The Banking, Financial Services and Insurance sector is one of the fastest-growing industries for incorporating artificial intelligence. This is mainly due to the growing advancement in AI and machine learning across the globe. The ability that AI has, to respond to ambiguous real-world inputs by giving a probabilistic output, is one of its critical features in the BFSI industry and AI will dominate BFSI. The major applications of artificial intelligence in banking are analytics, bots, digital avatars, robotic process automation (RPA), and report generation.
Because of the ongoing pandemic, most people prefer not to go to the bank. Therefore, banks and credit unions have to resort to digital means to let the customers transact in the comfort of their homes. Banks have to stay updated on the technological front to keep up with the rising requirements of BFSI instead of trying to change the entire landscape.
Talking about customer preference in particular, it varies widely in the current BFSI market scenario. Artificial intelligence has helped banks and financial institutions to customize and personalize their service according to the various needs of the customers. AI has also helped financial institutions to reduce their long-term costs by deploying bots for customer service. According to a report by Research and Markets, the global artificial intelligence in the BFSI market was valued at $17,765.2 million in 2018 and is projected to reach $247,366.6 million by 2026, growing at a compound annual growth rate of 38% from 2019 to 2026.
Use cases of AI
Banking and financial services have recognized the true potential of Artificial intelligence and AI will dominate BFSI. Analysts and experts estimate that AI will save the banking industry around $1 trillion by 2030. Here are some of the best ways that AI can be used in BFSI:
- Customer Service
Using a virtual assistant can save a lot of time during customer support. Voice assistants help people get more work done, which adds to the flexibility of an omnichannel experience. Virtual avatars can also be seen in digital kiosks for personalizing the customer’s experience. Using built-in chatbots and AI technology, banking professionals can guide customers through different intervals of the buyer’s journey, capitalizing on good response times and personalization of the customer experience.
There is a need for proper processes, security measures, and central repositories in any BFSI sector to prevent cyberattacks, information leaks, and legal action. This is because banks need to meet strict regulatory requirements. By automating the flow of information, data is transferred securely and quickly on one main master unit. Each stakeholder is notified, therefore removing the likelihood of human error and missed deadlines. Process automation can integrate with AI and RPA to help banks in the long run.
- Risk management
As compared to traditional credit scoring systems, AI is based on more complex and sophisticated rules for the same. Artificial Intelligence is present to help lenders to distinguish high-default risk applicants and those who are credit-worthy but lack an extensive credit history. This is mainly dependent on predictive analytics and NLP, to determine alternative credit risk score models. This shows how AI will dominate BFSI.
- Fraud and anti-money laundering (AML)
To identify early signs of potential future issues, there are certain algorithms present to analyze risk cases. AI in finance is a powerful ally when it comes to analyzing real-time activities in any given scenario. AI can drive significant efficiencies in tasks like KYC verification procedures, automating formerly manual workflows, and transaction monitoring control through machine learning.
Looking over the lending lifecycle has always been manual and paper-intensive. Most of the banks today are turning to AI and process automation to digitize these lending processes, along with gaining a greater understanding of customer profiles based on data analytics. Operations like pre-screening, application processing, underwriting, and disbursal can be automated across a vast range of loan products.
People are focusing more on increased transactional and account security, especially due to the expansion of cryptocurrency and the adoption of blockchain. Blockchain will surely become a part of the core business platform which enables transactional transparency across a wide variety of business functions. This might reduce or even eliminate transaction fees altogether because of removing the middleman in transactions.
By 2030, FinTechs anticipate AI will have expanded their workforce by 19%. And according to a survey, 64% expect to become mass adopters within two years, proving the growing potential of AI to stimulate innovation and growth across a wide range of business functions. Banking and financial services are definitely changing for the better and they must be prepared to handle new challenges.