Driving Customer Delight in Corporate Banking with Intelligent ...

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Driving Customer Delight in Corporate Banking with Intelligent Automation

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It is often reported that it costs five times more to attract a new customer than it does to keep an existing one.  Yet, in today’s hyper-competitive business environment where customers who already demonstrate low levels of loyalty and are presented with virtually unlimited choice, many financial services firms fail to show that they truly understand their customers’ needs. Even worse, many banks fail to engage with customers on their terms, or take swift action based on their feedback. The challenges are well known, the solutions less so, but technology can help.

 

Banks worldwide are increasingly looking to intelligent automation solutions – not only to help make their processes better, faster and cheaper, but to deliver insight into what customers are doing today and what they are likely to do tomorrow. Intelligent automation solutions turn a torrent of raw data into streams of actionable intelligence that can be applied in order to continuously improve customer experience.

 

According to KPMG, enterprise investment in intelligent automation technologies – which includes artificial intelligence, machine learning and RPA – is expected to reach $232 billion by 2025 compared to an estimated $12.4 billion today. Banks have already started leveraging artificial intelligence to improve customer experience for millions of retail customers, but the technology is just making its way to corporate clients, who present bigger challenges for artificial intelligence programmers. For instance, while a retail customer typically has a handful of accounts, a company could have thousands of accounts in dozens of currencies around the world, with each individual corporate user typically having role-based access.

 

There are four key areas where banks can leverage intelligent automation to provide an outstanding experience for their corporate customers:

 

1. Delivering a better on-boarding experience: An average corporate on-boarding often requires up to 100 documents, takes up to 34 weeks and costs USD 25,000 per client. Complex and time consuming on-boarding processes increase abandonment rates, in fact according to Aite Group, as many as 15% of new customer applications are abandoned before on-boarding is complete. Banks are now increasingly looking at AI-driven automation to streamline the manual tasks required in client on-boarding and after-sales client service today.

Last year, JP Morgan introduced an artificial intelligence tool that eliminated an estimated 360,000 hours of work each year previously done by lawyers and financial loan officers in reviewing and scoring commercial loan agreements. The same tool could, in essence, be used for various on-boarding tasks such as processing and lodging documents and assessing standard terms and conditions in product agreements.

 

2. Providing high quality financial advice: In June this year, JP Morgan’s Treasury Services launched a new pilot program for an artificial intelligence-powered virtual assistant. Claimed to be a world first for corporate payments, the program enables the client to simply ask for information on balances instead of navigating through some of the website’s 1,200 pages to do things like send wires or export data from multiple accounts in order to determine balances. Eventually the virtual assistant will also learn the clients’ behavior and will ultimately be able to make recommendations.

With fintechs gaining ground over traditional banks by providing specialized solutions with superior digital capabilities, banks stand to lose significant non-interest income, unless they differentiate themselves. However, with access to their customers’ transaction history and the knowledge of their financial assets and liabilities, banks can leverage artificial intelligence and advanced analytics to provide value-added advisory services for their customers’ cash management activities. The advice could be on regular activities such as suggesting the execution time of account payables and receivables, identifying which supply chain partners should be offered discounts, providing guidance on the most cost effective way of working capital financing and making optimum use of idle cash and even longer-term agendas covering areas such as risk reduction and hedging strategies. Banks can continually improve on the quality of advice through machine learning while neural networks can assist in creating advice not just with the customer’s own data, but industry and global economic data as well.

 

3. Ensuring excellence in customer service: Delivering contextual insights to the right customer at the right time through their preferred channel is crucial to the success of the bank’s customer service interactions. With artificial intelligence powered chatbots, financial institutions can create a differentiated experience for their customers by combining knowledge across all relevant segments and providing better insights. In fact, according to Gartner, by 2020 chatbots will be handling up to 85% of all customer service interactions.

 The usage of the chatbot as a new-age contact centre executive will also reduce the time it takes to reply to customers while dramatically cutting costs. According to a report released by Juniper, chatbots will be responsible for over $8 billion annual cost savings by 2022. Some chatbots even leverage neural network-based language models to classify the intent of a sentence by the customer- either casual or business, and respond in an appropriate manner. This can enable corporate customers to move to a new level of conversational banking where results are delivered instantly through real-time conversations, thus facilitating better decision making.

 

4. Making financial transactions safer: As customers’ expectations of real-time financial services constantly increase, so too does the potential for mistakes and fraud. The 2018 AFP Payments Fraud Survey revealed that a record 78 percent of all organizations were hit by payments fraud last year. Given the interconnectedness of various stakeholders in the payment ecosystem, not only does fraud result in financial losses and reputational risk but it can also undermine confidence in the entire system. In the past financial institutions typically focused on the quantification of financial impact when fraud or duplicate transactions were detected. However, advanced analytical tools with built-in machine learning capabilities can enable financial institutions to do much more. Duplicate transactions can be captured swiftly and potential instances of fraud can be intercepted and stopped before they happen, thereby increasing the effectiveness of fraud monitoring programs.

Natwest Bank recently reported that it was able to prevent £7m of corporate fraud using a machine learning system. A number of banks including HSBC, Danske Bank and OCBC have already deployed AI to monitor frauds whereas others like Bank of America are in the early stages of experimenting with how artificial intelligence could help improve their fraud detection efforts.

 

The shortcut to outstanding customer experience?

The Forrester Customer Experience Index states that a change in customer experience ratings for a multichannel bank leaves $124 million on the table for every 1-point decline in its CX Index score. If banks are unable to provide their customers the experience they want, their historical central role may soon turn out to be history. Intelligent Automation could well be the silver bullet banks are looking for to deliver an outstanding customer experience and retain their position as their customers’ principal bank

 

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About the Author

Avik Dasgupta

Avik Dasgupta leads the transaction banking and analytics solutions marketing at Nucleus Software. With over nine years of IT marketing experience, Avik has authored several blogs and articles on BFSI and travel technology innovations. He has worked in leading firms like Polaris Financial Technology and Cognizant Technology Solutions prior to joining Nucleus Software. Avik has an engineering degree in Information technology from Mumbai University and a management degree in Marketing from the Institute of Management Technology, Nagpur.

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About Nucleus

At Nucleus Software we are committed to providing efficient, modern yet proven software solutions for the global Banking and Financial Service industry. We have been pioneers in developing Retail Banking Software, Corporate Banking Solutions, Transaction Banking, Cash Management and Internet Banking Software since 1986. Our success spreads across more than 50 countries, and we serve our customers globally through our direct and partner operations across US, Europe, Asia-Pacific, Africa and the Middle East. We are known for our world-class expertise and innovation in lending and transaction banking technology. Our two flagship products, built on the latest technology are: FinnOne™ and FinnAxia™.