Economy


The power of data in the financial services industry




Suits The C-Suite
Veronica Mae A. Arce


Posted on April 13, 2015


Changes in business and technology in the financial services industry have opened up new possibilities. With the rapidly growing number of customer interactions through digital banking, there is a huge volume of customer data now available that can provide strategic opportunities for business growth and tremendous prospects for improved management tools.

However, after experiencing the challenges of the recent financial crisis, most Philippine financial services companies are understandably more focused on compliance and risk management, rather than on growth opportunities resulting from improved data and analytics. They are still dominated by data management solutions and have yet to truly embed analytics into business decisions. Data is used operationally and not strategically. They have yet to embrace the key awareness that, in this digital age, acknowledging the value of data as a strategic asset, deploying sophisticated analytics to realize the benefits of that asset, and converting information into insights and practical actions create a competitive advantage.

The industry has always used big data, particularly in credit analysis. Many analytics tools are currently available such as ACL, SQL, SAS, Falcon, Lavastorm, Tableau, Spotfire and Qlikview. At present, the business functions that are most advanced in terms of analytics are finance and risk management. There is also increased use in compliance and internal audits. However, the power of data has remained largely unexploited and untapped. Insights from big data can also be used to make well-informed strategic decisions by using data to effectively extract value from customers, identify risks, and improve operational efficiency.

A few high-growth financial services companies in the Philippines, mostly foreign, are beginning to embed data analytics in sales, marketing, budgeting and planning. They understand that product and service models must be fine-tuned to respond to changing customer preferences and expectations. Using big data techniques can help enhance customer targeting, as well as advice and adjust pricing and resource allocation. Other companies in the financial services industry should consider adopting these initiatives in order to do well in light of increasing competition.

THE CHALLENGES
As with any new idea, gaining an appreciation for the opportunities in data analytics is not without difficulty. Regulations, data privacy, fragmentation and skills shortages are among the challenges facing the financial services industries in this regard.

• Regulation and data privacy concerns still dominate the financial services industry because failure may cause irreversible financial and reputational damage; after all, these businesses rely largely on credibility. The industry has also become a target for cyber attacks. Cybercriminals have developed advanced techniques to infiltrate businesses and fraudulently access sensitive information such as usernames, passwords and credit card details. Top cyber attacks in the financial services industry include phishing (unsolicited e-mails sent without the recipients’ consent to steal login credentials and banking details), and remote access Trojans (fraudulently gaining access to sensitive and private information). Consequently, customers continue to take issue with digital banking.

This should not, however, dissuade companies in the financial services industry; this challenge does not prevent them from exploiting the full potential of data analytics. The industry must find ways to use big data to improve customer service without violating privacy concerns. It must continually reassure customers that their data is valuable and that their privacy has not been violated.

To retain confidence in their ability to safeguard customer data, financial services companies will need to consistently update information security policies, systems and infrastructures, and ensure that they are abreast with best practices.

• The infrastructure of many financial services companies is set up along products or business lines using legacy IT systems that are poorly connected and are unable to communicate with one another. Bridging the gaps between these fragmented systems and replacing them with new platforms represent a serious challenge, making it difficult to introduce new technology solutions. It requires simultaneously running the business while unwinding the legacy systems and migrating smoothly to a new platform with a central data system.

• Another important technical challenge is the lack of skilled data specialists who are able to understand and manage the complexity of the data from the emerging tools and technology and provide high-class analytics with business implications.

STRONG LEADERSHIP AND GOVERNANCE
Strong leadership and governance is the key to the success in the use of data analytics. Leaders with vision and character who are attuned to the fast and continuous growth in business and technology must first make a firm decision to give more impetus to data analytics, integrate the whole company’s data management team by hiring skilled data analysts and orchestrating the motion of extracting and exploiting big data and using it to achieve competitive advantage.

Data analysis was previously considered an IT-level matter. The scale of digitization and data analysis must be adopted as a core strategic issue and must move to the top level of management and be given due attention.

Effective data governance requires an integrated approach. Leaders should commit not just to the technology, but must also see the need to invest in the people, processes and structures necessary to ensure that technology delivers value throughout the business.

Part of the task requires re-educating the organization. Formalized data governance processes must be disseminated, understood, and complied with throughout the business.

Potential data issues should be identified through regular data quality audits, continuously training staff on governance policies and procedures, and conducting regular risk assessments aimed at identifying potential data vulnerabilities.

With these complex requirements and tasks, it may take time for companies to fully appreciate the advantages of data analytics. But with the rapid evolution of technology and increasing competition, forward-looking organizations might seriously consider fast-tracking the necessary steps to fully appreciate the power of data.

Veronica Mae A. Arce is a Senior Director of SGV & Co.