Banking and finance companies are using AI in almost every part of their operations. Here’s what to expect over the next few years.

AI, Banking, Finance

We can see AI’s impact in the worlds of banking and finance; voice-activated banking app assistants, personalized offers, enhanced customer service, 24×7 chatbot help, anti-fraud and risk management activities, and more have become linked with AI technologies. And like other industries, banking and finance are benefitting from the automation of routine manual tasks and decision algorithms.

According to Business Insider, most financial institutions are well aware of AI and its applications to their industry; the same article projected a potential cost savings of $447 billion would be attributed to using AI in various ways. Meanwhile, The Economist reports that approximately 30% of financial companies expect 50-75% of their workloads will be supported by AI within five years.

AI’s Ongoing Impact on Banking and Finance

As customers or clients, most of us have already had some contact – directly or indirectly – with AI’s applications in banking and finance. Below are five areas that are ready to expand their current use of AI.

Personalized Banking and Customer Experience

Much has already been said about using AI to anticipate customer needs, and that goes for banking institutions as well; such institutions can use multiple data sources to customize offers and provide better user experiences to their customers as individuals. For customers, this can take the form of such labor-saving devices as auto-filling forms, using chatbots to answer questions, and getting financial suggestions based on their own spending habits.
In the near future, look for more curated content and product offerings, personalized interactions, and improved customer service timeframes.

Language Processing and Voice Recognition

Thanks to Siri and her ilk, we’re all familiar with voice assistants. We know that this technology makes routine tasks quicker and easier. But in banking, the application of voice recognition technologies can go beyond simply checking our balance; vocals are poised to become the new fingerprint as banks investigate using voice biometrics as an authentication method.
Expect to see more companies invest in voice-based user experience and security measures, which rest upon Natural Language Processing and other AI subdisciplines.

Compliance and Information Security

As a highly regulated industry, banks and financial institutions have to meet stringent information protection requirements. On top of this, they have a legal and ethical obligation to their clients; thus, information security must be taken seriously.
Once again, we’re looking at an area where AI and machine learning (ML) are well-documented. In this case, AI technologies play a dual role; AI can automate the transfer of information, reduce human error, and increase security in transit, while ML fulfills traditional IT security activities like monitoring, identifying potential security threats, etc.

Fraud Prevention, Anti-Money Laundering, and Process Automation

Process automation – such as using text recognition to facilitate document capture and data entry – has many potential applications across the financial industry. The general task of business process automation is one of them; like other companies, banks can use this to automate time-consuming manual workflows and reduce expenses. However, there are several automation applications specific to the financial sector, e.g., credit or loan application processing, Know Your Customer checks, report generation, general ledger preparation, and validation, etc.

AI’s role in fraud and money-laundering prevention is of special interest here. As with the security issues mentioned above, its pattern-spotting abilities can be tremendously valuable in the early detection of suspicious activity – especially with very small anomalies that humans might ignore. By learning customers’ behavior and transaction patterns, AI can quickly flag unusual movements and alert banks about potential problems. It can also significantly improve the investigation of possible fraud and money-laundering activities, helping financial institutions limit (and possibly recover) damages.

Lending and Risk Management

AI can process more complex and sophisticated rules than traditional credit scoring systems. It can also help banks and other lending institutions distinguish between high-risk applicants because of defaulting on loans and those who are high-risk because of having little or no credit history.
Additionally, AI can help speed the lending process at several stages: by pre-screening applicants and the automation of application processing, by automating underwriting and disbursal, and using data analytics to understand customer behaviors and needs deeply. Thus, AI technologies not only shorten timeframes but also allow banks to provide more personalized services and offers to their customers.

AI and the Future of Banking

From these insights, it’s quite clear that the future of banking will continue to lean into digitalization and technology. Customers demand instant, personalized attention; security and regulatory demands require constant (and constantly improving) monitoring and action; emerging trends like blockchain and cryptocurrency demand investigation. Without technology, the needs of modern banking are daunting. But with AI, it’s possible to stay connected, relevant, and competitive even in a changing landscape.

Authored by: Dr. Anil Kaul, CEO of Absolutdata


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