AI In Banking: How will Artificial Intelligence Change the Banking Industry?
Artificial Intelligence is at the heart of a seismic shift in the financial industry. It has already started to empower banking organizations to redefine operation, establish innovative products and services, and impact customer experience.
And the best part: we’re just beginning to feel the tremors of a far-reaching revolution.
We are entering the machine age, banks who are early adopters of these technologies will have a serious advantage and find themselves on the competitive edge.
However, if they lag then the upstart fintech firms will leverage these advanced technologies to take them over with their sophisticated algorithms.
Hence, if the players in the finance industry want to maintain a sharp competitive edge, they need to embrace AI and carefully weave it into their business strategy.
In this blog post, we will examine the dynamics of AI ecosystems in the banking industry by understanding AI’s colossal impact on banking.
We will also see major disruptions in the industry. Finally, we’ll explore how AI is changing banking and its future financial impact.
1. Financial Institutions Became early Adopters of AI to Secure their Futures.
Analysts predict that throughout the next 10 to 15 years, AI applications will create $1 trillion funds for the financial industry in savings. These savings will be achieved through a mix of office efficiencies encompassing everything from improved data processing to shifts in staffing levels.
One trillion dollars is a huge number; however, it fails to help us understand the impact these applications will have on midsize FIs. But, to translate it more easily consider these figures for your bank:
- 34% increase in revenue
- 22% reduction in operating expenses
- 30% higher sales conversion rates
Now, imagine the impact of those results on your bottom line!
AI is poised to spur unprecedented gains for all those who are prepared to embrace it in the financial industry. More than 70% of big banks are already planning to implement AI solutions for front- or back-office.
Unfortunately, midsize banks are struggling as only 2% have deployed technology and in the near future, only 13% are planning to invest in AI.
For sure, it’s a challenge, however to midsize banks need to do some forward-thinking and their credit unions should recognize it as an opportunity if they want to flourish in the future. Most importantly if competitors are ignoring it then it means that it is time to begin implementation.
2. AI will Fuel Revenue Growth
By the year 2030, artificial intelligence-powered applications will boost revenues by 34%.
AI-powered applications can help boost revenues by leveraging the power of machine learning. Deep learning applications can identify motivations and sales triggers by scanning millions of records and examining consumer behavior.
Then, computers can be used to automatically deliver targeted messages to customers by applying that knowledge.
3. Higher Conversions with Personalized Offers
The foundation of sound marketing practice is delivering the right message (offer), to the right people, at the right time.
New-age bankers draw on experience to achieve that trifecta and drive customers to their branches. However, with AI, they can take a deeper dive by automatically delivering personalized offers which makes it more likely for customers to act on.
4. Automated up and Cross-Selling
Artificial intelligence in the banking sector can learn consumer behavior trends and according to that auto-suggest up and cross-sells to interested customers. The technology can suggest appropriate selling to bank staff during their face-to-face interactions with customers.
Let’s take an example, most of the current web interfaces have post banner ads and pop-ups to automate upsells and cross-sells. However, we are not sure as to how many times they work or if they are as efficient as they could be.
Instead, what if, you have a chatbot to greet customers by their name and voice? What if that chatbot or assistant initiated conversations based on a user’s transaction history? For instance: “Hello Ann, I can see that you sent nine international wires in the past week. Did you know of other electronic payment options available at a lesser cost?”
Unsurprisingly, customers are more responsive to that kind of prompt than banner ads.
Are we talking about taking financial advice from a machine?
Yes, and trust me it’s not that far-fetched. Plus, it can yield far bigger dividends than personalized advice as that is prone to human error.
In reality, customers can process little AI and data that funnels through numerous neural network layers. Plus, its solid market advice helps keep customers coming back by building wealth.
6. Alerts for High-Risk Customers
Artificial intelligence applications can help banks recognize warning signs that a customer is about to jump ship.
Well, AI can do this simply through constant monitoring and tracking their reduced platform login frequency and large withdrawals, for example. Computers can, then, automatically alert banking staff, giving them a chance to intervene.
Such automated processes help grow revenues by freeing banking staff and saving time to focus on deeper, valuable customer engagements. In turn, that can help yield greater profitability by improving a better customer experience, and ultimately, earn more sales.
7. AI will Offer Significant Savings
Increased revenues are just a part of the equation as AI implementation can help banks save tons of money. This is because there’s no better way to cut costs than with artificially intelligent applications without jeopardizing the quality of service.
In fact, artificial intelligence in the banking system can deliver a better customer experience as it allows staff to focus on customer retention.
8. Enhanced Customer Experience
Artificial intelligence-powered chatbots and virtual assistants in the banking system are a breakthrough. They can onboard new customers, answer customer questions, and help in customer account management.
This means that banks will no longer need staff to move money between accounts, or help customers reset their passwords, or find months-old bank statement copies.
Moreover, image recognition can eliminate the need for passwords through advanced facial and biometrics recognition. This will enhance the customer experience, save time, and reduce costly security breaches.
Banks can also leverage Natural Language Processing (NLP) for direct interactions with customers via virtual assistants such as Siri and Alexa. These bots can be deployed on different platforms, such as Facebook Messenger, to reach customers in their comfortable environment.
Indeed, by implementing AI for customer service, organizations report 33% savings compared to a live agent call, 70% fewer calls and email inquiries, and massive savings in staff time.
9. Improved Operational Efficiency
Experts say banks that implement AI report a 22% reduction in operating expenses as compared to those savings through saved staff hours and error elimination.
10. Accurate Processing
Today, 70% of the banks prioritize integrated receivables, and for good reason For instance, according to some NACHA estimates more than 60% of ACH payments arrive separately from remittance information.
Stranded receivable means that staff members have to track down email remittances and manually enter data. This, in turn, delays posting, lengthens DSO, and impacts cash flow.
By leveraging intelligent automation, banks can analyze large unstructured data without human intervention and reassociate payments. In fact, AI can increase processing rates by up to 95%.
11. Workflow Automation, Contract Reviews, and Reporting
Bank staff analyzes and organizes unstructured data which is tedious, costly, and error-prone work. The banking sector can utilize artificial intelligence algorithms and robotic processes for quick automated workflows and eliminate the need for human involvement.
Over time, AI become even more efficient and lead to billions of dollars in saving across the financial industry.
12. Improved Risk Management and Compliance
We all know that fraud costs banks millions if not billions. And, even if a bank is lucky enough to reclaim funds lost through the fraudulent transaction, they have to relegate staff to fraud management.
The application of artificial intelligence in the banking system can help prevent fraud. AI algorithms can scan millions of credit card transactions to detect potentially fraudulent transactions.
Moreover, AI-powered applications can help banks automate Anti-Money Laundering (AML) and Know Your Customer (KYC) compliance. These tools can extract data from a different source to quickly flag suspicious activity during onboarding or examine millions of transactions.
Finally, AI supports reliable credit decision-making by analyzing millions of data points against both traditional and non-traditional criteria to arrive at instant credit decisions. For instance, borrower education and job history.
This will be beneficial to financial institutions at three-folds: minimize risks, confident investment in high-value customers, and quickly lending of funds to avoid losing business to competitors. Lastly, this reduces the need for human intervention.