technlogy in finance Group-1.pptx BASIC.
- 1. Applications of Latest technologies in Finace sector Presentation by: Huligemma, suswait. Ajay, Jeevan, Chandrakant. Keonics, Hubli.
- 2. There are so many processes in banking & finance which can be automated or improved with the help of AI and ML Chatbots: are used to automate customer interactions with the banking staff. By identifying most frequent transactions happening between the staff and customers, like fd enquiry, loan enquiry, branch enquiry. Documentation enquiry etc.
- 3. Speech recognition: 1. Through speech recognition, bank systems can identify and authenticate a customer by matching his voice blueprint, and can enable him for further transactions. It can provide added layer of security to signatures obtained by the customers. 2. Once a transaction happens , customers cannot backtrack from the transactions , by denying that they have requested for the transaction to happen. As there voice blue print will be the banking systems. Ex: This can save banks and investment firms lots of time in surveillance activities or dealing with false customer complaints . 3. Voice activated systems can help blind persons to operate ATMs on voice request or voice commands 4. Through speech recognition banks can identify the intention of the customer to pay or receive and only that transaction should happen.
- 4. BLOCKCHAINenables secure, transparent and efficient transactions. Payments and remittances: it eliminates intermediaries and transaction fees and reduces transaction time is cost effective. Know your client: it can facilitate strong KYC , by a secure sharing of KYC data of a client across many financial institutions. It’s a regulatory requirement and helps banks to avoid fraud customers. Smart contracts: These are self executing agreements, which re programmed to trigger specific actions ,when buyers and sellers fulfill their obligations. These are very useful in stock exchanges.
- 5. NLP: Natural language processing. Through natural language processing our Chatbots interacting with the customers can identify and assess,(sentiment analysis) what service or product customer planning to buy in future and can suggest him products accordingly. Also all these conversations can be saved for future reference by /for staff or ML models to improve further in customer offerings. Also ML models can identify any fraud intentions by the clients , because previous conversations are saved, these red flags can be noticed by the bank staff.
- 6. CLOUD COMPUTING: Data storage management: vast data cane be stored efficiently, cost effective , secure and can be accessed from any where in the world Risk management: cloud based risk analytics tools, banks can manage risks quickly. Fraud detection: banks can improve their fraud detection capacity by training their ML algorithms over a vast set of data provided by the cloud computing platforms By detecting patterns and anomalies. Cost savings: Cloud can help banks to save big on IT infra spending, as banks can hire cloud services whenever they need them, which are provided by third party cloud service providers. Rather than investing big amount in them. Banks are left with good amount of money in their core banking activities to lend.
- 7. SECURITY RISKS: To mitigate the risks of data breaches, banks can invest heavily in technology to enhance security measures. Such as firewalls, intrusion detection systems, data encryption, multifactor authentication.
- 8. LEGACY SYSTEM: IS AN old practice and strength of the bank, which they cannot ignore while adopting new technologies. Ex : SBI yono : new way of 100% digital banking for tech savvy guys, which operates on fingerprints , otps, passwords user number etc without the use of a single pen and paper. Banks need to slowly adopt to changes . They should train the staff. Slowly introduce customers to change , like passbook updating, cash deposit etc.
- 9. REGULATORY COMPLIANCE This is a big challenge for banks as it’s a highly regulated industry in terms of data privacy and security. Banks need to ensure that they have adopted the strong technological measures of data security and privacy as discussed in above slides like multi layer authentication data encryption, fire walls, security intrusion alerts etc. damage and disaster recovery measures etc
- 10. THANK YOU