5 use cases for AI in banking (beyond those helpful chatbots)
Artificial intelligence is already changing the face of banking. In many cases, banks are literally using AI-powered chatbots to present a face to customers other than a bank employee. However, it is worth noting that chatbots are not the only way banks can use AI to improve their propositions – and, indeed, just because a bot is chatting to customers doesn’t mean banks are powering it with the right intelligence.
The area of AI that will most impact chatbots – and the whole help and support sphere – is NLP, or Natural Language Processing. This is machine learning technology that, over time, processes inputs and behaviour to find trends and, eventually, ‘understand’ human language. Until this technology is perfected and deployed to banks’ chatbots, we will still be faced with (essentially) fancy decision trees, which simply give us a different way to navigate help and support.
There are several different ways that AI can be used by banks to acquire, engage and delight customers. Here are five of them.
1. Personal financial management
Personal financial management is currently going through a sea change, with PSD2 opening up new possibilities for banks in terms of what they can do for customers once they have access to all of their financial information. On top of this, AI has the potential to help PFM platforms go even further. One of the best ways AI can improve personal financial management is in the field of spend forecasting, using customer data going back weeks, months and years to offer customers realistic predictions of how much they will spend in coming months, which helps them to determine where they can cut down and make savings. Some platforms, such as Yolt and Pariti, already offer this type of facility, but there is a long way to go before the information can be considered reliable enough to entirely depend on.
In theory, AI is an advertiser’s dream. The digital footprint of each individual is enormous, meaning that there is a massive amount of information waiting to be harnessed by banks. Given that traditional audience segmentation is falling away, AI can revolutionise how banks look at customer data in order to make huge strides in being able to offer a unique, personal experience, in line with what customers are beginning to expect. They can utilise AI to process the data in order to produce tailored advertising based on the lifestyle and preferences of every customer.
The natural next step from banks using AI to personalise their advertising is using it to provide recommendations to customers. While this facility already exists, banks are, in general, not utilising it to provide tailored product recommendations for their customers. As ever-improving AI helps banks understand their customers’ individual habits, pain points and life goals, banks are in an ideal position to develop a much more personal relationship with their customers, becoming trusted partners in their lives. If they can achieve this, banks will have the potential to hold on to customers for positive reasons, as opposed to the customer apathy towards banking that stops many customers from changing providers at the moment.
4. Security (Fraud Detection)
While AI is currently very trendy in the financial services world, it isn’t brand new. Customers will be most familiar with it being used in fraud detection, with many having experienced having a card transaction declined followed by an almost-instant automated call or message from their bank to discuss irregular activity on their account. When fraud has been correctly detected this process is extremely satisfying, but when the bank has misunderstood and blocked a safe transaction, while feeling reassured that their bank is keeping a close eye on security, customers find the situation inconvenient and annoying. While current systems are relatively effective at detecting fraud, improvements in AI via machine learning and big data analysis will continue to improve the accuracy of fraud detection, eliminating the inconvenience and annoyance associated with wrong calls.
5. Financial advice
The area where banks have the most to gain, but also a huge amount to lose is by employing AI to give financial advice to customers. The complex regulation around giving financial advice will deter those who are less than fully convinced by the potential of AI. However, banks cannot afford not to move forward with AI-driven advisory solutions. Tech juggernauts such as Google, Facebook and Amazon are moving at great speed when it comes to using AI and already encroaching on the territory of banks. Over a relatively short period of time, they have built brand recognition that has already overtaken banks, and while customer trust is not yet at the same level for them as it is for banks, the greater role they play in the everyday lives of consumers, the easier trust will come. Companies such as this are much less wary of regulation and will not hesitate in developing platforms that move them far ahead of banks.
As noted in Financial Brand: ‘With an origin rooted in risk and fraud detection and cost reduction, AI is increasingly important for financial services firms to be competitive. The digital consumer is being trained by firms that are becoming masters of AI (Amazon, Google, Facebook and Apple) and expect the companies they use to know them, understand them and reward them through personalized communication.’