SINGAPORE (Dec 6): Artificial Intelligence (AI)-based applications are making its way into every area of our lives today, playing very important roles.
In recent years, Singapore’s financial services industry has also been at the forefront of developing and adopting AI technology in their businesses.
The Monetary Authority of Singapore (MAS) recently announced that it has rolled out a $27 million Artificial Intelligence and Data Analytics (AIDA) Grant under the Financial Technology and Innovation Scheme (FTIS) to promote the adoption and integration of AI and data analytics in financial institutions island-wide.
According to SAC Advisors, there are five key applications of AI in the financial industry:
1. Anti-money laundering pattern detection
Local banks have been working with local startups to combat money laundering and terrorist financing issues. OCBC has recently conducted a trial run with AI startup Silent8, which has provided the bank with its technology that is able to detect potential money laundering cases 10 times faster than the bank’s current processes.
2. Chat bots
AI-based automated chat systems that can communicate with humans without human intervention are now a common occurrence in several banking platforms. OCBC is also working with local startup CogniCor, which has developed a chat bot called Emma. The chat bot specialises in home loans and has helped the bank signed on about $70 million worth of home loans so far.
3. Algorithmic trading
Many hedge funds are now using AI to generate returns. These AI systems make investment decisions by analysing large amounts of data from the financial market. According to SAC, reports have claimed that more than 70% of trading today is carried out by AIsystems.
4. Fraud detection
Fraud detection has been proven to be the most successful AI-based application in the financial industry, according to SAC. Sumitomo Mitsui Financial Group is also collaborating with Google to explore using AI for credit card fraud detection at Sumitomo Mitsui Card Co (SMCC), reducing the investigation load associated with transactions being flagged as suspicious by conventional means.
5. Customer recommendations
Recommendation engines are the main users of AI in the financial services industry. It utilises historical data of users and offerings, such as credit card plans and investment strategies, from the bank to make appropriate recommendations to users, based on that particular user’s preferences and past history.
As much as the applications of AI has had its benefits to the financial services industry, the industry still faces some challenges.
Firstly, who owns the data that is essential to AI?
Many financial institutions partner with other entities for their AI solutions that collect, store and process data. This complicates the data privacy issue. Agreements are also difficult to construct and interpret, while strict limitations on data usage can be difficult to enforce.
Secondly, finding out what an AI program has learnt and how this would affect its decisions is difficult. Despite existing laws and regulations in place, grey areas are increasing.
Lastly, AI is vulnerable to cyber attacks as its basic info, consisting of big and commingled data, is needed to form new information creates a growing attack surface.
Commingling of data makes it difficult and costly to track the respective sources of the data, whether the data contains PII (personal identifiable information) and how these data can be used.
The reality about AI is that it is here to stay although many argue that jobs may be replaced by machines, causing an increase in unemployment rate.