Data Is Key
Barry McCarthy,SVP, Financial Institutions, First Data
Ongoing seismic shifts in the industry – such as regulatory changes, the need for new technology investments, and increased competition from alternative providers – will require banks to devise creative strategies to maintain profitability during 2013 and beyond.
Many institutions are succeeding with data-driven strategies for identifying new opportunities and enhancing value with their customers. Through predictive modeling, progressive institutions are using meaningful incentives to increase usage of revenue-generating products. Through sophisticated customer segmentation, data can indicate which products or services a financial institution should offer and in what sequence.
Banks can also enhance the customer relationship with sophisticated promotional management platforms that enable consumers to attach deals, coupons, and loyalty programs to payment cards or to their mobile wallet. Such offers reassert the value of the financial institutional relationship and encourage activity on that card or wallet.
As they face a rapidly evolving industry, it is essential for all financial institutions to use data to better understand consumer needs. They then can use that knowledge to enhance their core offerings and better meet those needs.
Cyber attacks a great threat
Luge Pravda, SVP, NetNames
One of the biggest IT challenges for banks in 2013 will undoubtedly come from ongoing DDoS cyberattacks by so-called "hacktivists" that block customers from accessing their online banking services. DDoS, or distributed denial of service, is an attempt to make a network unavailable to its intended users.
We saw these attacks occur on a massive scale in 2012 when a hacker group with Middle Eastern ties claimed responsibility for causing mass chaos at Bank of America, PNC Bank, JP Morgan Chase, SunTrust, U.S. Bank and others.
This was far from being an isolated incident, with the attacks escalating as the year draws to a close. DDoS attacks will probably not only increase in number, but in severity; they are positioned to increase at a growing number of application levels (so-called ‚─˙low and slow‚─¨ DDoS attacks); and they will become worse against smaller banks and businesses, who have less sophisticated security measures in place.
The DDoS threat also seems to be increasing in sheer bandwidth, as botnet digital muscle becomes ever cheaper -- it can be hired by the hour for less than your average latte. Banks will need to ramp up their awareness of impending attacks and immediate response in order to warn customers of slowdowns and non-access, and shield themselves using a combination of dedicated and cloud-based DDoS mitigation against savvier attackers.
With hackers devising new strategies daily, it is key that any solutions are scalable, robust and regularly updated, and consulting with security experts can help identify the next area of vulnerability for the bank.
Luge Pravda is Senior Vice President at NetNames USA, Inc. He can be reached at Luge.Pravda@NetNames.com
Big Data, Big Challenges
Michael Langenkamp, CCG Catalyst Consulting Group
A key challenge facing the banking technology community in 2013 is everyone’s favorite buzzword—“Big Data.” Bankers realize that to remain competitive, they have to understand their customers like retailers do, with the ability to predict and behavior offer the right products at the right time.
But the challenge is this -- bankers have long since realized the importance of data. Some have installed data warehouses, others have tried to implement profitability modeling, CRM, or data analytics all with varying degrees of success.
While bankers are still defining what big data really means in financial services, any data-related project must have heavy volume (either in terms of size or record count), high speed (real time or close to it), and incorporate multiple sources (for a bank, this would include their own internal data like transaction volumes and channels, as well as external data like social presence). All too often, approaching a project of this magnitude is simply overwhelming and remains undone.
Big data for banks may mean first connecting the dots among the data they already have. Think how much data runs daily through the bank—transaction history, channel preferences, communication preferences. Banks should invest in the technologies that integrate the data they already have, and then use that as the foundation to build “bigger.”