The world has come a long way in terms of technology. From adjusting the antenna on a blank and white television to watching LIVE sports on handheld devices in full HD, there is no slowing down for innovation. The technological breakthrough and ease of access to innovative products have made the customer smarter and empowered him with choices. Evidently, the boom in technology has helped accelerate sales for service providers as customers are finding new ways to interact with their preferred brand or a company. Being Omni channel has certainly helped in the process of retaining a loyal relationship between the provider and the buyer. As more and more companies are competing with respect to ease of availability for the customers, managing systems has become crucial and a tedious task.
The companies are receiving a lot of data every minute that is mostly ignored because they are not equipped to handle such large volumes. The collection of data, processing, structuring, analyzing and extracting meaningful information is a time-consuming process that adds to the company’s operational expenses. This loss of valuable time affects strategic planning which leads to customers moving to competitors. The other problem that comes with the unavailability of an intelligent system is the possibility of human errors and overlooking unethical activities that cause losses to the company not only in terms of revenue but also its reputation. Financial institutions are one of the biggest industries facing these challenges.
The onus comes on the service providers to seamlessly serve their King in the best way possible while keeping the integrity of the company intact. The customers are getting to a point where they will easily switch their loyalty if their demands are not fulfilled. Slowly, companies are adapting Artificial Intelligence technology to help overcome these issues and help increase the agent’s productivity by automating various time-consuming processes.
The use of a strong machine learning algorithm that drives AI into making informed decisions is transforming the finance industry in various ways. Some are as below:RISK ASSESSMENT
The basis of AI technology is learning from past data, hence, the implementation of AI in the financial institution is destined to succeed. For a company that sells credit cards, a credit score is used as a deciding factor to identify who is eligible and who isn’t. For providing a customized interest rate on a credit card, the company can use the individual’s data such as loan repayment habits, number of active loans, the number of active credit cards, etc. AI with deep learning finds its place here as it has the capability of going through thousands of personal financial records and providing a figure quickly and accurately.
AI is functioning as a data analyst to save millions by eliminating inaccuracies. AI tech is powered by machine learning algorithms that can learn over time and analyze a vast amount of data that has established itself in areas that require analytical and clear thinking.
Financial institutions, like all businesses, aim to reduce the various risk conditions. Banks provide loans to an individual/organization at an interest. This money being provided by the bank is actually someone else’s money. Hence, the banking industry takes fraud extremely seriously. AI comes to the rescue here as it uses the past spending habits on various transactions to detect any unusual behavior such as swiping a card from another country shortly after it has been used elsewhere.
The other reason why AI is widely used to detect fraud is because of its deep learning algorithms. For example, if it flags a regular transaction and the human agent corrects it, AI learns from this experience and makes more sophisticated conclusions next time.
Having an omnichannel presence comes with its own pros and cons. One of the widely known disadvantages is the customer’s outburst on the Social Media platform. Companies have to be very careful in dealing with such instances because social media is such a platform that can make and (easily) break a company’s reputation. AI has proven to be a saviour that can spin this situation into a positive experience.
Deep learning has improved the machine’s ability to understand a query and give an appropriate response. The companies can find the opinions and views of their customers on various social media channels such as Twitter, Facebook, YouTube, etc. This data is fed through machine learning algorithms to understand the customer sentiment (positive, negative or neutral) to provide an appropriate response. This happens so smoothly in the background that a customer posting the query might not know that he is speaking to a Bot unless explicitly mentioned.
Predictions are an integral part of trading. As a lot of money is involved in trading, it is important to predict the future of the market as accurately as possible. Using AI, machines can be fed with a huge amount of data and they can be taught to observe the pattern in historical data and predict the repeatability of the same in the future. We have the data of the financial crisis that occurred in 2008 which can be made available to the machine learning algorithms to learn the anomalies. This way, AI can detect similar anomalies when they come across in future and plan strategies around the same.
Also, for individual traders, the AI can suggest portfolios depending on the person’s risk-taking capacity. For someone with a high-risk appetite, the AI can suggest when to buy, hold or sell a stock. For low-risk takers, AI can give an alert if the market is expected to fall and then take a decision to stay with the investment or get out.
Managing finances is a challenging task due to its complex nature, hence, AI is also used here for managing the same. Personal financial management is one of the recent developments in the AI-based wallet. A San Francisco startup has created an e-wallet that uses machine learning algorithms to help individuals make smart and informed decisions about spends. The AI basically scans through the customer’s web footprint and learns from the past transactions to create spending graphs. This not only helps the consumer in making the right decision to manage finances but also saves the time of creating lengthy spreadsheets to track expenditure. From small scale investments to large scale, AI is being used to manage finances and optimize spending habits.
There is no iota of doubt that AI will continue to evolve, and its business applications will keep growing. The manual operations in the financial ecosystem could be a thing of the past with AI taking informed business decisions and involving humans only in rare cases of disputes. This technology will also allow the assets and wealth management managers to focus on client relationships and strategic planning.