humans by understanding how they feel and give sensitive responses. For example, a client who is about to pay for a service but experiences an emergency that takes away the funds. In this case, AI, based on its imputed data, cannot show empathy and understand what it feels like to be in this kind of situation, but humans can if they choose to.
2. AI also lacks emotional intelligence because it does not have emotions in the first place. This shows in the content it produces, which is why AI is better at assisting humans with performing their tasks. Humans can leverage AI by prompting it, and with AI’s assistance, humans can be more productive and efficient.
3. AI lacks human creativity: AI itself is a result of the creativity of humans; everything it knows was imputed by humans, and everything it knows will be imputed by humans too.
Types of AI
Basically, there are two types of AI: AI based on capabilities and AI based on functionalities. Under these two, we have classifications:
AI based on capabilities:
- Narrow AI (ANI): Built to perform specific tasks, with knowledge restricted to a narrow domain. These types of AI are also known as weak AI because of their limitation to one task. Examples include self-driving cars and AI-powered virtual assistants such as Siri, Alexa, and Google Assistant.
- Artificial General Intelligence (AGI): Also called Strong AI, this refers to a theoretical form of AI capable of learning, thinking, and performing tasks at a human level. Its goal is to develop versatile, human-like intelligence adaptable across multiple fields. This type of AI does not exist yet, but researchers are working on bringing it to life.
- Artificial Superintelligence (ASI): A hypothetical stage where AI surpasses human intelligence and capabilities. While still science fiction, ASI is often linked to concerns about AI dominance. This type of AI has only been displayed in fictional movies like Iron Man (Jarvis and Ultron).
AI based on functionalities
- Reactive Machine AI: Systems that respond to stimuli in real time but cannot store memory or learn from past experiences. These are the oldest types of AI. Examples include IBM’s Deep Blue chess computer and recommendation engines like Netflix.
- Limited Memory AI: These systems can temporarily store and use past data to make decisions or predictions. Common applications include chatbots, self-driving vehicles like Tesla and ChatGPT.
- Theory of Mind AI: Still in development, this form of AI would be able to understand and respond to human emotions while performing the functions of limited memory AI.
- Self-Aware AI: A hypothetical stage where AI achieves human-level intelligence and develops self-awareness, often referred to as the “singularity.” This type of AI is still science fiction displayed in movies like Terminator.
Some Myths about AI
Myth 1: AI algorithms can magically make sense of messy data.
Reality: AI is not “load and go.” The quality of data is more important than the algorithm itself. Poor data inevitably produces poor results, regardless of the sophistication of the model.
Myth 2: Businesses need data scientists, machine learning experts, and huge budgets to use AI.
Reality: Many AI tools are now accessible without requiring Google-sized investments. Organisations can leverage prebuilt applications from leading providers and start-ups at reasonable costs.
Myth 3: “Cognitive AI” can solve problems the way the human brain can.
Reality: Cognitive technologies can only solve problems for which they were specifically designed. General AI (true human-like intelligence) remains theoretical.
Myth 4: Neural networks mean computers learn like humans.
Reality: Neural networks are powerful but nowhere near replicating the complexity of the human brain. Their effectiveness is limited to the scope they were trained on.
Myth 5: AI will replace humans and make jobs obsolete.
Reality: Like past technological shifts, AI enhances human capabilities and creates new roles. For example, in customer service, AI augments operations through call routing, training customisation, and fraud detection , but people remain essential.
How AI Supports the Finance Industry
According to NVIDIA, 91% of financial services companies are already using or actively assessing AI. The technology is transforming banking, insurance, and financial services by enhancing efficiency, compliance, and decision-making.
Key areas include:
- Identifying Trends and Patterns: AI-powered predictive analysis uses historical data to forecast outcomes and uncover hidden correlations, giving professionals insights for better decision-making.
- Data Analysis: AI can process vast amounts of information in real time. Data analysis, like automated financial services, predictive analytics, sentiment analysis etc. With these analyses, finance professionals can forecast revenue, cash flow, analyse market news and investor sentiment, and improve data processes better than manual methods.
- Client Service: Chatbots and virtual assistants, like advisory services to client needs, analyse behaviour to product offering, and improve client interactions.
- Compliance: AI continuously monitors transactions and activities, flagging potential violations faster and more accurately than manual reviews.
- Portfolio Optimisation: Automated investment platforms use AI to analyse client risk profiles and recommend optimised portfolios.
- Risk Management: AI helps advisers detect potential risks, identify misalignments in portfolios, and recommend timely adjustments.
Case in Point: ICL Reconciliator by ICL, Iwelabi Consulting Ltd
AI is not designed to take over the roles of finance professionals but to empower them with better tools. A clear example is the ICL Reconciliator by Iwelabi Consulting.
This solution leverages AI-driven matching algorithms to automate reconciliation processes that would otherwise require hours of manual effort. It can:
- Match transactions intelligently (one-to-one, one-to-many, and many-to-one).
- Detects anomalies, duplicates, and inconsistencies in records.
- Handle fuzzy matching where references or narrations differ.
- Integrate seamlessly with Excel and existing finance systems.
- Deliver results without storing sensitive financial data, ensuring privacy.
Instead of replacing finance professionals, ICL Reconciliator reduces repetitive manual work, allowing experts to focus on strategic analysis, compliance, and client trust-building.
What inspired the ICL Reconciliator?
Reconciliation is one of the biggest pain points in finance and accounting operations. It is often a tedious and time-consuming task that takes valuable time away from more strategic work. The ICL Reconciliator was created to address this challenge, making reconciliation faster, simpler, and more reliable. Automating and streamlining the process empowers finance teams to focus on higher-value tasks. It is also our flagship product, the first step on our broader product roadmap. The long-term vision is to build an ecosystem of solutions that will support different aspects of finance and accounting operations.
What makes the ICL Reconciliator exceptional?
The ICL Reconciliator stands out for three main reasons:
- Simplicity: It is extremely user-friendly, designed with a clean interface that avoids unnecessary complexity.
- Versatility: It goes beyond bank reconciliations; it can be applied to multiple use cases such as ledger, payables, receivables, or any dataset that involves components like date, amount, and description.
- Deep Insight: It doesn’t just reconcile, it also provides detailed visibility into the condition of your data from one-to-one matches to one-to-many matches, and beyond.
Together, these qualities make the ICL Reconciliator a practical yet powerful tool for tackling one of the most persistent challenges in accounting and finance.
Conclusion: AI as a Co-Pilot, Not a Replacement
Artificial Intelligence should not be viewed as a threat to jobs, but as a co-pilot that enhances accuracy, productivity, and efficiency. Finance professionals remain central; interpreting results, applying judgment, and making strategic decisions while AI handles repetitive and data-heavy tasks.
The future of finance lies in human expertise powered by AI tools like ICL Reconciliator. Together, they form a partnership that drives growth, innovation, and trust in an increasingly digital world.
REFERENCES:
AI for Finance: Top AI Tools for a Finance Professional https://corporatefinanceinstitute.com/resources/career/ai-tools-for-a-finance-professional/
How Can AI Help Financial Advisers?
https://www.investopedia.com/how-can-ai-help-financial-advisors-8385520
Myth vs Reality in Artificial Intelligence
https://www.earley.com/insights/myth-vs-reality-artificial-intelligence
Five Myths About Artificial Intelligence https://www.ttec.com/articles/five-myths-about-artificial-intelligence
7 Types of Artificial Intelligence https://builtin.com/artificial-intelligence/types-of-artificial-intelligence
Types of AI Explained https://www.simplilearn.com/tutorials/artificial-intelligence-tutorial/types-of-artificial-intelligence
