Artificial intelligence (AI) has already become an everyday part of our lives. We use it at work and at home – often without even realizing it. AI is evolving now in all industries especially in the banking sector, 2018 will showcase many projects and applications that are adopting AI to increase their performance and security in all terms.
In the past few years almost all the tech giants have started using and promoting AI in their applications, and embedding it into their processes and new releases. Oracle; for example, the software giant announced its autonomous database 18c in Oracle Open World 2017 which will run and manage all of it’s patches by itself without the need of the DBAs, Oracle is just one of so many other software companies which have started promoting the use of AI.
The banking sector has realized that it has to adopt AI into its processes and applications as fast as possible as the outcome of this technology will enrich the customer experience in many areas; it will also increase customer confidence and engagement, which will enable banks to know their customers and provide guidance on how and what services to offer them.
Banks should take into consideration the following key factors when implementing AI to guarantee its success:
a) What will be the ROI for such projects?
b) How many data sources are available for the project?
c) Are all data sources trusted?
d) What is the accuracy and the speed of the decisions taken by those applications?
AI can be implemented the following areas:
a) Fraud management
b) Anti-money laundering
d) Investment research
e) A personalized banking experience
f) Credit scoring
g) Trading assistance
Today for example, many banks have implemented a chatbot agent which is used to communicate with their customers, but those agents are not intelligent or sufficient enough to act or decide like a human due to the huge amount of information required, but in the future, that machine should keep on learning until it reacts by itself.
Fraud management and anti-money laundering platforms are that most interesting areas to benefit from AI. In security for example, banks can benefit from it to monitor and protect all kinds of financial transactions which will give the ability to such systems to act like a human being by or even better, all of that can be achieved by teaching machines effectively, and feeding them with the largest amount of data needed to make better decisions and recommendations.
Blockchain, on the other hand, should be a good source for data used in machine learning as all transactions are logged; in addition to it’s sources, these are stored in the blockchain network, by this, the banking sector can benefit from such technology to be the source for information. In addition, the blockchain network and its connected applications will be monitored by fraud management solutions that are controlled by AI software. In the future the whole ecosystems will connect to each other to provide secure, fast and cost-effective transactions for both clients and banks.
We need to take into consideration that blockchain technology is still not implemented effectively in real life yet, but will certainly grow in the next few years. It’s expected that in the year 2018, many banks and fintechs will start doing PoCs in blockchain technology which will give AI more time to be able to benefit from the data collected from blockchain networks and nodes until these applications become mature. Meanwhile these applications can be built, controlled and monitored by AI
Banks can deliver personalized offers and products for customers therefore providing them with the best experience using AI; this can be achieved based on the amount of data collected, which is why big data is a very critical factor in enabling AI applications to make better decisions and offers. These offers should be designed and promoted in an attractive way without giving the impression that it was built based on a Facebook post for example, or by making the client feel that the bank is spying on him as this is a very critical point for a majority of customers.
The move to open digital branches with no employees is the first step for banks to become smart, as it will speed up the transaction process and enhance the customer experience, but this cannot be achieved easily without multiple AI technologies implemented. The customer journey inside the smart branch should be studied very carefully as many banks failed either because they didn’t choose the correct location, or they were depending on human agents in the background which caused delays in the transaction process.
The whole world is connected to each other, and governments are seeking to create a centric profile for citizens which includes payments, transfers, personal data …etc., Banks can benefit from this huge amount of trusted data and other data sources like social media and data warehouse applications, which can be used for machine learning for better results using AI which will end up with more revenue sources for the financial institution.