By the end of 2030, Fintech to have its workforce expanded by 19 percent.

  • Global AI in Financial Services Survey supported by Invesco and EY demonstrates the effect AI has on financial institutions – from transforming different business models to changing the workforce.

This survey speaks of how AI is drastically changing the way how financial service industries create data and how they’re using the positive insights extracted from the data.  In return, these insights were proven valuable in creating newer business models, changing how the newer workforce works by reshaping their working environments and giving rise to newer risk dynamics.

Artificial intelligence is on the verge of changing multiple business models in the finance industry. A survey conducted by the Cambridge Centre for Alternative Finance (CCAF), University of Cambridge Judge Business School along with the World Economic Forum.

AI has multiple reasons to work in parallelism to technological advancements in sectors such as communications, construction, computers, and printing. Thus said, it is a commendable opportunity for those looking to transform their careers from being a tech professional into an AI professional.

Precisely, there are multiple reasons to believe how AI will revolutionize the way we manage money. Modern AI has started paving its way and leaving footprints in several sectors that include the payments and the banking sectors.

According to Jochem Wubs, a data scientist at ABN AMRO, there was hardly any momentum on the consumer side four years back. Because then the usage of data science and machine learning in the banking sector was limited restricting any further involvement in the credit applications.

However, in recent years, these have changed says, Jochem Wubs.

Now many parts of the banking sector are AI-driven enabling other sections like the merchants, service providers, and financial institutions in order to understand the customer preferences. Additionally, AI-powered consumer technologies are making transactions frictionless and easier.

Let us find out how AI is revolutionizing the finance world.

  • Voice shopping

Deep learning and neural networks have undoubtedly boosted the rise of automated speech recognition systems (ASR). A technology that enables digital assistants like Siri and Alexa process voice command and understands every sound of speech.

Amazon has been ahead of this feature and has supported the shopping of millions of items. With the help of voice assistant apps shopping online is as easy as telling Alexa to order paper towels or any items online. As voice assistants gain popularity in the shopping domain, other brands using voice assistant apps are looking for similar ways to implement AI-powered speech recognition in their shopping experience.

Starbucks recently developed a voice push app called Bixby that enables the customer to order their food items while placing their order or making personal changes in their beverages.

  • Conversational banking

Thanks to AIs support in natural language processing (NLP) which now allows their customers to have conversational banking support with the help of chatbots. These chatbots provide 24/7 support to the customers making their banking experience flexible and smooth.

Erica, a digital assistant launched by Bank of America last year now makes it easier for BOAs customers to interact with Erica. Erica can answer simple queries and provide information related to checking the banking balance, credit score, and account and routing numbers, etc.

  • Smart loans

One of the major ways to determine whether you’re liable to apply for loans or not is based on your credit scoring systems. The best part about this scoring system is that it takes into your financial status into account such as your banking history, income, and tax payment history, etc. However, this system only works well for those having credit history and have used credits on their account. This does not include the hundreds of millions of people that are under the bank and are not in the digital financial system.

Looking at the possibilities of AI, a couple of companies are now redefining their creditworthiness along with risk assessment in loans in an attempt to provide better opportunities to people. A Singapore-based fintech startup Lenddo uses machine learning “alternative data” to check how likely will the person be able to repay their loans.

The algorithms used by Lenddo scan through thousands of data points that include data from email subject lines, social media account use, internet browsing, geolocation data along with behavioral traits to check the individuals’ customer creditworthiness.

  • Fraud detection

Based on a report by McAffee, a cybersecurity company, the online fraud accounts for about USD600-billion toll cybercriminal activities every year.

Cybercriminal activities such as fraudulent transactions majorly revolve under static rules such as geolocation, the difference between billing and shipping addresses, IP addresses, type of items, and the amount of the purchase made. But there are fix rules that result in a legitimate transaction that gets declined at times (false positives) coming through at a huge cost especially to online retailers. With AI technology on-board, it will get easier for financial institutions and merchants to have much more analysis about the transaction taking place. This further could help in identifying the differences between fraud transactions and regular transactions.

“Technological developments in the banking and finance sector are advancing at an accelerating pace. We’re in a transition in the way of thinking about money. It’s interesting to see how the industry adjusts to that,” says Jochem Wubs.