The world of banking and financial services may remain one of the more conservative sectors of the economy today but if organisations operating across these marketplaces want to drive competitive edge and business advantage in the future, they can no longer afford to ignore the consumer-driven pull towards the use of artificial intelligence (AI).
People are used to these technologies in their everyday lives. They are used to smart software telling them what they want to buy next even before they realise it themselves.
Today, it’s increasingly vital that banks, financial services organisations and financial departments within enterprises are all in touch with these trends. They need to start looking at the benefits that analytics and other predictive technologies can bring them. Their employees and customers will expect them to do so.
We are already seeing AI widely used in consumer banking. And it seems that is something that many consumers broadly welcome. A recent Accenture survey of 33,000 consumers across 18 countries found that more than 70 per cent would be willing to receive computer-generated banking advice. “Comfort with computer-generated support is growing, bolstered by lower costs, increased consistency and high reliability,” said the report. “Automated servicing can be the sole source of data for some customers, even when making more complex decisions around products.”
In consumer banking, chatbots are increasingly seen as cheap alternatives to banking apps, and they are increasingly prevalent as result. Major Singaporean bank DBS, for example, recently launched the POSB digibank Virtual Assistant, powered by the KAI conversational bot/artificial intelligence (AI) platform from New York-based fintech start-up, Kasisto. The POSB chatbot is currently available on Facebook Messenger and can answer questions relating to account balances, utility bill payments and fund transfer requests. WhatsApp and WeChat versions are set to follow.
AI is about automation
This kind of approach to banking interaction becoming second nature to millenials and will become even more widely accepted by the generations that follow them.
But what will all of this mean in a commercial finance environment?
The business sector is understandably more cautious, prudent perhaps, about adopting new technologies until they have matured. But as millenials increasingly take up more senior roles in the commercial banking world, they will be increasingly pushing for the rich functionality they are used to there to also be integrated into their working environment and ecosystem.
Today, we are seeing signs that adoption rates of AI-based technology are set to take off in business banking too. More and more banks are borrowing retail banking experience to build out their commercial and business strategies. But while the focus of its use in the retail banking world has mainly been for customer service and sales applications, in commercial banking, use cases (initially at least) are likely to be more around streamlining operational processes.
In a sense, AI as it stands today, in this environment is all about automation, about making processes faster and more efficient. And there are a raft of applications here where automation is having a hugely positive impact.
Take the introduction of digital expenses platforms and integrated payments tools, both of which have the potential to significantly improve a business’s approach to how it manages cash flow. By having an immediate oversight, through live reporting of all spending from business cards and invoice payments, as well as balances and credit limits across departments and individuals, businesses can foresee potential problems more quickly and react accordingly. All these services become even more powerful when combined with technologies like machine learning, data analytics and task automation.
We are already seeing growing instances of AI and automation being used to streamline payment processes in banks. Cards can be cancelled or at least suspended quickly and easily and without the need to contact the issuing bank, while invoices can also be automated, to streamline business payments. This means businesses can effectively keep hold of money longer and at the same time pay creditors more quickly. Moving beyond straightforward invoice processing, intelligent payments systems can be deployed to maximize this use of company credit lines automatically.
Looking ahead, we see a raft of applications for AI in the payments management field around analysing data with the end objective of spotting anomalies in it. With the short and frequent batches of payments data used within most enterprises today, it is unlikely that even the best trained administrator would be able to spot transactions that were out of the normal pattern. The latest AI technology could be used here to tease out anomalies and pinpoint unusual patterns or trends in spending that could then be investigated and addressed.
While this area remains in its infancy within the banking and financial services sector, with technology advancing, financial services organisations and the enterprise customers they deal with will in the future will be well placed to make active use of AI that will help clients track not just what they have been spending historically but also to predict what they are likely to spend in the future. AI will ultimately enable businesses to move from reactive historical reporting to proactive anticipation of likely future trends. We are entering an exciting new age.
Russell Bennett, CTO Fraedom