“The best way to predict the future is to create it”

Peter Drucker, hailed as the father of modern management methods, said: “The best way to predict the future is to create it”. In the financial industry, the future is now thanks to the use of new technologies.

AI Supporting Investment Decisions

One of the hottest trends in the financial industry is artificial intelligence (AI). With the use of advanced algorithms and machine learning, AI can help financial firms with data analysis, market prediction, and better risk management. AI helps to automate processes, which increases efficiency and reduces the risk of human error, often resulting from fatigue, distraction or insufficient knowledge. Well designed and maintained software supports repetitive tasks performed with the same precision, at the same time, with the same result. It reduces the risk of stoppages usually caused by failures due to human error. Nevertheless, human still play a key role in automation as they are responsible for designing and maintaining the process.

According to implementation reports from reputed consultancies, such as EY and Deloitte, the use of artificial intelligence in analysing vast amounts of financial data leads to better investment decisions. With the help of advanced AI algorithms, financial firms can draw on a wide variety of sources: stock market data, customer information, news published in the media, and historical data. This is helpful in detecting patterns and models that can be difficult for a human to capture due to the required huge computing power.

AI can help predict how the market will behave in the future. By analysing both current and historical data, AI can help predict a rise or fall in stock prices, helping investment firms make better decisions. AI can help predict other market trends, such as changes in currency exchange rates or commodity prices.

Importantly, AI helps to manage risks by detecting and analysing signals that indicate potential risks. Using advanced algorithms, AI can detect anomalies in data that may indicate potential fraud or other anomalies. Elon Musk, founder and co-founder of companies such as PayPal, SpaceX, and Tesla, predicted a few years ago that “artificial intelligence could potentially be more dangerous than nukes.” However, as technology advances, it seems that the use of AI in the financial industry will only increase.

Big Data, Big Deal

Every day, huge amounts of data are generated worldwide from a variety of sources: mobile devices, IT systems, media, especially social media, and many others. Properly analysed and used, Big Data can provide valuable information to support key processes, including business decision-making. The financial industry is one of those sectors of the economy that can benefit from the processing of huge data sets.

The use of Big Data enables better risk management, improves operational efficiency, and drives more profit. By analysing swaths of data, financial institutions can identify trends, customer behaviour, and risks that impact their business.

Risk analysis is one of the most important applications of Big Data in the financial industry. It allows companies to better understand the risks involved in lending, investment decisions, and asset valuation, to name a few. It also helps to quickly identify financial fraud, suspicious behaviour, and other irregularities, allowing companies to reduce reaction time and limit potential losses.

Big Data helps improve operational efficiency in financial firms. Data can optimise business processes, including analysing expenses, managing customer relationships, and assessing employee performance. In this context, data analytics can provide valuable insights to improve business processes and reduce costs.

Another application of Big Data in the financial industry is the personalisation of services. Data analytics provides a better understanding of customer behaviour and preferences, enabling the delivery of products and services that are tailored to customer needs. Firms can use customer data, such as transaction history, purchase and service preferences, to better understand what the customer wants, and provide them with the right solutions.

Satya Nadella, CEO of Microsoft, says that the use of Big Data is key to making faster and more accurate business decisions, and that data analytics can help understand trends, customer behaviour and risks, allowing for fact-based decision-making and risk mitigation.

Digitisation and Automation in Finance

In this day and age, digitalisation and automation are key drivers in many industries, including finance. According to Deloitte’s 2022 Central Europe CFO Survey, for one in three CFOs from Central Europe, digital transition is driving strategic change in business operations. 98 percent of respondents said that their companies are conducting or planning digitalisation in finance.

One obvious advantage of using such technology is to improve efficiency and quality of service. With automated processes, labour time and costs can be reduced while improving the quality and precision of operations. Automation enables faster decision-making and the detection and minimisation of the risk of human error, which leads to better customer service and increased customer trust. The use of tools such as chatbots and mobile applications allows customers to access financial services more quickly and conveniently, increasing their satisfaction with the service and boosting brand loyalty.

However, while digitalisation and automation tools bring many benefits, they pose some challenges for the financial industry. One of the key challenges is digital transition, adapting existing processes and infrastructure to new technologies. This requires investment in new IT systems and employee training, and a change in organisational culture.

Another challenge is the protection of customer data and privacy. As the quantity of data processed by the financial industry grows, so does the risk of privacy breaches and unauthorised use. Appropriate procedures and tools must be put in place to ensure that customer data is protected.

It seems that new technologies such as AI, Big Data, digitisation and automation are the future of the financial industry. They are a key part of the sector’s transition, necessary to offer innovative solutions and services, improve customer service, and increase the competitiveness and efficiency of business processes. However, all this requires the adaptation of infrastructure and processes to new technologies and the implementation of a range of changes in financial institutions. Change is the only thing that is certain about the future.