Innovating banking

December 30, 2018 01:30 AM Ananda Khatiwada


Ananda Khatiwada

Ananda Khatiwada

The author is currently working as Data Engineer in Capital One Bank, based in the US

Age of digitization has made available several technologies to make banking efficient. Banks in Nepal should benefit from them

Technology helps a lot in keeping the banking system efficient. IT facilitates and network transactions save time of customers and employees and cut down expenses. Banks are undergoing a fundamental transformation resulting from a range of technological innovations. Of the many, six technologies—Cloud Computing, Big Data and Analytics, Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), Distributed Ledger Technology (DLT) and Internet of Things (IoT)—have done wonders in financial innovation.

Cloud computing helps financial institutions to achieve considerable gains in efficiency and reductions in costs, as the technology requires banks to pay for only the service they use. It helps IT resources to be redeployed quickly and rapidly besides enhancing efficiency and productivity. 

It helps to lower the risks associated with traditional technology. It can equip banks with more control over security. Banks can scan potentially thousands of transactions per second, which dramatically improves the industry’s ability to combat financial crime, such as fraud and money laundering. In the banking sector volume as well as velocity of data have become important factors. The big data analytics comes into picture in cases when sheer volume and size of the data is beyond the capability of traditional databases.

These technologies use series of integrated disciplines, including applied statistics and mathematics, operations research and computer programming. Some elements of big data and analytics are well known and broadly adopted within financial services, such as the use of machine learning in algorithmic trading and natural language processing in customer service call centers. However, newer and more advanced uses of analytics to predict trends and prescribe actions in areas such as risk management are in the early stage. 

Financial services firms can collect data from customers’ social media profiles to figure out their needs through sentiment analysis and then create a credit risk assessment. This can also help establish an automated, accurate and highly personalized customer support service. Big Data also helps in Human Resources management by implementing incentive optimization, attrition modeling and salary optimization. The increase in amount of the data has made it essential for banks to incorporate implementation of Big Data Analytics.

The AI boon

Artificial Intelligence and Machine Learning allows computers to learn from data to predict and make decisions beyond human scale. Machine learning enables computers to detect fraud. Automated AI systems are responsible for nearly 70 percent of trading today. It would do well for banks and financial institutions in Nepal to follow this technology.

Artificial Intelligence and Machine Learning is designed with intent of stopping money laundering. AI-based systems are most intelligent at detecting money laundering patterns and fraud. The FICO (Falcon Fraud Management Solution) is the best example of how software makes use of AI to identify problem of transactional fraud and security threats. At the time of fraud detection, the AI model collects tons of transactional data and discovers unusual or fraudulent trends and activities. AI based chat system, also called chatbots, simulates human interaction and work with zero human intervention. Chatbots are used for improving customer relationship at personal level. 

Robotic Process Automation (RPA) is rapidly emerging as a highly efficient way to help financial institutions support their digital transformation initiatives.  It helps to capture and interpret existing means for processing a transaction, manipulating data, triggering responses or communicating with other digital systems. 

Distributed ledgers use shared database, which are distributed across a network that maintains a growing list of transaction between participants. The record is synchronized while the copy of record is identical and automatically updated and immutable as the recorded data on ledger cannot be changed. This technology was initially showcased through bitcoin, by enabling non-expert-peer exchange of virtual currency. Banks are currently evaluating distributed ledger and smart contract technology for a variety of uses, including master data management, asset /securities issuance and servicing, collateral management and trade/contract validation. 

Internet of Things (IoT) provides easy-to-access services to both credit and debit card customers. The customer data available through IoT will help banks to identify their customer business needs. The information received from the customers can help banks provide value-added services. IoT, along with data bank, can gather customer location that may lead to breach of privacy. It may cause data hacking and infringement which may adversely affect bank-customer relationship. For this, banks should incorporate best and latest data security technologies and must take corrective measure to ensure that data is secured.

Age of digitization has made available several technologies to make banking efficient and easy. Banks in Nepal have not been able to benefit from them all. Nepal’s banks need to explore all technologies that could make their jobs easy.

The author is currently working as Data Engineer in Capital One Bank, based in the US


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