According to one study, the market of Artificial Intelligence (AI) in the Banking, Financial Services, and Insurance (BFSI) industry was valued at $20 billion in 2022 and was projected to grow by 20% between 2023 and 2032. Another study showed that the market size of Blockchain technology in BFSI was $2034.1 million in 2021 and is expected to grow to $17,583.4 million in 2026 at a rate of 53.9%. These numbers depict how AI and blockchain are being integrated into several facets of the BFSI Industry.
In the post-COVID era, digitalisation has become one of the necessities of systems across various sectors, and BFSI is no exception to this. Digitalisation, automation, and the need for smarter systems are necessary to cater to the increased demand for services, amp up security, prevent fraudulent activities, offer better quality services, decrease costs, and much more.
In this article, we’ll look at some of the key use cases where Artificial Intelligence (AI) and Blockchain can be leveraged to upgrade the workings of the BFSI industry.
AI and Blockchain use cases can be divided into several categories within the BFSI industry:
BFSI Operational Services refer to the back-end operations that enable companies to offer services to their customers. This could involve approving loans, facilitating cross-border payments or large settlements, assessing risk and compliance, and more.
Banks have several redundant and repetitive tasks, such as data entry, verification of documents, and more. AI and Blockchain technologies, such as smart contracts, can replace menial tasks. Smart contracts allow any code to reflect real-life conditions and check if those conditions are met. With AI being integrated with smart contracts, institutions can easily check if loan applicants’ details are correct and if the applicant matches the criteria provided by the bank. Furthermore, entering data and cleaning it can become much faster without human intervention.
AI algorithms can enable financial institutions to assess the risk of lending a loan to a person. This is possible by factoring in metrics such as credit history, market trends, income, and much more. Generative AI algorithms can assess these metrics to derive insights on potential borrowers, assign them a score, and predict which ones will likely default on their loans. Based on this, banks can determine which people to give a loan to and which ones do not.
Banks, financial institutions, and insurance companies have several regulatory standards to meet across different departments and operations. Usually, companies use a manual process to vet their operations and practices against standards sourced from different portals on the internet. With AI, the process can be made simpler and faster as the algorithm will automatically check for regulatory standards from various online sources, vet the companies’ systems, and check if they follow such regulations. This is yet another process that can be conducted with minimal human intervention.
Cross-border payments take a lot of time and are quite expensive. In an era where real-time fund transfers are in demand, companies can utilise stablecoins and blockchain technology to facilitate payments in near real-time. These are digital currencies whose value is pegged to a fiat currency. Thus, they aren’t volatile and remain stable, as the name suggests. Due to this quality, stablecoins are apt for cross-border payments because companies can execute such payments and transfers much faster and cheaper.
Claiming insurance and checking if a policyholder is eligible or not is yet another manual task that can be automated. With insurance claims, companies need to check for several medical criteria, income, age, and more. Like the data entry process, smart contracts can also be used here, wherein the different criteria for passing/approving a claim can be coded, and only if the policyholder passes the criteria will their claim be approved and the amount transferred.
Another intriguing part where generative AI can make strides is portfolio management. Software incorporating AI can offer several features, including market analysis, risk assessment, asset allocation, and more. Although AI systems are not flawless, they have a higher level of accuracy, are transparent, and enable humans to make better decisions after they factor in their own understanding of the market.
KYC and AML compliance are common processes people must complete to access several financial and blockchain services. The process is repetitive and can be automated with the help of smart contracts and data interrogation using AI and machine learning (ML). The application would resemble insurance claim settlement, loan approval, and other such operations.
Regarding security, financial institutions can leverage blockchain and AI for cybersecurity and fraud detection. Frauds can occur in different forms. While one involves identity theft and illegal takeover of the banking systems, the other involves lying on application documents and more. AI can be used in two ways to tackle the two distinct challenges.
Firstly, AI tools can help audit the cyber infrastructure of financial institutions. The results can showcase vulnerabilities, past attacks, and their reasons and derive meaningful insights about the complete IT system. As a result, organisations can use the insights to determine their next steps to harden the infrastructure.
Secondly, ML models can be trained with data showcasing fraudulent behaviour patterns. These data sets can include transactions, historical data, and data from multiple external sources. With this, the algorithm can learn to identify fraudulent behaviour, and financial institutions can prevent such malicious activities.
Customer support is another department where AI and blockchain will be largely helpful. In today’s time, customers are looking for the highest degree of personalization in everything – How brands communicate with them, the offers they receive, and the features they need in a product. For such use cases, AI and blockchain can be leveraged in the following ways:
Chatbots and voice assistants can help with customer queries and also enable them to fulfil preliminary steps of any formalities with the help of AI. This way, human intervention will be less, and customers will be able to accomplish their tasks without going through multiple points of contact or visiting a branch office.
Banks, financial institutions, and insurance companies develop various offers, gift vouchers, and more to attract customers. However, these are often generic and do not offer a high degree of personalization. AI systems can look past customers’ behaviour on the apps and websites. They can also look at their transactional data to determine what kind of offers each customer would appreciate and buy into. Based on this, companies will have a higher conversion rate when it comes to selling their offers.
BFSI institutions can also develop customer loyalty programs with the help of blockchain technologies such as smart contracts, stablecoins, Non-Fungible Tokens (NFTs), and more. For instance, stablecoins can be used as loyalty points for customers to get cheaper cross-border payments. Apps can also have a feature for people to convert digital currency to fiat and use it in different places. Alternatively, NFTs can be used as rewards that people can sell in exchange for money. However, NFTs can also come with several utilities that customers tend to use.
AI and Blockchain can also be leveraged in marketing efforts to improve marketing campaigns’ efficiency, accuracy, and conversion rates.
AI and ML software will be able to trace user activity across applications, websites, and more. These will enable the algorithms to better understand potential customers’ needs and the values they look for in a company. Based on this, marketing campaigns can be strategized, which will be driven by insights into the AI/ML systems and help increase conversion rates.
Market trends are an integral part of the BFSI industry. Generative AI can be used to read, analyse, and derive insights from historical data from multiple sources. Based on this, predictive analysis models can help determine future industry trends. Companies can leverage these to decide on future policies, pivot if needed, and be prepared for the ups and downs.
Overall, these are only a few broad use cases of AI and blockchain in BFSI. These enable increased security, efficient processes, enhanced customer experience, and better growth of the companies.
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