The Infosys Labs research blog tracks trends in technology with a focus on applied research in Information and Communication Technology (ICT)

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Artificial Intelligence & Financial Services - The Applications

In my previous blog "Artificial Intelligence & Financial Services - The Business Case" we explored the business case for adoption of AI in the financial industry. In this blog we will look at the technology, its applications and its adoption by the industry.

The most mature use cases are in chatbots in the front office, antifraud and risk and KYC/AML in the middle office, and credit underwriting in the back office.

Front office operations have leveraged chatbots to revolutionize customer relationship management. Other than assisting customers with their transactions, chatbots enable banks to segment customers individually rather than general buckets by collecting data regarding their behavior and habits. Infact, Nina, Swedbank's AI chatbot was deployed to assist customers 2 years ago. Already, Nina has successfully demonstrated its ability to resolve 78% contact resolution and has a customer adoption rate of 30,000 conversations per month. By 2024, 42.82% of the estimated $1.25 billion market for chatbots is expected to be generated by the rising need for enhancing the customer services to retain existing customers and attracting potential customers.

Similarly, AI based anti-fraud and KYC/AML applications have been gaining traction in middle office operations thanks to the superior cognitive capabilities of AI. The digitization of banking products and services has led to an increased susceptibility to fraud. Using AI significantly reduces the time taken to review transaction, including all the factors and relevant data associated with it. Lloyds Banking Group is using AI models that detect when the person logged in is not the customer, but a fraudster or a bot. Similarly, Natwest has been using AI to reduce fraudulent transactions and reported that AI has prevented 7 million Pounds of false payments.

Back office operations too are undergoing a change. AI is used for applications such as credit and risk underwriting in the back office by creating a more complete and unbiased assessment of an applicant's credit worthiness. AI based underwriting provides a more comprehensive view of the assessee' s credit worthiness. Startup, Lenddo has already enabled their partners to assess 5 million applicants through the 12,000 variables collected from alternative sources.

AI has also been widely adopted by hedge funds for algorithmic trading, AI collects data from several sources to create a more accurate prediction. They are also being used by banks to discover investment opportunities by scouring the markets. CircleUp, a venture capital firm has created Classifier, a machine learning crowdfunding platform to determine which companies to fund. The Classifier has the capability to review 500 opportunities per month with a team of less than 10 analysts vs the 500 evaluations per year done by the average private equity firm.

While chatbots, anti-fraud, risk management, KYC/AML, credit underwriting and asset management are being adopted by the financial industry, the other applications are generating a lot of interest and it won't be long before they too go mainstream. With AI estimated to add more than 1 trillion in value to the financial industry it won't be long before robots cater to our financial needs while algorithms manage our daily finances.


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