The role of AI in capital markets
Even before the Covid-19 pandemic hit, investors limited their portfolios to well-established companies and stock corporations. The pandemic, with its uncertainty, layoffs, and multiple closures, exacerbated the tendency to patronise known brands.
Manual legacy systems in the capital market lack transparency and efficiency. On the one hand, they deny investors the required visibility of underrepresented businesses and on the other, restrict growth opportunities for smaller but promising entrepreneurs.
Using AI in capital markets can catalyse inclusion, diversity, and equitable opportunities for investors and corporations.
How can AI augment capital market and financial services?
Using AI in capital markets can empower individuals and businesses to detect and leverage insights through big data often inaccessible through conventional research. Here are some ways in which AI can empower capital markets and financial services organisations:
Robotic Processes Automation (RPA)
Sentiment analysis through NLP
Processes throughout the trade lifecycle, such as customer onboarding and servicing, trade settlement, reconciliation, and regulatory compliance, are expensive and labour-intensive. Companies typically outsource these services to low-cost locations. However, offshoring is not always sustainable due to time zone and demographic differences.
RPA automation services are cost-effective way of automating middle and back operations in capital market firms. RPA in rules-based processes can minimise manual labour and operational costs, drive high accuracy, break across departmental silos, and generate audit trails for regulatory requirements.
AI-driven cognitive technologies combine RPA, Machine Learning (ML), and Natural Language Processing (NLP) to take over complex processes that traditionally require human thinking, such as financial advice, portfolio management, and anomaly detection.
Cognitive computing tools use predictive and prescriptive analytics to lend capital firms a competitive advantage in volatile markets. This frees up human teams for higher-value activities such as idea generation and client relationship management.
Emotion drives the capital market rather than fundamental value, especially in uncertain times. NLP-powered AI applications outperform traditional models in sentiment analysis to present a clearer picture of bearish or bullish propensities. AI models in capital market firms can tune in to diverse datasets such as social media mentions, market research, and customer feedback to help investors and firms gauge the market sentiment towards specific securities.
Deep learning models process huge amounts of data from disparate datasets such as stock price movements, historical data, and customer feedback to identify market patterns and aid algorithmic decision-making. Firms can deploy deep learning applications in various domains, such as price forecasting, portfolio management, and fraud detection.
AI use cases in capital markets
Most capital firms already use some form of process automation for repetitive tasks such as client onboarding and compliance checks. Here are some more use cases of AI in capital markets:
Risk analysis and management
AI in capital markets can enable firms to assess a client’s creditworthiness by analysing factors such as transaction and credit history, investment preferences, and income growth. Data insights can also support pre-trade and post-trade risk analysis by computing initial margins and generating predictive models for price forecasting.
Many reputed hedge funds use AI to generate quick and accurate market analyses that provide crucial insights into market conditions, consumer behaviour, and future trends. This allows them to make better and faster decisions based on trading algorithms.
AI can also augment decision-making by identifying buy-side and sell-side opportunities, prescribing the next best action, and recommending risk handling in unexpected situations.
With personal information, reputation, and money at stake, fraud prevention is a crucial concern for capital markets. AI and ML-powered fraud detection models can process enormous amounts of historical and current data, flag anomalies, reject suspicious transactions, and rate the likelihood of fraud in real time.
Capital markets and financial services firms must comply with multiple rules and regulations that often change with socio-political disruptions. Non-compliance can lead the organisation to serious problems. AI completely automates regulatory compliance, eliminating human intervention and resultant errors.
Chatbots, Robo-advisors, and virtual assistants can answer customer queries in real time and provide recommendations based on individual goals and risk capacities. This can minimise the need for human asset managers and enhance the customer experience.
Deploying artificial intelligence in capital markets can thus augment various processes and create a level playing field for investors and businesses of all sizes.
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How can Infosys BPM help?
Infosys BPM Capital Market financial services enable financial institutions to optimise performance, reduce complexity, and stay ahead of the competition. We assist global asset and wealth managers, custodians, private equity firms, investment banks, broker-dealers, and financial information providers in preparing for the future.