Issue link: https://maltatoday.uberflip.com/i/1265531
02.07.2020 9 OPINION Alexiei Dingli Prof Alexiei Dingli is a Professor of AI at the University of Malta and has been conducting research and working in the field of AI for more than two decades, assisting different companies to implement AI solutions. He forms part of the Malta.AI task-force, set up by the Maltese government, aimed at making Malta one of the top AI countries in the world O ur banking system is today facing increased competition. Innova- tive services are on the rise, thus making the traditional banking we have known for decades slowly obsolete. ere seems to be a drive for more self-service round the clock banking services, which are cheaper and more convenient for the customers. All of this is happening within a global scenario where compliance is becom- ing much more stringent, and security risks are increasing exponentially. Fi- nally, with transactions happening at the speed of light, the volume of data is growing at record speed, thus mak- ing effective decision making difficult. Of course, all of these goals may sound daunting for traditional banks, but they can be easily achievable with the help of Artificial Intelligence (AI). Let us have a look at the technologies which are transforming traditional Banks into Fin-tech organisations. Digital banking assistants offer users financial coaching and access to the var- ious services provided by the bank. One can consider them as being a personal- ised cashier that knows the clients indi- vidually on a first name basis and is ready to give them all the information they de- sire at the click of a button. Such systems make use of Human Language Technol- ogies (HLTs) which converse with the user using a natural language (such as English, Chinese, etc.). is technolo- gy increases the overall user experience drastically since the user interacts with the virtual assistant as if he is speaking with another human. Furthermore, the assistant is capable of upselling other banking products, thus helping the cus- tomer to explore new possibilities. Client Profiling is another area where AI can assist. By going through their demographic and historical data, banks can automate the categorisation of cli- ents based upon their risk profile. Advi- sors can then use this information to of- fer clients different financial products in an automated way and based upon their profile. e advantage of using such a system is that the client is not subjec- tive to data-induced bias. Furthermore, since the AI is continuously updating the profile of the client, it can immedi- ately notice any growing risks and alert the bank before it is too late. Contract analysis is a somewhat repet- itive task which takes a lot of resources. Because of this, Managers and advisors can assign this task to an AI assistant. Optical Character Recognition (OCR) can be used to digitise the documents (both typed and handwritten) and send them to the contract analyser. e Nat- ural Language Processing (NLP) mod- ule will then interpret the text, analyse it and apply business rules. e business rules applied can vary; from straight- forward ones (like checking the status of checkboxes) to extremely complex ones (like checking the logic behind the text). e AI model uses past con- tracts for training, thus increasing its accuracy drastically. Large companies like JP Morgan report that using such an approach; they managed to con- dense 360,000 hours yearly of work into a few seconds. Once the system com- pletes the processing, it provides alerts with suggested corrections at very high speed which are reviewed by Managers or advisors. Customer churn is another major headache in such a competitive envi- ronment. AI can be beneficial in pre- dicting churn based upon the client's interaction (or lack of it) with the bank. e system can quickly analyse all the data about a client, make a prediction and creates a prioritised list of clients who will probably terminate their busi- ness with the bank. e manager can then intervene directly with the clients in the hope of retaining them or at least, understand why they opted for a com- peting bank. Research shows that it is much more difficult and expensive to acquire a new customer than retaining an existent one. Mass marketing fails in these situations because customers are so diverse that the message will not get through. us, customer analysis and churn predictions are vital to creating marketing initiatives specific to par- ticular customers. Algorithmic Trading uses AI tech- niques to trade shares, stocks, etc. It achieves this by analysing data coming from different sources such as past his- torical data, news items, etc. and taking incredibly fast decisions. e patterns found in this data is complicated to spot by a human, or it is physically impossi- ble for a person to process that tsunami of information promptly. Of course, a computer can automatically execute trades rather quickly and secure a sale or a purchase at lightning speed. Automated Research tools handle the background research necessary to ap- prove or decline financial investments. is task is extremely time-consuming for a human to do, but for an AI, it is rather simple. e system is capable of performing sentiment analysis on infor- mation about individuals or companies. It can detect if people have a negative or positive sentiment about the entity and thus provide managers with critical in- formation. Advanced language process- ing techniques can help researchers get a quick overview of a company's finan- cial reports by zooming-in on crucial topics and automatically highlighting specific passages. Automated Valuations of investments is another application of AI. Using var- ious features such as age, historical val- ues, etc.; the system can calculate the worth of an asset. Traditionally, such a system was initially used in real-estate to calculate the valuation of houses. However, financial firms adopted sim- ilar approaches by looking at economic indicators, growth predictors, etc. to reach a final estimate. ese were just a few examples of where the banking sector is using AI. In the coming years, we expect to see many more innovations dealing with the operations, marketing, sales, cus- tomer experience, revenues and quality of deals amongst others. AI is a tool that is changing the way we bank forever, and it is ushering the era of modern banking. Our banks cannot stand still, or they will die. As the old Chinese proverb goes "Be not afraid of growing slowly; be afraid only of stand- ing still." Reinventing banking in the new decade using AI