Aiding Information Discovery
Financial services companies can keep “discovering” real-time insights on their portfolios and accordingly update their portfolio strategies
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Financial service providers such as banks, wealth management advisors, and fintech startups are embracing the application of AI (artificial intelligence) across the value chain. AI is a blend of three advanced technologies – machine learning, natural language processing and cognitive technology/ analytics. Cognitive analytics is an enhanced approach to information discovery and decision-making. It can drive opportunity and value in almost every financial service function.
Financial services companies can keep “discovering” real-time insights on their portfolios and accordingly update their portfolio strategies.
We can classify the cognitive analytics into the following four categories:
Cognitive engagement: Improve customer understanding and activation through personalisation, influencing desired actions
Cognitive automation: Automate repetitive, knowledge and natural language rich, human intensive decision processes
Cognitive insights: Detect key patterns and relationships from billions of data sources in real time to derive deep and actionable insights
Cognitive ‘sensing and shaping strategies’: Build a deep understanding and knowledge of company, market dynamics, and disruptive trends to shape strategies
On the customer front, Indian consumers will benefit from AI technology in terms of reduced waiting time in self-help customer service or real-time turnaround for banking and wealth management services, among others. For example, customers will be able to apply for a credit card via a chatbots/chat-based system (enabled by a cognitive engine) from their own office or home. They will receive a real-time decision on their application status and if approved, they will receive a virtual credit card for instant use. The backend system integration could enable the virtual credit card for use with point-of-sales terminals via a mobile device.
From a sector perspective, the AI technology helps in analysing anti-money laundering patterns. Banking institutions are globally shifting from rule-based software systems to AI-based systems for robust and accurate insights. Similarly, hedge funds are using high-end systems to deploy the AI models to make investment decisions. AI has provided the maximum benefits in the fraud detection sector by providing real-time accurate and high-quality results on early warning signals and fraud detection, providing regulatory oversight and trade secret protection, among others.
Globally, the large commercial and investment banks are incorporating AI and blockchain for both back office and customer experience roles. However, in India, the widespread adoption of these technologies is relatively at a nascent stage and is yet to experience the sunshine.
With the government’s special focus on the digital transformation, financial inclusion as well as the adoption of modern methods like mobile banking and online payments across the country, data analytics has become an imperative to increase revenue, enhance customer experience, optimise cost structures, and manage enterprise risks.
Applications of AI in Indian financial services industries will increase customer interaction, accurate insights and real-time fraud risk management. It is evident that there is stiff competition in the Indian financial industry today, and companies are exploring and adopting new technologies in order to stay ahead of their competitors.
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