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Artificial Intelligence (AI) is becoming more and more essential in today’s era. Its use is felt in almost every field and the respective operations involved. This tech advancement has revamped the world of  financial services, the entire BFSI sector like never before. It not only boosts customer interactions and improves customer visibility but also plays a pivotal role in securing a digital identity, implementing anti-money laundering (AML) practices, detecting frauds and giving out solutions. Enterprises have already begun implementing AI in their day-to-day business operations and have started seeing results. However, all said and done, AI can be only used as an aide to humans and cannot take them over.

The challenges that AI address

Fraudulent transactions in the BFSI sector: A fraud is a regular transaction before it gets detected. Even if an enterprise loses a small amount by way of fraud every month, the annual figure shoots up by way of fraud to quite a large extent. In many cases, the revenue loss is as same as the GDP of some of the European countries. However, such fraud may not be detected when there is no data; and more so, when enterprises function in silos.

In such cases, AI not only helps when it comes to in creating an integrated view of the entire business but also helps to discover patterns and this way can detect and finally curb fraud.

It is interesting to note that intelligent algorithms can help to expedite the time, which is mostly taken to handle manually huge amounts of data, which we often term as Big Data, and arrive at patterns. For example, the contemporary mechanisms working on enterprise systems housing thousands of accounts and carrying out billions of transactions annually, would require years to identify just one single pattern. On the contrary, AI does the task in a few hours. This way, AI can not only be leveraged towards social good, but it can also help to better understand what “may happen” and so in a way, future-proof enterprises against frauds of any kind.

How does AI detect fraud?

AI is often considered a boon. But it needs data to function. Its algorithms work on mostly the concept of self-training. The more they consume the data, the more convenient it becomes for them to learn from the emerging patterns. In fact, they create intelligence, which is not available in the regular KYC documents.

When the focus is more on how the transaction is happening, the source from which the money is being sent, and the respective accounts, AI helps you decipher the exact relationships between both the transacting entities and determines the respective behaviour patterns. It also underscores the penchant of committing fraud.

AI also helps to discover transaction patterns, be it normal or anomalous, depending on the associations as well as relationships between entities. This way, it can effortlessly nip any anti-social activity at the bud.

When it comes to monitoring and flagging of certain patterns, it can be done so through AI. Accounts that have low tenure of money stay, multi-currency transactions across geographies, unprecedented rise in activity after being dormant, sudden dormancy of high transactions, everything can be effortlessly auto-scrutinised with the help of AI algorithms.

The algorithms detect specific activity patterns and deliver the entire bigger picture. It is also effective when it comes to business forensics.