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

« Journey towards Adaptive Care | Main | Sports and Technology »

Artificial Intelligence & Financial Services - The Business Case

Artificial Intelligence & Financial Services - The Business Case

The new wave of innovation and technology commonly referred to as "fintech" is reshaping the financial services industry and forcing the critical financial intermediaries to adopt emerging technologies. AI has been the focus of financial institutions due to the opportunities arising from the rise in volume of data, speed of access to it and the emergence of new and advanced algorithms able to analyse data in a more intelligent. Industries are leveraging the technology to gain a competitive advantage against their peers by improving speed, cost efficiency and accuracy of processes and meeting rising customer expectations.

The highest adoption rates of AI in financial services companies are in IT with 63.5%, finance and accounting with 40.4%, marketing with 31.4% and customer services with 30.8%. Challenges with the adoption of AI in the financial service industry has been the auditability and traceability of the applications. Financial institutions have to comply with regulations requiring them to explain their decisions to customers and report the same to regulators.


Cost savings is expected to be the primary driver of AI in the financial industry, analysts estimate that AI will save the banking Industry $1 trillion in savings by 2035 with most of the savings coming from the front office. Although the changes are predicted to be gradual until 2025, the adoption rate is expected to accelerate until 2030.


Reduction in the scale of retail branch networks and other distribution staff will generate most of the savings in the front office with $199 billion. Chatbots are expected to take over and handle upto 85% of the world's customer interaction. Chatbots are already being leveraged to help customers manage their personal finances, provide investment advice and suggest the best product for the customer while enabling the customer to perform simple transactions effortlessly.

The application of AI for compliance, KYC/AML and data processing is forecasted to save $217 billion in the middle office. One of the mature applications, KYC/AML uses pattern detection d unstructured text analysis to identify potential fraudulent activity in real time while identifying complex linkages between entities.

Back office operations are also expected to generate $200 billion in savings of which $31 billion will be generated through the application of AI for underwriting and collection systems. AI enables underwriters to collect data from alternative sources such as social media and geolocation data enabling to assess candidates with limited credit history and speed up the entire process.

Applications of AI range from customer service through AI assistants to process automation tools for eliminating time intensive work. Irrespective of whether its intelligent automation for repetitive manual tasks, the enhanced judgement and improved interactions provided by AI is the future of the industry and will drive enterprise growth and profitability in the years to come.

In my next blog "Artificial Intelligence & Financial Services - The Applications", we will dive deeper into the application of AI in financial services.


Deloitte: Ai and risk management - Innovation with Confidence

Post a comment

(If you haven't left a comment here before, you may need to be approved by the site owner before your comment will appear. Until then, it won't appear on the entry. Thanks for waiting.)

Please key in the two words you see in the box to validate your identity as an authentic user and reduce spam.

Subscribe to this blog's feed

Follow us on