Whether technology is a boon or a curse that, still remains an unanswered question.
Artificial intelligence has evolved to make a mark in some big industries and businesses, leading to disruptive markets.
Let’s take a look at some pros and cons to understand it a little better.
Improved Customer service – Automated customer service has drastically reduced the turn-around-time for customer queries and requests, resulting in superlative customer experience. Chatbots are getting better day by day and learning more with new customer experiences.
Effective Marketing – AI can get relevant information like customer spending habits, interests, demographics, etc. from customer-facing API platforms which provide the marketing team insights to customer behaviour and make better product offerings to the customer. Without spending money on product-specific campaigns, banks can now analyse and improve customer portfolios offering them multiple solutions.
Consistent performance – Consistency has a great impact on the overall performance of an organisation. The HR departments often face issues with the best of their employees on attrition, performance, absenteeism, health issues, tardiness etc., which directly contributes to underperformance. With Machine Learning (ML) algorithms in place, admin tasks can be executed with ease and consistency. With limited human intervention AI gives prominent results with a reduction in error rates.
Risk Assessment – Approving loan is a complex process involving multiple checkpoints. AI can execute the process with simplicity by analysing the data and transactions retaining customers confidentiality. With the help of Machine learning, risk patterns are detected at an early stage. It also evaluates the creditworthiness and speeds up the process to provide a good customer experience. It helps the bank in saving the costs for servicing the customer, decrease losses due to fraud and saves time spent on due diligence and other paperwork.
Fraud prevention- Traditional fraud prevention techniques are based on identifying past data and trends. With the help of AI, a combination of supervised and unsupervised Machine Learning models are trained on historical data to detect anomalies. Banks can identify customer suspected fraudulent activities in real-time and take preventive measures. Unsupervised learning model with neural networking learns constantly from the new data. It has helped the banks to identify new trends in fraud cases using predictive analysis.
It gives banks more control over validating transactions, reject payments and stop fraudulent activities.
Improved Investment and Trading Strategies – Data science plays an important role in systematic asset management. Financial organisations use AI strategy in their techniques for signal generation and portfolio constructions.
With deep learning techniques, new market trends can be detected early and based on the past actions it can predict outcomes for multiple permutations and combinations.
AI-powered tools can get financial data from financial markets across the world. With Machine learning and deep learning techniques evolving to an advanced stage of high-frequency trading, investment decisions can be instantly managed more accurately.
Data – Organisations using traditional IT infrastructure may have a poor quality of data available in some cases and it takes an enormous amount of time for the transformation. Results may hamper depending on the quality of data.
Cost- Banks and financial institutions are complex in structure. With the changing environment, the AI programmes need to be upgraded periodically which needs and expert in-house IT team or consultation. Businesses without an in-house IT team will spend more on hiring AI professionals or outsourcing. At the same time an in-house IT team will need to be trained and up-skilled.
Lack of emotions – No doubt chatbots are smart but it lacks emotions. Though it may quickly provide accurate information, it can not empathise. In some cases, it affects the customer experience. Trade decisions made with AI-based systems are focused on specific events and does not take public events into consideration which may occur in real life such as political, religious, etc.
Unemployment – Most of the jobs that are replaced by computers are monotonous and physical tasks which also contributes to a major mass of the population.
Self- driven vehicles are replacing human drivers. Biometric payment systems will soon replace the behind the counter jobs. If the knowledge upgrade doesn’t take place it will give rise to unemployment.
Distribution of power – The combination of AI and Cloud technology can unleash limitless possibilities. AI gives the power to selective few and unethical uses of AI can lead to unfavourable results. Think of corrupt politicians or Capitalists using the technology to their benefit.
AI-powered computers are capable of performing human tasks – it may sound, like an obnoxious truth. One can’t deny this technology is also creating new jobs and pushing humans to adapt and acquire a new set of advanced skills.
Is this a part of human evolution?