graphic by MZUKRI
YOUR former school mates are your Facebook friends. A few of you get together for a drink. One of your friends snaps a photo on his smartphone camera and puts it up on his Facebook page.
You get tagged automatically. This automatic tagging is possible because Facebook recognises your photo image and is able to associate your image to your profile. This is an example of machine learning in software application. Machine learning is a subset of artificial intelligence (AI).
Clara Durodie, a renowned thought leader in the field of applied AI, defines AI as the “theory and development of computer systems able to perform tasks that normally require human intelligence such as visual perception, speech perception and decision making under uncertainty.”
She adds the scope of AI includes machine learning, natural language processing, image and speech recognition.
Let’s focus on machine learning. While machine learning could be applied to just about any industry, financial services have been identified as one of the sectors that could benefit greatly.
Machine learning could apply to credit decisioning, risk assessment, fraud prevention and process automation.
Of all these applications, machine learning’s unique capability in gearing financial institutions towards personalised customer services — especially as customers are demanding for more and more personalised approaches — is intriguing. These personalised services could be reactive or proactive.
Reactive means financial institutions would recommend products or services based on instructions from customers. To narrow down the options, financial institutions may even ask the customers to answer specific questions.
Based on the instructions and the answers, machine learning logic would be applied to come up with recommendations. Such solutions have been deployed by online investment advisors better known as robo-advisor.
For example, a Shariah-compliant robo-advisor in the market uses neural network machine learning technology to pick stocks from Shariah compliant S&P500 Index.
Proactive personalised services, on the other hand, refer to recommendations to customers based on intelligence drawn from his or her own data.
While this is not yet prevalent, the potential is huge because financial institutions collect tonnes of data on a daily basis.
For example, a typical salaried person would have his salary credited to a bank account once every month. Soon after getting the salary, the person would be logging on to online banking facilities to settle his or her monthly commitments such as loans and bills.
The person may also make payments for investments and some other purposes. These would enable financial institutions to collect not only general banking information such as account balances and transactions, but also data on purchases, spending habits and channel usage. On top of that, they can even determine geolocational preferences.
Applying machine learning techniques to the insights drawn from these data, financial institutions could proactively recommend financial solutions to customers. For Shariah-compliant purposes, Islamic financial institutions could limit the options to Shariah compliant products and services only.
For example, if data shows the customer is making payments to a conventional credit card — a specific Shariah- compliant credit card product could be recommended. If there are balances idle in saving and current accounts — a Shariah- compliant investment products could be recommended.
As the financial services industry is going through a transformational journey with the comprehensive use of advanced technology such as AI — Islamic financial institutions need to be part of the game.
To get started, Islamic financial institutions could put together a strategy to focus on some AI applications such as machine learning on existing assets in the shape of customer data. This would enable Islamic financial institutions to give personal touch and improve customer services.
Othman Abdullah is CEO for Islamic banking and innovative services delivery at Silverlake Sprints Sdn Bhd, a unit of the Malaysian-based Silverlake Group. The views expressed are of the writer and do not necessarily reflect the stand of the newspaper’s owners and editorial board.