How Artificial Intelligence is transforming the finance industry

September 9, 2020

Artificial Intelligence and Machine Learning are continuously transforming businesses and influencing traditional processes in the finance industry. AI technology already supports many daily activities, and quite often does this without us knowing.

A recent study by Gartner suggests that 40% of major businesses plan to implement AI solutions in 2020 and over half intend to double their existing services during this year. Admittedly these forecasts were made before the pandemic, but analysts believe the rise of AI will inevitably continue.

In certain industries, AI and ML offer a wider range of opportunities. One particular sector this relates to is in finance, where new technologies are already having an impact and altering the traditional shape of the financial industry. Some businesses are taking full advantage of AI solutions in the most effective manner. This enables businesses to utilise the potential of new technologies and improve their processes.

Risk Management

AI plays a critical part in risk management and this is particularly important for the finance industry. For certain cases of risk, algorithms can be implemented to measure case history and determine particular problems. This involves using ML to generate certain trends and identify potential risks.

The use of ML in risk management means a significant amount of data can be processed more quickly. For example, structured and unstructured data can be managed via cognitive computing. Processes like this would translate into many hours for a team to work on.

Fraud Prevention

With a rise in digital customer transactions in the last few years, providing an effective fraud detection model has become an important part of protecting sensitive information. AI can be implemented to enhance existing rule-based models and support human analysts, providing more efficient, accurate and cost-effective results.

Personalised Banking Service

In the banking industry, smart chat features supported by AI can provide intelligent solutions for users and reduce the overall workload for associated companies. Voice-activated virtual assistants are continuing to grow in popularity. These services are capable of checking balances, account activity and scheduling payments.

Many banks now have applications that provide personalised financial support and help in meeting financial goals. These AI-driven systems can monitor income, expenses, spending behaviours and provide financial support. Many banking applications can also provide reminders to pay bills, transactions and offer a more interactive and convenient service.

Quantitative Trading

Quantitative trading or data-driven investment has been expanding within the global stock markets in recent years. Investment companies rely on data to generate accurate predictions and determine future patterns in the market.

AI enables the added advantage of measuring trends from previous data and making predictions on whether they are likely to happen again in the future. When there are particular disruptions in the data, AI can examine the data in more detail and understand certain factors that may have influenced this change and be more prepared for the future.

Credit Decisions

In many industries, AI is effective in enhancing the decision-making process. In terms of credit, AI offers accurate information on potential borrowers, presenting key details quickly and at a lower cost. AI credit scoring is more detailed and can identify applicants who are more likely to default and others that may not have a suitable credit history. AI models also lack the human element which means they are unbiased and not influenced by human decisions.

Systems that are driven by AI can be implemented quickly and are likely to become more efficient and reliable. The services are emerging more within the finance industry and are being actively integrated into more businesses operating within the finance industry. AI holds a lot of potential for the finance market but it is up to each business to implement the right technology and make the smartest decisions with the right data.

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