ARTIFICIAL INTELLIGENCE – THE NEXT DISRUPTOR IN FINANCE WORLD

Whilst the origin of AI can be traced over fifty years back, its possibilities have significantly risen in recent times in today's world. This has spurred development of varieties of practical applications in financial sector and other areas of specialization.

AI is a wide term that relates to advancements that make machines "intelligent" and the term AI was coined by John McCarthy in 1956. There are many different terms that relate to AI, for example, deep learning, machine learning, image recognition, natural language processing (NLP), cognitive computing, cognitive augmentation, machine augmented intelligence, and augmented intelligence.

Broadly, there are two ways AI operates, one is symbolic based, and the other is data based. For data based machine leaning, the machine is first fed with lots of data before it can learn by itself. For instance, machine can search for high dimensional data and determine patterns and develop a model which it then uses to create forecasts in a way that is more precise than what humans can do.

The capabilities of AI are diverse and includes reasoning, knowledge representation, planning, learning, natural Language processing, perception and the ability to move and manipulate items. One of the long term objective of AI is development of general intelligence which utilises many approaches including statistical methods, machine intelligence and symbolic AI. There are many tools that use AI to efficiently deliver results. They include, search engine optimization, artificial neural networks, statistics applications, probability models and economic models. The field of AI utilizes various disciplines including information technology, mathematics, linguistics, psychology, philosophy as well as many other areas.

Researchers in the fields of statistics and computing have created advanced techniques for obtaining insights from large data sets that are disparate. Nevertheless, on the whole, data can broadly be categorized as structured or unstructured data. With these techniques, it becomes possible to leverage the capacity of machines to accomplish certain tasks like natural language processing and image recognition by experiential learning. The application of cognitive tools to perform duties that traditionally involve human sophistication is widely referred to as AI as was analyzed by Financial Stability Board in 2017.

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The other fields that AI is rapidly growing are in healthcare and financial reporting. In healthcare for instance, AI is being tested and used for dosing medicines and carrying out various treatments on patients and performing surgeries. In financial sector, AI is being used to identify and mark unusual banking and finance activities, such as uncommon use of debit cards and big account deposits, which can assist a bank's fraud unit in flagging out unusual transactions. Applications of AI are also being used to simplify and facilitate trading. This is achieved by facilitating the estimation of production, request and price of stocks.

In spite of the point that AI is without a doubt multifaceted, there are broadly four main categories of AI, they include, reactive machines, restricted memory, mind theory, and self-awareness. These four categories then evolve to smaller aspects of the general domain of AI.

Reactive machines category is fundamentally unique because they do not store 'memories' or use past encounters to decide future activities. They basically look at the world and respond to it. IBM's Deep Blue, which won against chess grandmaster Kasporov, is an example reactive machine that sees the pawns on a chess board and responds to them. It cannot allude to any of its prior experiences and cannot improve with training. Another example is Google Al-phaGo which won against human Go champion (Ray 2018.)

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Limited memory category on the other hand consists of a machine learning designs that draw understanding from information, stored data or activities that have already been learnt. Unlike reactive machines, restricted memory learns from the past by watching activities or information that have been given to it in order to create experience. Almost all apps we know of are in this AI class. Limited memory computers can maintain information for a brief time period. Many vehicles, chat bots and digital private assistants use Limited Memory technology. (Reynoso 2019.)

Theory of mind category of AI has the capability to understand thoughts and emotions which affect the human behavior. This type of AI can comprehend feelings, motives, intentions, expectations and can also interact socially. An example is Sophia, a humanoid robot invented by Hanson Robotics. (Yaninen 2017.)

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Self-aware machine category can make depictions about itself. They are conscious of their inner states, can fore-cast the emotions of others, and can produce abstractions and inferences. They are the future generation of machines: super intelligent, sentiment and conscious. The question whether a device can really be self-conscious or "aware" is better to leave for philosophers. (Yaninen 2017.)

The Fourth Industrial Revolution “present to us changes to the way we live, go to work and relate to each other due to the implementation of cyber-physical systems, Internet of Things and the Internet of Systems.” In near future individuals will be able to identify and design personalized products and facilities that they get from industries, transport, banking, investment and insurance. Technology will probably be implemented across all governmental organizations and legal systems with just the most complicated cases being a human judge and complete trial cases. Further, Autonomous vehicles will begin showing up in many urban areas over the world. (Aguis 2019.)

The AI Disruption

AI is currently utilized in different fields including financial and health sector. The sort and type of AI required will rely on the task at hand. AI can improve business performance in areas of predictive maintenance and where AI has the ability to analyze large number of data from images and audio, can efficiently uncover abnormalities in for instance, airplane engines or mistakes made in assembly lines. In logistics applications, AI can be applied to adjust delivery traffic, improve fuel efficiency and reducing delivery times. Applications like voice recognition is an effective tool in customer service management, sales, understanding customer demographics Transaction data in social media applications can help produce personalized recommendations for customers, which many retailers use to their advantage.

Artificial intelligence has streamlined programs and procedures, automated routine tasks which, improves customer service experience and helps businesses with their bottom line performance. In fact,?Business Insider ?predicts that artificial intelligence applications will save banks and financial institutions $447 billion by 2023.

?Artificial Intelligence in Finance world

In the coming years, financial institutions can get substantial benefits by using AI to develop new competitive policies across their value chains. Most notable areas of finance AI can be beneficial include;

Risk Assessment - Artificial intelligence can be used to determine whether someone is eligible for a loan. With the wake of digital revolution, digital lenders in Kenya and indeed the world, banks and other financial institutions are using machine learning algorithms to not only determine a person’s loan eligibility, but also provide personalized options, AI has been proven to make a determination on loan eligibility quickly and more accurately.

Risk Management - Risk mitigation is always an important yet ongoing challenge in financial institution such as banking. The machine learning can help experts use data to pinpoint trends, identify risks, conserve manpower and ensure better information for future planning.

Fraud detection, management and prevention - Occasionally you may receive a phone call from your credit card company after you’ve made several purchases, this is made possible thanks to artificial intelligence, fraud detection systems analyze a person’s buying behavior and trigger an alert if something seems out of the ordinary or contradicts your traditional spending patterns.

Credit Adjudication - AI will enable immediate analysis and decisions, enabling loans to be delivered in actual moment. Artificial intelligence can quickly and more accurately assess a potential customer based on a variety of factors, including smartphone data, Social media data, credit reference bureau amount other data available for analysis. Artificial intelligence can analyze a customer’s spending patterns and actions, which can predict loan borrowing behavior. This is also important in areas around the world where people have smartphones and other means of connection and communication but may not have traditional credit

Financial advisory services. If you are Looking to follow the latest financial trends or Interested in a portfolio review artificial intelligence algorithms can analyze a person’s or institution portfolio or the latest trends or most types of relevant financial information so that you can receive the information you need as quickly as possible for faster decision making. This can greatly help the portfolio managers or personal wealth consultants to offer the best to their clients??

Trading. The artificial intelligence is used to analyze patterns within large data sets, it’s no surprise that it’s often used in trading. AI-powered computers can sift through data faster than humans, which expedites the entire process and saves large chunks of time. This can be used by stock brokers and investment managers in their operations and return optimization

Managing finances and personalized banking. Chat bots and virtual assistants have reduced and in some cases eliminated the need to spend time on the phone waiting to speak with a customer service representative thanks to technology and AI, customers can check their balance, schedule payments, look up account activity, ask questions with a virtual assistant and receive personalized banking advice. Common example is the use of chat bot in Safaricom, KCB and standard chartered. Many other banks in Kenya and indeed the world are following suit?

Prevention of cyberattacks. Consumers want to be reassured that banks and financial institutions will keep their money and personal information as safe and secure as possible, and artificial intelligence can help. It’s estimated that up to?95% of cloud breaches ?are caused by human error. Artificial intelligence can?boost company security ?by analyzing and determining normal data patterns and trends, and alerting companies of discrepancies or unusual activity.

Process automation and reduction of human errors. AI can automate ?repetitive mundane, time-consuming tasks, such as reviewing documents or pulling information from applications, which will free up employees to tackle other projects. Further In the financial services industry,?94% of surveyed IT professionals ?said they aren’t confident that their employees, consultants and partners can safely protect customer data. Thankfully, artificial intelligence can help reduce false positives and human error.

Making Smart underwriting decision in banks and insurance industry - AI solutions are helping banks and lenders make smarter underwriting decisions when it comes to the approval process for loans and credit cards using deep analytics of customer data to develop patterns and predictor probability analysis on default occurrence basing on historical data. Further AI can be used to predict false insurance claims enabled by data analytics to reveal unusual claims for investigation. Past data analytic can be used to evaluate the risk of the insured which further can assist in insurance premium build up.??

The future of AI in finance

Since artificial intelligence has become more widespread across all industries, it’s no surprise that it is taking off within the world of finance, especially since COVID-19 has changed human interaction. By streamlining and consolidating tasks and analyzing data and information far faster than humans, AI has had a profound impact, and experts predict that it will save the financial industry about?$1 trillion by 2030 .

Artificial intelligence technologies are increasingly integral to the world we live in, and financial institution need to deploy these technologies at scale to remain relevant,” according to?McKinsey & Company . “Success requires a holistic transformation spanning multiple layers of the organization.”

It’s also important to note that millennials and “Gen Zers” are becoming the financial institution’ “largest addressable consumer group” ?Across the world, financial institutions are looking to increase their IT and AI budgets “to meet higher digital standards” since younger consumers often prefer digital banking. In fact, a recent study indicated 78% of millennials say they won’t go to a bank if there’s an alternative.

Article By

CPA James Njogu

Head – Tax and shared services – UAP Old mutual Group