The other day, this writer was talking with a banker about the various ways through which fraudsters use fake land documents to get loans approved. The banker said that the chain of title and land deeds is matched discreetly.
The prevalence of fraudulent activities has been a part and parcel of banking sector since the 20th century. As the global business world developed, the techniques by fraudsters also changed.
'The Wolf of Wall Street', released in 2013 and starring Leonardo DiCaprio, is a movie on the life of a stockbroker who rose to the top by committing frauds and indulging in corruption. The movie is based on a memoir by stockbroker Jordan Belfort who, in 1999, pleaded guilty to stock market fraud.
Another recent story on fraud is the case of Punjab National Bank (PNB), the second-biggest state-run lender. The bank stunned the country's financial sector when it announced recently that it has discovered fraudulent transactions worth US$ 1.77 billion at a single branch in Mumbai. PNB official from Mumbai filed a criminal complaint with India's federal investigative agency against three companies and four people, including billionaire jeweller Nirav Modi and his uncle, Mehul Choksi, the managing director of Gitanjali Gems Limited, saying they had defrauded the bank and caused a loss of 2.8 billion rupees. The bank alleged that two junior employees at the Mumbai branch had helped the companies in managing 'letters of undertaking' (LoUs) from it without having a sanctioned credit limit or maintaining funds 'on margin'. The LOUs were used to obtain short-term credit from overseas branches of other Indian banks, PNB said. The fraud, by far the biggest-ever detected by an Indian bank, came to light at a time when lenders -especially the state-run banks-were hobbled by US$ 147 billion in soured loans on their books. This problem has choked new lending and hurt the country's economic recovery.
Perhaps artificial intelligence can be put to use to detect cases of fraud and manage customer services and other parts of banking.
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of 'intelligent agents' any device that perceives its environment and takes actions that maximise its chances of successfully achieving its goals. Kaplan and Haenlein defined AI as "a system's ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation". Colloquially, the term 'artificial intelligence' is applied when a machine mimics 'cognitive' functions that humans associate with other human minds, such as 'learning' and 'problem solving'. AI often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute. A complex algorithm is often built on top of other, simpler, algorithms.
Human errors or frauds can effectively be detected and managed properly through the application of Artificial Intelligence (AI). Thanks to thriving Artificial Intelligence (AI) concept, companies can make their devices more powerful and 'intelligent' to serve their customers in a better way. Both B2B and B2C businesses have started adopting this revolutionary technology as per their scale and size. However, the penetration of AI in the banking sector is somewhat limited till date. The distinct data sets and the risk of confidential data are primarily responsible for the sluggishness of AI integration in the banking system. But then, as online banking and mobile banking is becoming increasingly popular as a tool for transactions 24/7, it can be expected that AI will soon take over to address risks of fraud and other problems.
Digital personal assistants and chatbots have revolutionised the customer services and business communication. From assisting people in performing daily tasks to giving them a personalised experience, virtual assistants and chatbots have many applications. Mobile app development can integrate the AI technology for enhancing services. After gathering the data from the user's mobile devices, the AI-based mobile banking app processes the data through machine learning to provide the relevant information or redirecting the users to the source of information.
It is easy for a banking app integrated with AI-related features to show services, offers and insights in line with the user's behaviour. What is more, the app handles the advice and communication part by analysing the user's data. Banks can give online wealth management services and other services by integrating AI advancements into the app. The revolutionary AI technology works on the principle of data collection and analysis. Any AI system can work well with better data sets. A tailored mobile banking app enriched with AI-based features can collect all the relevant and useful data of the users to improvise the learning process and enhance the overall user experience. After accumulating and analysing the data, the experience can be made more personalised. Also, the data regarding financial transaction can help the bank understand the expenditure pattern of the customer. The bank can come up with a customised investment plan accordingly and also assist the customers for budgeting. Banks can send the notification about the advice for keeping a check on the expenses and investments based on the data.
At the moment, banks are using third party modules and connecting the same to the Core Banking System through application programming interfaces (APIs). The use of open source codes are also increasing more and more to ensure banks adapt to the dynamics of rapid changes by customising seamless services with customer requirements.
Risk assessment prior to approving loans is a very complex and critical process. It requires both accuracy and confidentiality. AI can handle and simplify this process by analysing relevant data of the prospective borrower. AI can analyse the data related to the latest transactions, market trends, and the most recent financial activities to identify the potential risks in giving the loan. Banks can also get the idea of the prospect's behaviour with AI-based risk assessment process. AI can minimise the probability of error at identifying even the slightest probability of fraud. The predictive analytics can manage the entire process smoothly. Banks should ensure secure and swift transactions. AI is designed to detect the fraud in the transactions on the basis of a pre-defined set of rules. Also, the mobile app can find out any suspicious activity in the customer's account on the basis of behaviour analysis. For example, any online transaction of a huge amount from the customer's account that has a history of small transactions can instantly raise alarms. Use of predictive modelling can approach any suspicious transactions and prompt the relevant authorities accordingly.
AI also plays a vital role in protecting personal data. With the increase of cyber crime in recent years, AI-based fraud detection can lend a helping hand in preventing such attempts. So, for banking and finance sector, AI has a tremendous scope in the domain of cyber security.
The mobile app development services can address the issue of fraud and data breach while developing an AI-powered mobile app for the banks. AI has many benefits to offer to the banking sector. Be it an Android app development or iOS app development, the AI can bring revolutionary changes in the banking industry.
The bank and financial institutions can understand the user's behaviour and give personalised experience through an app.
Masihul Huq Chowdhury is Managing Director & CEO of Community Bank
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