Banking on ICT: BFSI players update their technological architecture for better service delivery

Banking, Finance & Insurance , June 29, 2017

The banking, financial services and insurance (BFSI) industry has witnessed several notable developments in the recent past. A number of customers have been brought into the banking fold with the government’s increased thrust on financial inclusion. New digital payment platforms have been launched following the November 2016 demonetisation move. And new models of banking, in the form of payments banks and small finance banks, have emerged.

While these developments have opened up many new opportunities for the BFSI industry, they have led to several challenges too. The biggest of these is the increased threat of cyberattacks. There is also the challenge of BFSI players remaining technologically updated in order to cope with the demands of the changing milieu. In this regard, a robust IT and telecom set-up is of immense importance. Emerging technologies such as the cloud, internet of things (IoT) and analytics can prove to be game changers in the industry.

A look at the key IT applications being adopted by organisations in the BFSI space…

Enterprise applications

Computerisation marked the beginning of all technological initiatives in the banking industry. The process involved the installation of simple computers to automate the functioning of branches, especially high traffic branches, and was followed by total branch automation. However, it did not involve branch-level networking. Subsequently, core banking solutions (CBS) were introduced to enable banks to offer multiple customer-centric services on 24x7 basis from a single location, supporting retail as well as corporate banking activities. CBS benefits both customers and banks. Through CBS, customers can access their accounts from any branch irrespective of where they have physically opened their accounts. Further, it enables fast payment processing through internet and mobile banking, and facilitates routine transactions at bank counters. For banks, CBS has resulted in process standardisation across branches, increased transaction accuracy, improved documentation and data retrieval through centralised databases, and greater convenience in opening accounts, servicing loans and implementing policy changes. Almost all the branches of scheduled commercial banks have been brought into the core banking fold.

Meanwhile, an increasing number of banks are adopting customer management tools such as customer relationship management (CRM) to better analyse customer behaviour, facilitate business process re-engineering, and manage multiple distribution branches and customer groups.

Most banks in India are using operational CRM that provides access to information through phones or email. Using operational CRM, banks can provide the requisite information to customers through their call centres. Meanwhile, analytical CRM is used to analyse the information by understanding the nature of the account and the transaction. It utilises data warehousing and data mining. A data warehouse gives the bank a single view of disparate data that may be spread across its various systems. Data mining helps decode the information and use it for positioning and targeting decisions. Other advantages of analytical CRM include cross-selling and upselling of services.

Banks have also started implementing e-CRM solutions, which help them receive real-time information about customers, track customer details, address queries, and analyse the data and marketing initiatives taken by them. Some of the e-CRM solutions implemented by Indian banks are internet banking, mobile banking, computerised decision support systems and customer smart cards.

IoT in the BFSI industry

IoT can help financial institutions innovate and devise better ways to design customer products, improve risk management and increase overall operational efficiency. According to a study by Tata Consultancy Services, financial institutions use IoT mainly for tracking their products and services after they are sold or leased to customers. The next common IoT application is monitoring customers through digital or wearable devices they carry while using the company’s products or services. The data gathered through these devices helps the companies track and analyse customer behaviour and demands. This information can be used to provide customers with a more personalised experience. Besides, IoT is used by financial institutions for on-premises monitoring and supply chain monitoring, which involves tracking customer experience at the financial company’s stores, branches and offices, and for tracking product/service operations (production, warehouse operations and other processes).

A key application of IoT in insurance is providing usage-based insurance products. In the case of life and injury insurance, all kinds of risks are covered under a single policy. However, by using real-time data about personal behaviours, firms can fine-tune coverage to potentially add or eliminate certain risk clauses. Although this would make the pricing of policies a complex procedure, it would result in greater customer satisfaction. Meanwhile, asset and wealth management companies can use IoT to help businesses and consumers make investment decisions and undertake asset allocation based on behaviours, personal choices and geographic considerations.

Role of analytics

Analytics is helping the BFSI industry in managing the myriad challenges it faces. While basic reporting and descriptive analytics continue to be essential tools for the segment, advanced predictive and prescriptive analytics are also being adopted to generate insights that could have a significant business impact. Advanced analytics-backed solutions enable the sector to manage not only the increasing cost of compliance, but also the risks (both monetary and reputational) of non-compliance. Product and portfolio optimisation is helping banks achieve profitable growth in a market environment that is characterised by significant volatility across asset classes and rising losses in traditional banking products. Fraud analytics helps banks and insurance companies to prevent money laundering and associated potential losses. Consumer behaviour and marketing analytics provides a competitive advantage in an era of eroding product differentiation, waning customer loyalty, and exploding volumes of data.

Cloud adoption

The BFSI industry generates a large amount of data on a daily basis, which needs to be accessible anywhere, any time to consumers. This can be ensured through cloud-hosted solutions. Most financial trading firms have moved their operations online. This has helped boost customer confidence in trading as they are able to access real-time data. This, in turn, has increased trading volumes. Insurance firms, too, see cloud as a critical enabler that can help them reduce costs and enhance operational efficiencies.

Challenges in technology implementation

One of the major challenges faced by banks with regard to the adoption of technological solutions is the integration of the various applications developed on varied platforms. There is no single banking solution available to meet enterprise-wide requirements in an integrated manner.

Security is another major concern in a technology-based networked financial environment. Information systems used in banks are not only between businesses, but also between a business and a customer. BFSI enterprises are at the foremost risk from cyberattacks. With the rise in the number of online transactions, the threat of customer data theft has increased manyfold.

Increasing customer expectations present another challenge to effective technology implementation at banks. Shifts in demographics, incomes, etc. are empowering bank customers to demand greater autonomy, responsiveness and transparency from their banks. With increased competition in the banking space, customers are now exercising their freedom of choice by opting for banks that offer them better and customised services. Changing customer requirements call for continuous technological advancements, thereby rendering integration of technology at the enterprise level extremely difficult.


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