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Deloitte Analytics: Banking

Know what’s next

While analytics isn’t exactly new to the world of banking, plenty of banks are gearing up for their next big analytics push, propelled by a load of data and new, sophisticated tools and technologies. Why has business analytics jumped to the top of the priority list for banks? Pick a reason. Regulatory reform, managing risk, changing business models, expansion into new markets, a renewed focus on customer profitability – any one of these are reason enough for many banks to reconsider what today’s analytics capabilities can offer. A host of significant, recent changes in the banking industry have resulted in a long list of business challenges that the practice of business analytics may be positioned to address. Learn more about the offering.

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Banks need more in depth information to answer these and identify additional questions to effectively manage risk and drive risk-adjusted performance. Leveraging business analytics may help turn data into information that can provide these answers.

Learn more about the offering

Behind the headlines 

While there are a host of reasons banks are taking a fresh look at analytics, three in particular have emerged as specific drivers:

  • Regulatory reform. Major regulatory reforms such as Dodd-Frank, the CARD Act, FATCA (Foreign Account Tax Compliance Act) and Basel III have changed the business environment for banks. Historically, much of the investment in risk systems and more sophisticated risk analytics, particularly in larger banks, had been driven by regulatory requirements such as Basel II. The banks did what regulators required without truly examining how this was applicable to their current business model, products and business practices. The analytics for capital and risk estimation may not have been as effectively applied in decisions on products, pricing, portfolio management and underwriting decisions. The crisis has showed that the analytical techniques inherent in regulator-prescribed approaches may not have been as effective in measuring the specific risks of some complex products. Banks should revisit how they analyze the risks posed by these products and improve their approaches to measurement.
  • Operational efficiency. While banks have trimmed a lot of fat over the past few years, there’s still plenty of room for improvement. Duplicative systems. Manual reconciliation tasks. Increasing information costs due to reporting across different systems, producing inconsistent results. These are a few of the operational challenges that banks are facing as they look to grow again.
  • Customer profitability. Personalized offerings are expected to play a big role in attracting and retaining customers, but studies show that a small percentage of bank executives have strong capabilities in this area. At the same time, new restrictions on fee income and interest rates makes it even more important to understand the economics of each customer and find ways to gain wallet share in the more profitable segments. To win, banks should rethink how they segment and target their customers to achieve a bigger share of wallet, leveraging social analytics and unstructured data to come up with sophisticated models for sales and servicing.

The good news is that banks aren’t starting from scratch – they have remained at the forefront of data management and analytics. Plus, banks are practically swimming in data. Customer, pricing, credit bureau, macro-economic data and now unstructured data, you name it. There’s a lot of value that can be gleaned from this wealth of data.

But these are the same reasons that banks face some challenges when it comes to analytics. Their long history in managing and analyzing data can mean that they bring a lot of outdated legacy systems to the party – systems that may be past their prime and difficult to transition in a new environment. And no matter where it’s kept, the growing mountain of data banks have on hand can make it hard to know where to start. Is the data trustworthy? Is it consistent from system to system? Is it accessible? Start asking questions like these and you may find yourself backing away from a new analytics initiative.

But it doesn’t have to be that way. New tools and approaches can provide an additional resource to tap the value of data and smoothly transition from legacy systems. That’s where Deloitte excels.

How we can help

Deloitte is widely recognized as a leader in the field of analytics. And our deep experience in the banking industry means that we know how to bring analytics capabilities to life in the uniquely challenging environment of banking. We bring an unmatched range of capabilities in areas such as risk, finance and enterprise information management. And we have developed a host of accelerators and frameworks in each of these areas to help banks get their analytics capabilities up and running faster than ever.

Here are some of the specific areas where we’ve recently helped banks use analytics to gain a competitive edge:

Risk and finance integration
The ability to report to regulators in a timely manner is important to banks today; they are increasingly facing new requirements for better data governance and improved integration of risk and finance data. But many banks are only investing in one-off tactical fixes rather than focusing on a truly integrated risk-finance data solution that can address the root problems. Such “response-to-compliance” approaches to data management may result in more gaps, redundancies and inefficiencies.We focus on fully integrated solutions that are designed to address modified information reporting, analytics and data requirements as needed by regulators driven by BASEL III, Dodd-Frank or FATCA, etc.

Risk analytics
Recent events suggest that despite substantial investments in risk measurement and analytics, many banks may not be adequately measuring credit and market risks, nor are they applying analytics-driven insights to underwriting and investment decisions. Analytics capabilities developed for Basel II can hold significant potential to transform more bank offerings from products to pricing, portfolio management to underwriting. Additional areas of focus like stress testing, liquidity management, counterparty risk, regulatory reporting, internal audit analytics, fraud analytics are where we can help.

Customer analytics
Determining which prospects to target is one of the more important decisions banks make day in and day out. Some business lines (such as credit card) have become increasingly sophisticated in their understanding of prospect potential. But many others still seem to be in reactive mode, inadequately differentiating between prospects and rewarding sales efforts equally indiscriminately. Which customers and prospects may be interested in which additional products and services? How do they want to be reached? Analytics around customer acquisition, customer servicing, relationship development and customer retention can help answer important questions like these.

Bottom-line benefits

An effective analytics strategy can result in benefits such:

  • Increased ability to address and monitor regulatory compliance
  • Increased transparency and understanding of risk exposures to manage the business more effectively
  • Increased risk adjusted view of performance
  • Manage fraud effectively
  • Measure customer and product profitability
  • Identify "high-potential" prospects and customers
  • Increased ability to target products and services to prospects or customers
  • Improve the specific elements of the offer – product, pricing, channel
  • Allow senior management to make informed operational decisions

Five ways to get more value now

We’ve helped all types of banks deliver more value from their data using analytics. Here are some things we’ve learned along the way.

Start where you are.
Chances are, your organization already has many of the raw tools and capabilities required to begin its analytics journey. Assess your current capabilities and determine what you can begin doing today. While a long-term plan is important, don’t let excessive planning get in the way of targeted action.

Ask “crunchy” questions.
Crunchy questions are practical, highly specific queries that have answers you can actually use. They’re designed to lay the groundwork for action. The meeting you have on analytics should be filled with crunchy questions on what matters more to your industry, strategy and priorities.

Focus on signal strength. Detecting and responding to the signals hidden in your data is the key to achieving competitive advantage.

Invest in user engagement. Analytics has the potential to deliver the insights people need, in whatever forms they need them, to make effective decisions. The good news is that there are plenty of tools that can bring user engagement within reach, using intuitive interfaces and data visualization approaches that can bring additional insight for more users.

Use the right tools for the job. Analytics tools can be massively complex. For some challenges, that’s just what’s needed. For others, a simpler approach can be taken. Make sure you’re being careful to match the particular statistical and analytics techniques to the job at hand.

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Meet our people

Omer Sohail, Principal, Deloitte Consulting LLP

Brian Johnston, Principal, Deloitte Consulting LLP

As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.

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