How Data Analytics is Transforming the Financial Services Industry
The ability to use data intelligently has become a key differentiating factor for the world’s banks and financial institutions. In the area of consumer finance, customers value ease of doing business very highly. Traditional banks, with their legacy systems and processes involving multiple departments, are often at a disadvantage.
Financial technology companies or fintechs are rapidly increasing their market share in areas as diverse as consumer lending, insurance, and wealth management. One of their greatest advantages is that they have the ability to manage data effectively and use it to provide customers with a high level of service.
But the banks are fighting back. They are using data analytics to implement real-time systems that anticipate client needs. Their existing customer relationship management infrastructure is being modified to gain insights into client behaviour. By making this change, banks are able to offer customers those products that they require, increasing the probability of enhancing the volumes of repeat business.
Banks are taking a cue from e-commerce firms
JPMorgan Chase, a financial services company that provides its clients with the opportunity to trade in fixed income securities and equities, is using data analytics to boost its business. A report in the Financial Times provides details about how the bank is in the process of introducing a new customer relationship management system that will give its traders instant information about a customer’s preferences.
The system that the bank has been using requires traders to obtain data on a client’s previous deals by pulling it out themselves if the need arises. The new CRM will link a customer’s phone call to previous trades automatically, providing the bank’s salesperson with the opportunity to offer products that match the client’s trading history.
The bank is a market leader and generated US$21 billion in fixed income and equity sales and trading revenues in 2016. In an attempt to bolster these numbers, the bank will now utilise analytics to mine customer data in much the same way as is done by e-commerce firms.
Amazon has perfected the art of offering its customers products that match their previous purchases and surfing history. JPMorgan Chase hopes to use the same principle to grow its trading volumes.
It recently bought a stake in InvestCloud, a California-based firm that specialises in making apps designed for the financial services industry. JPMorgan will use InvestCloud technology to provide its wealth management clients the ability to view sophisticated web dashboards that address their individual needs.
Research at financial firms is now being driven by data analytics
The world’s largest banks have well-staffed research departments that churn out hundreds of reports, many which are never read by clients. Benjamin Quinlan, the CEO of Quinlan & Associates, a consulting firm specialising in financial services, estimates that over 40,000 articles are emailed by banks and brokerages to their clients every week. Only about 2% to 5% of these reports are ever read.
In an attempt to cut costs and increase efficiencies, financial service companies are cutting down on their research staff.
To meet its objective of providing clients with personalised research reports, BCA Research, a firm established in Montreal in 1949, is working to bring about great changes in the way it creates functions. As a first step, it is moving away from the standard practice of emailing reports to clients. Instead, it is promoting interactive websites that allow customers to access the information that they need.
Given that recipients read only a minuscule percentage of the reports that they receive, research departments sorely need to change their approach.
UBS, a leading Swiss bank, is restructuring the manner in which it carries out research activity. Its head of global research, Juan-Luis Perez says, “If I showed you a report from the 1920s and today you’d be surprised at how similar they are.”
The bank has recently hired data scientists who will work jointly with industry experts to prepare reports that are tailor-made for clients. A company that requests a report will even be able to ask for the research to describe various scenarios based on the assumptions that it provides.
Data drives Citi’s global business
Citigroup has over 200 million customer accounts distributed across 160 countries. Data analytics and the ability to use the information that it generates can provide the bank with a significant competitive advantage. With its huge base of customers and their past transactions, Citi is uniquely positioned to profit from developing new initiatives built on analysing the data in its records.
The bank has launched a “data innovation” program that runs new products through a proof-of-concept exercise. In an interview, Michael Simone, managing director of Data Platform Engineering at Citigroup, said, “We are focused on having actionable results that are balanced with very specific metric-based outcomes.”
Citi uses data analytics extensively in its customer retention and acquisition strategies. Promotional campaigns for selling the bank’s products are run on the basis of existing data about its clients. Data analytics also allows the bank to monitor its customers’ transactions in real time and spot anomalies instantly. This information can be used to prevent fraud and also to offer clients an enhanced level of service.
Michael Simone says “We have been managing and analysing data effectively for years to see how we can improve our operations…”
How data analytics helps the financial services industry
Banks and financial institutions can make significant gains by using data analytics intelligently. A lender’s risk management capabilities can be enhanced by studying the repayment patterns of existing borrowers based on the initial credit analysis that was conducted.
This information can be used to vary lending rates. Borrowers who have a higher risk of default could be offered more expensive loans while low-risk borrowers could be provided with better rates of interest. Using “predictive” data analytics in this fashion could result in greater business volumes as well as an enhanced level of profitability.
Data analytics can also be used to monitor employee performance and provide a basis for developing sales budgets for the various regions and branches of a bank.