The spending on Artificial Intelligence is expected to reach $57.6 Bn by 2025. Additionally, the current adoption of fintech is estimated to be at 33 percent around the world.

It’s no surprise that IoT devices, in conjunction with data-fueled AI systems, have the groundbreaking potential for all industries, including fintech. With everything getting digital and automated, the finance and banking sector is set to radically change by the combined effect of machine learning and the Internet of things.

To gauge the scope of potential, let’s look at some interesting ways how ML and IoT are transforming the fintech space.

Leveraging ML and IoT to Birth Possibilities

Personalized Wealth Management

According to JD Power’s 2018 Retail Banking Advice study, 78% of consumers want financial advice and guidance from their bank. However, only 28% of consumers feel they are getting the same.

The survey also unearthed the matters that concern customers the most. It found that customers seek advice more commonly about investment, retirement, savings, and keeping track of expenses.

In response to this growing trend, almost every other major bank is now using AI and IoT to personalize wealth management for its customers. Personalized wealth management includes services such as tailored retirement advice, products, and plans that fit in well into a customer’s financial portfolio and offer them value considering their current standing.

By offering personalized recommendations for products and services, banks can improve overall revenue, business from individual customers, and profit margins – all the while providing a better experience to their customers.

Fraud Detection + Cybersecurity Risk Detection

ML tools can analyze existing fraudulent cases, detect common patterns among them, and evaluate whether a particular transaction exhibits specific characteristic. he banking industry is the most obvious target for online hacks and frauds. It is, therefore, tempting to look at emerging and arriving technologies to help avoid such associated risks.

The financial gain for fintech companies to use ML and IoT in this direction is massive. According to a 2018 report by LexisNexis, for every dollar of fraud, companies have to spend $3.37 in resolving it and appeasing the customer.

Banks can address issues such as these by developing programs that use machine learning and deep learning to identify the nature of each transaction before it finalizes. Another possibility for banks is to use ML to learn and identify a customer’s behavior and notify authorities when a customer exhibits a pattern unusual to her.

The trick would be to do this intuitively and accurately, so as not to pose an inconvenience to a customer who is not acting fishy.

Personalized Customer Experience

Banks have remained cold and distant for a long time when other industries have known and reacted to the fact that customer convenience is superior, just like product quality or service delivery is. The average customer still operates in the dark at their bank and is least aware of the policies, terms, and conditions that their bank follows.

ML and IoT, along with data analytics, can help create a more friendly atmosphere within banks and other financial institutions, delivering more delightful customer experience. For instance, banks are now looking at customer spending habits and buying behaviors to provide personalized suggestions and saving plans to them that they might have missed.

ML and IoT can become the drivers of personalization within the fintech industry, leading banks to better customer engagement.

Better Customer Service

For customers, getting on the phone with bank personnel can lead to a lot of miscommunication and misunderstanding, often resulting in visiting the bank in person. When it comes to customer service, banks can use AI to automate several tasks, leading to a more efficient, faster, and productive service.

According to a report by PwC titled, “Financial Services Technology: 2020 and Beyond”, self-service dashboards are the path to smarter services and smarter sales for banks and FIs, which also look alluring to customers.

Several studies have shown that customers now like to take matters in their own hands rather than having to speak with a customer service agent. AI-powered customer service can help banks cut down costs and save man-hours.

Wireless Payments, Security, and Authentication

The Internet of Things can have a huge impact on how we interact with applications in the fintech domain. As such, wearables have the potential to transform cash withdrawal and payment by replacing traditional cards and smartphones with smart devices.

Not only that, wearables and IoT can mean better security in fintech, as banks start to use wristbands and smartwatches to track the person’s heartbeat as a biometric authentication key.

Solutions such as Kerv position themselves as the first contactless payment ring, allowing us to be optimistic about the possibilities of IoT and wearables in the fintech industry.

According to Forrester Research, AI and IoT are the technologies that will provide an edge to fintech companies by 2025, allowing them a massive opportunity to grow and expand on the customer engagement front. With the growth in technology and the ever-changing demands of financial markets, the revolution was inevitable.

Combining Artificial Intelligence, Machine Learning, and the Internet of Things in banking can prove crucial in attracting customers, retaining them, and offering them value coupled with stellar customer experiences.

Unsure about the next move? Rubiscape helps fintech companies with technologies that add value to their digital transformation efforts. Get in touch with us to explore synergies.

Author: webhero