Five Impact Areas That Should Not be Ignored

The banking industry is undergoing a transformation with artificial intelligence (AI) at its heart. Not only does AI impact the way banks conduct traditional banking operations, it also enables the delivery of smart new banking services.

Financial services organizations understand that customers expect the same frictionless experience from their banks that they enjoy in other areas of life, notably online shopping and social media. But it’s important to recognize that the benefits of AI go way beyond the front-end of service delivery deep into fundamental process automation.

  1. Improved Fraud Detection

Fraud and cybercrime continue to be a serious concern for the financial services industry. Such incidents can impact the bottom line but also damage a bank’s corporate reputation. The rise of e-commerce and digital payments means that the types of fraud that are now possible necessitate the adoption of ever more sophisticated anti-fraud protection measures.

This has created a Catch 22 situation for banks, where adopting a very aggressive approach to fraud prevention potentially costs more than the fraud incidents themselves. Banks run the risk of not only losing customers but also of paying damages for legitimate transactions that were declined. This is where AI can bring real value to the financial services industry.

AI-powered solutions can analyze large volumes of security data to identify possible fraudulent behavior and suspicious transactions before they are enacted. Machine learning algorithms can detect fraudulent transactions that can be missed by human intervention alone. They now work beyond predefined rules and are able to pick up patterns from historical behavior to identify possible fraud – flagging it up in real-time.

2.    Chatbots for a Personalized Banking Experience

In recent years, customers have embraced self-service channels that allow them to have more control over their experiences with a brand. Rather than waiting in a lengthy queue to speak to a customer service advisor, they increasingly opt to use automated interactive voice response (IVR) or chatbots.

Banking AI chatbots are now moving beyond the realm of just allowing customers to have useful but relatively simple conversations with a brand. When linked with a bank account, chatbots can analyze income and spending patterns and share useful analysis and insights. They can act as personal digital accountants and offer relevant financial planning tips.

Chatbots are already transforming the way customers interact with their bank by making  financial services more personalized and conversational. The first level may have been simple Q&As that alleviated pressure on contact center staff, but AI is also adding value in more sophisticated areas such as robo-advice in investment management.

3.    Automation & Operational Excellence

The need for precision and security means that banking processes have traditionally been both complex and  time-consuming, with  a lot of documentation and paperwork involved.

Although AI technology has not yet evolved to a level where it can replace a human, it can certainly automate processes and accelerate them. It can generate reports faster without any errors, identify breaches to corporate policies and flag them up faster, and also route documents and  information more quickly around the organization as well as externally.

Increased levels of automation of banking processes have:

  • Expedited service delivery times
  • Reduced human errors
  • Made operations more efficient

4.    Customer Intelligence

The huge opportunity presented in today’s era of Big Data is the ability to build accurate and detailed customer insights. The banking industry has always held a treasure trove of data, but this has often been under utilized due to the fact that it sits in different silos and is difficult to access and analyze in one place. AI now makes it possible for banks to combine customer data from structured and unstructured sources into a standard format and then analyze it for more insights.

Machine learning algorithms allow banks to gain valuable customer insights which are not only actionable but also contextual. AI-based tools help create a better understanding of customers and their behaviour patterns so the need for new products can be predicted and fulfilled. They can also be used to identify potential shortfalls in customer satisfaction and trigger subsequent marketing strategies and engagement programs.

As well as helping banks create more relevant and personalised products and services, insights can be used to make more informed strategic decisions and reduce risk.

5.    Accurate Market Predictions

Every bank depends on forward-looking economic and market reports. A human analyst may find it overwhelming to analyze current market trends, identify hidden yet evolving opportunities, and predict them in time for the bank to respond and make the most of emerging trends.

Using AI, analysts can sift through huge datasets from multiple sources more accurately and more quickly.  AI can help identify patterns to support a human analyst, make connections with historical data, and predict future behavior.

Conclusion

The banking industry has been talking about process automation and data analytics for a long time. AI is the lynchpin for the delivery of both these concepts. AI bots make automation possible, and machine learning raises data science to the level of Big Data.

AI is not about replacing humans in the banking industry, or about simple cost reduction. It is about freeing up humans from mundane tasks so that they can focus on the core activities where a personal touch is needed. By considering the five impacts outlined above, banks can start making the most of the opportunities that AI presents – or risk being left behind.