Data & Analytics

10:14 AM
Colin Kerr, Microsoft
Colin Kerr, Microsoft

Data Analytics: Reaping the Data Dividend

Data analytics are essential to helping financial institutions stay the strategic course while balancing risk mitigation requirements with the drive for growth.

It is an unprecedented time in the industry with extremely high regulatory scrutiny of banks and capital markets firms, coupled with an acute need to grow deposits and revenue streams in the light of increasing diverse competition. To address these challenges, two key roles in financial institutions have risen to the forefront of business strategy: the Chief Risk Office (CRO), and the Chief Marketing Office (CMO). Although facing such different priorities, these two executive offices do have something in common as they transform the business: data analytics.

Regulations such as Basel III and Dodd-Frank are having a profound effect on the business models of financial institutions. Therefore, regulatory compliance and risk management remain top priorities for banks as they look to navigate in the "new normal." The economic crisis of 2008 highlighted the importance of counterparty measures that could help mitigate the potentially far-reaching impact of economic risks, such as a fiscal or liquidity crisis, which is still one of 10 risks considered of "highest concern" in the World Economic Forum Global Risks Report for 2014.

Colin Kerr, Microsoft
Colin Kerr, Microsoft

In addition, government regulators in the U.S. and abroad, who are intent on preventing the recurrence of an economic crisis, have enacted new measures, some of which make it more challenging to respond to strategic risks, such as the growth in alternative digital banking services.

And finally, customer loyalty metrics have been in decline, led in part by the public's negative sentiment toward the financial services industry and giving way to grass roots efforts such as the Move Your Moneyproject. A 2012 World Retail Banking report from Capgemini noted that of the 18,000 customers surveyed in 35 countries, 40% were "unsure" whether they'll stay with their current bank long-term.

[Bank customers say they are having fewer positive customer experiences, according to a new Capgemini study: Positive Customer Experiences Decline, Raising Alarm]

In the midst of this shifting landscape, the industry is ripe with opportunity, but it falls to risk managers to take a balanced approach in mitigating risk, while allowing for continued business growth. And such growth won't be possible without CMOs taking steps to expand the customer base and strengthen the loyalty of those that already exist.

The availability of new data types, such as online customer reviews, customer sentiment analysis, socio-political events, or macro-economic trends provides a compass of sorts, helping risk managers improve their oversight of risk positions and regulatory compliance, and giving CMOs a better understanding of customer preferences.

While processing, calculating and analyzing data is not new to an industry long steeped in margins, rates and yields, today's financial institutions are seeing the use of data as a new form of currency. Combining current, more traditional data with less traditional, unstructured data streams, and feeding them into an analytics solution, can help CMOs interpret the life of the customer, how they use your product and where there's an opportunity to meet an unmet need.

Likewise, risk managers can begin identifying factors that are more peripheral, such as macro-economic or atmospheric data, but which have some bearing on how they approach risks.

For example, the Royal Bank of Scotland (a Microsoftcustomer) is using insights from data to monitor the core currencies used by U.K. manufacturers in their supply chains, as well as to see how the cross-currency interdependencies increase/decrease supply chain risk. Another institution -- Credit Suisse -- is using Microsoft's data analytics platform, enabling employees to view risk across various organizational silos globally.

Microsoft recently commissioned IDC to conduct research across industries to better understand what businesses globally -- including the financial sector -- stand to gain by propagating a "data culture" across their organization. The numbers were eye-popping.

Over the next four years, the research showed that financial services institutions and related companies worldwide have the potential to gain more than $308 billion in value from data, or what we call the "data dividend." Of that amount, $131 billion of value is forecast to come through improvements in areas such as human capital, IT optimization and regulatory compliance measures -- including risk management.

To be sure, realizing the full potential of this data dividend will require that financial institutions no longer settle for status quo. Instead, they can look to cloud-based, big data analytics as a viable solution. Rather than deploying costly, on-premise compute grids that are left unused much of the time, cloud-based computing resources offer flexible, high-performance computing capabilities that give financial institutions the context they need to deal with emerging risks appropriately.

These same solutions can be used to harness new streams of data and the capabilities of machine learning and cloud-based analytics tools, ensuring banks that their "single source of truth" is informed by all of the data available within the organization, rather than merely relying on data within a particular line of business.

Companies should consider the following guidelines to harness the full potential of data, both big and small:

1.There is an inherent difference between information -- the raw data that lives within an institution's computer network -- and knowledge, the understanding of how to harness and apply that information. This nuance is especially critical in making decisions for banks, capital markets firms and insurance companies that are seeking to monetize data. Without education and understanding, the value of the information will be unrealized and the opportunity to analyze and use it lost.

2.The potential of that information is only as useful as the ability to access and use it by the appropriate people. We advocates the democratization of BI through self-service tools. Although IT must retain control of data, the tools for the analysis and interpretation of data insights must be in the hands of business users. Ensure employees across all levels of the organization understand the potential of data and have the tools in place to analyze, visualize and share their findings.

3.Start with "what if" scenarios and questions. Don't drive a business initiative by thinking about data management and what can be collected in an enterprise data warehouse. Think about what insights are needed to properly assess a risk.

4.Begin with an easily quantifiable, easily manageable project that promises unique insights. Then, build on that success. Make sure that the data platform you're building on can scale as you expand the scope of your big data initiatives, both in terms of raw data processing power, analytics, and ability to surface insights in widely-used productivity and collaboration tools.

By using modern, cloud-based data analytics solutions, and analysis tools that allow business users to visualize and interpret information, risk managers and CMOs can combine legacy and on-premise, cloud-based and third-party data into one, truly single source of truth that helps them deftly anticipate and mitigate risks as they emerge, and stay the course in fulfilling the company's vision.

Colin Kerr is Industry Solutions Director, Microsoft. He is responsible for defining Microsoft's vision, partner and go-to-market strategy for business analytics and banking operations solutions across the worldwide financial services sector.

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