The financial industry has transformed noticeably over the years. It revamped its traditional methods of service to be more customer-centric in its approach. To a large extent, Artificial Intelligence (AI) has been a critical enabler in this transformation. Today, the financial industry is majorly based on building itself as a customer-centric domain and providing never-like-before customer experiences. For instance, Chatbots and virtual assistants have not only made services available 24×7 but have also improved customer service and satisfaction drastically, all while reducing costs for financial institutions. AI also has the reliable ability to analyze customer data that enables it to create personalized financial plans along with recommendations of customized products and services that are fast, accurate, efficient and secure. Interestingly, AI still has areas to be explored and is capable of much more than it is currently offering in the financial domain. AI brings in an amalgamation of better experience, lower costs and better growth. Revolutionizing AI trends There are several AI trends that have the potential to revolutionize the Fintech industry. Some of the most significant ones include – Personalized banking experiences: With AI, fintech companies can use customer data to create personalized experiences for users. This can include personalized product recommendations, customized investment portfolios, and tailored financial advice. For example, investment companies understand customer’s income and expenditure behaviour along with the duration of peak to low expense span. Based on this analysis along with others like your investment preference, type and need, they create an entire portfolio for you to benefit from. Fraud detection: AI-powered fraud detection systems can analyze customer behaviour and transactions in real-time to detect any suspicious activity. This can help prevent fraudulent activities such as identity theft, money laundering, and credit card fraud. Due to the potential AI holds in the field of fraud detection, Banks worldwide are expected to spend an additional $31 billion on artificial intelligence (AI) embedded in existing systems by 2025 to reduce fraud. Risk management: AI can help fintech companies analyze large amounts of data to identify potential risks and opportunities. This can help them make more informed decisions and manage risks more effectively. As a lender, financial institutions face huge risks in ascertaining their borrowers. AI reduces this risk significantly by creating a financial personality of the borrower by collating and analyzing various data points. Blockchain technology: AI can be used to enhance the security and efficiency of blockchain-based transactions. This can help fintech companies offer more secure and transparent financial services. Blockchain plays a very critical role in taking financial services to the last mile. It enables the integration of various points to build a secure and reliable marketplace for individuals far and new to the financial domain. AI holds great potential and it is with time we shall witness the transformation it is yet to bring!
Tag: management
7 Types of Risk Management You Must Know About
The COVID-19 pandemic has caused major disruptions in banking operations. Consumers have become more demanding and so, risk management must be robust. According to leading banking professionals participating in the Deloitte Banking Risk & Regulatory Academy, financial institutions must focus more on credit risk management. The banking structure must restructure and be prepared for forbearance. Apart from commonly known risk management strategies, leading banks also focus on Environmental, Social, and Governance (ESG) by improving data management strategies and analytics. Moving to the cloud is the next inevitable step to navigating complex risks and ever-changing regulatory requirements. Types Of Risk Management Risk in the banking sector refers to unplanned incidents with major financial consequences, such as reduced or lost earnings. Risk management involves establishing a series of protocols and multi-step procedures that can precisely and accurately mitigate risks. Risk management planning should help financial institutions to recognise threats, assess the damage, and take control measures to prevent risk and minimise the damage. 1. Liquidity Risk Management Banks must safeguard long-term asset funding using short-term liabilities. Funding risk for banks increases when the net outflows increases. This can be due to the non-renewal of different types of retail and wholesale deposits or unexpected withdrawals. Funding institutions must also be prepared to deal with time risk when the expected fund inflows are delayed. Risk management is essential when the non-performing assets increase. Call risk happens when contingent liabilities crystallise, and no viable business opportunities are available. 2. Interest Rate Risk Management Determining the right interest rate that is beneficial for the banks and also for the customers is always challenging. NBFCs that offer lower interest rates to beat the competition must be careful because the adjustments must not result in reduced Market Value of Equity (MVE). The interest rate risks can affect the banks’ earnings and the economic value of the off-balance sheet. 3. Market Risk Management Market fluctuations can lead to market risk when the mark-to-market value of trading portfolios goes down. Also called price risk, the market risk can dramatically increase when the transactions have to be liquidated. Different factors, such as volatility in commodities, equities, currencies, and interest rates, can influence market risks. 4. Credit Risk Management As NBFCs try to capture market share by disbursing more loans to underserved markets, their credit risk increases dramatically. The NPA level of the Indian banking system is high. When the borrowers fail to fulfil their obligations, the counterparty risk and country risk for banks increase. Loan portfolio management and detailed evaluation of borrowers are crucial to managing credit risks. 5. Operational Risk Management Banks risk a huge financial loss when internal processes and systems fail. Global financial links have increased as the banking and financial sector adopt automation. As a result, the potential for operational risks also increases. Transaction risk can result in failure in business continuity. Compliance risk can affect the integrity and credibility of banks. 6. ESG Risk Management ESG risk is the new age risk for financial institutions as they have to comply with inclusion and diversity policies. The pressure from multiple governments to contribute to climate change policies also affects investment value for the banks. Proactive risk management using models that integrate ESG and climate data must be used. 7. Reputational Risk Management In the highly competitive banking sector, reputational risk can result in a loss of trust by customers and stakeholders. This risk can be caused by poor customer service, corruption, and fraud. Banks can prevent class-action lawsuits and other punitive damages with proper reputational risk management. Mitigate Risks With Risk Management Framework Banks and financial institutions must build a robust and scalable risk management model. The framework should include all risk parameters with adequate risk grading. The framework should be updated continuously based on updated risk tolerance levels. The model risk management framework must be built into banking operations for effective risk mitigation.