Category Archives: Banking & Capital Markets

Regulation Ready: People, Processes and Technology, oh my!

Regulation Ready

Regulation Ready

Data Governance, the art of being Regulation Ready is about a lot of things, but one thing is clear. It’s NOT just about the technology. You ever been in one of those meetings, probably more than a few, where committees and virtual teams discuss the latest corporate initiatives? You know, those meetings where you want to dip your face in lava and run into the ocean? Because at the end of the meeting, everyone goes back to their day jobs and nothing changes.

Now comes a new law or regulation from the governing body du jour. There are common threads to each and every regulation related to data. Laws like HIPAA even had entire sections dedicated to the types of filing cabinets required in the office to protect healthcare data. And the same is true of regulations like BCBS 239, CCAR reporting and Solvency II. The laws ask; what are you reporting, how did you get that data, where has it been, what does this data mean and who has touched it. Virtually all of the regulations dealing with data have those elements.

So it behooves an organization to be Regulation Ready. This means those committees and virtual teams need to be driving cultural and process change. It’s not just about the technology; it’s as much about people and processes. Every role in the organization, from the developer to the business executive should embed the concepts of data governance in their daily work. From the time a developer or architect builds a new system, they need to document and define everything and every piece of data. It reminds me of days writing code and remembering to comment each code block. And the business executive likewise is sharing business rules and definition from the top so they can be integrated into the systems that eventually have to report on it.

Finally, the processes that support a data governance program are augmented by the technology. It may seem to suffice, that systems are documented in spreadsheets and documents, but those are more and more error prone and in the end not reliable in audit.

Informatica is the market leader in data management infrastructure to be Regulation Ready. This means, everything, from data movement and quality to definitions and security. Because at the end of the day, once you have the people culturally integrated, and the processes supporting the data workload, a centralized, high performance and feature rich technology needs to be in place to complete the trifecta. Informatica is pleased to offer the industry this leading technology as part of a comprehensive data governance foundation.

Informatica will be sharing this vision at the upcoming Annual FIMA 2015 Conference in Boston from March 30 to April 1. Come and visit Informatica at FIMA 2015 in Booth #3.

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What’s Driving Core Banking Modernization?

Renew

What’s Driving Core Banking Modernization

When’s the last time you visited your local branch bank and spoke to a human being? How about talking to your banker over the phone?  Can’t remember?  Well you’re not alone and don’t worry, it’s not a bad thing. The days of operating physical branches with expensive workers to greet and service customers  are being replaced with more modern and customer friendly mobile banking applications that allow consumers to deposit checks from the phone, apply for a mortgage and sign closing documents electronically, to eliminating the need to go to an ATM and get physical cash by using mobile payment solutions like Apple Pay.  In fact, a new report titled ‘Bricks + Clicks: Building the Digital Branch,’ from Jeanne Capachin and Jim Marous takes an in-depth look at how banks and credit unions are changing their branch and customer channel strategies to meet the demand of today’s digital banking customer.

Why am I talking about this? These market trends are dominating the CEO and CIO agenda in today’s banking industry. I just returned from the 2015 IDC Asian Financial Congress event in Singapore where the digital journey for the next generation bank was a major agenda item. According the IDC Financial Insights, global banks will invest $31.5B USD in core banking modernization to enable these services, improve operational efficiency, and position these banks to better compete on technology and convenience across markets. Core banking modernization initiatives are complex, costly, and fraught with risks. Let’s take a closer look. (more…)

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Posted in Application Retirement, Architects, Banking & Capital Markets, Data Migration, Data Privacy, Data Quality, Vertical | Tagged , , | Leave a comment

Banks and the Art of the Possible: Disruptors are Re-shaping Banking

Banks and the Art of the Possible

Banks and the Art of the Possible: Disruptors are Re-shaping Banking

The problem many banks encounter today is that they have vast sums of investment tied up in old ways of doing things. Historically, customers chose a bank and remained ’loyal’ throughout their lifetime…now competition is rife and loyalty is becoming a thing of a past. In order to stay ahead of the competition, gain and keep customers, they need to understand the ever-evolving market, disrupt norms and continue to delight customers. The tradition of staying with one bank due to family convention or from ease has now been replaced with a more informed customer who understands the variety of choice at their fingertips.

Challenger Banks don’t build on ideas of tradition and legacy and see how they can make adjustments to them. They embrace change. Longer-established banks can’t afford to do nothing, and assume their size and stature will attract customers.

Here’s some useful information

Accenture’s recent report, The Bank of Things, succinctly explains what ‘Customer 3.0’ is all about. The connected customer isn’t necessarily younger. It’s everybody. Banks can get to know their customers better by making better use of information. It all depends on using intelligent data rather than all data. Interrogating the wrong data can be time-consuming, costly and results in little actionable information.

When an organisation sets out with the intention of knowing its customers, then it can calibrate its data according with where the gold nuggets – the real business insights – come from. What do people do most? Where do they go most? Now that they’re using branches and phone banking less and less – what do they look for in a mobile app?

Customer 3.0 wants to know what the bank can offer them all-the-time, on the move, on their own device. They want offers designed for their lifestyle. Correctly deciphered data can drive the level of customer segmentation that empowers such marketing initiatives. This means an organisation has to have the ability and the agility to move with its customers. It’s a journey that never ends -technology will never have a cut-off point just like customer expectations will never stop evolving.

It’s time for banks to re-shape banking

Informatica have been working with major retail banks globally to redefine banking excellence and realign operations to deliver it. We always start by asking our customers the revealing question “Have you looked at the art of the possible to future-proof your business over the next five to ten years and beyond?” This is where the discussion begins to explore really interesting notions about unlocking potential. No bank can afford to ignore them.

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Posted in B2B Data Exchange, Banking & Capital Markets, Business Impact / Benefits, Business/IT Collaboration, Cloud Data Integration, Data Services, Financial Services | Tagged , , , , | Leave a comment

Financial Transformation is Really About Fixing the Business

clean data

Clean Data

According to Strategy and Business, the “CFO role is expanding to include being the company’s premier champion of strategic discipline.” It is no wonder that financial transformations are so much in vogue these days. According to The Conference Board, 81% of the companies that it surveyed are involved in a major financial transformation initiative. However, only 27% of these firms claim that they had achieved the benefits that were defined within their business case. Of the reasons for failure, the most interesting is thinking the transformation would be some kind of big bang. The problem is this type of thinking is unrealistic for today’s hyper competitive business environment. Financial strategy today needs be an enabler of business strategy. This means that it needs to be able to support the increasingly shorter duration of business strategy.

Financial Transformation needs to Enable Business Agility

Financial Transformation

Financial Transformation needs to Enable Business Agility

I have discovered the same thing in my discussions with IT organizations. In other words, enabling business strategies increasingly need to be built with a notion of agility. This means for financial strategies that they to need to first and foremost make organizations more agile and enable more continuous business change. Think about the impact of an organization that has as part of its strategy inorganic acquisition. This all means that thinking that a multi-year ERP implementations will on it’s own deliver financial transformation alone is unrealistic.

While it is absolutely fair to determine what at the manual tasks financial teams can eliminate, it does not make sense to think that they are done once an ERP implementation is completed. Recently, I was talking with a large accounting consulting and integration firm, they let me know that they really liked doing large ERP implementations and re-implementations, but they also knew that they would soon break under the weight of financial and business change unless flexibility was built in from the start. Financial transformation must start by creating business flexibility and agility to work in today’s business environment.

Does Your Close Process Get in the Way?

Financial Transformation

Best Practices

But achieving better financial agility and profitability improvement capabilities is often limited by the timeliness, trustworthiness of data. This why CFOs say that they spend so much of their time on the close process. According to the MIT CFO Summit Survey, nearly half of the organizations surveyed are feeling pressure from senior leadership to become more data driven and analytical. Data clearly limits the finance function ability to guide corporate executives, business-unit managers, and sales and marketing functions in ways to ensures business profitable and growth.

Financial Transformations Need to Fit Business Strategy

Financial Transformations

Financial Transformations Need to Fit Business Strategy

At the same time, it cannot be stressed enough that successful financial transformations need to be designed to fit with the company’s larger business strategy. The Conference Board suggests financial organizations should put real emphasis upon transformations that grow the business. Jonathan Brynes at the MIT Sloan School has suggested “the most important issue facing most managers …is making more money from their existing businesses without costly new initiatives”. In Brynes’ cross industry research, he found that 30% or higher of each company’s businesses are unprofitable. Brynes claims these business losses are offset by what are “islands of high profitability”. The root cause of this issue he asserts is the inability of current financial and management control systems to surface profitability problems and opportunities for investment to accelerate growth. For this reason, financial transformations should as a business goal make it easier to evaluate business profitability.

In a survey from CFO magazine, they found that nearly all the survey respondents said their companies are striving to improve profitability over the next year. 87% said their companies needed to analyze financial and performance data much more quickly if they were to meet business targets. However, only 12% said their finance organizations can respond to requests for financial reports and analysis from business managers in real or near-real time. At the same time, business managers are expecting finance staff to be able to tell the story behind the numbers — to integrate financial and operational data in ways that get at the drivers of improvement.

We Are Talking About More than Financial Decision Making

This means not just worrying about financial decision making, but ensuring that the right questions and the right insights are being provided for the business. As Geoffrey Moore has indicated economies of scale and market clout are no longer the formidable barriers to entry that they once were. The allocation of resources must be focused on a company’s most distinctive business capabilities—those things that provide the enterprise its “right to win”. To be a strategic, CFOs need to become a critical champion of the capabilities system, making sure it gets the investment and consideration it needs. This accentuates your ongoing role as a voice of reason in M&A—favoring acquisitions that fit well with the company’s capabilities system, and recommending divestitures of products and services that don’t.

Parting Remarks

Today, the CFO role is being transformed to increasingly be a catalyst for change. This involves increasingly helping companies focus upon the business capabilities that drive value. CFOs are uniquely positioned to take on this challenge. They are the company leader that combines strategic insight with a line of sight into business execution. Moreover, unlike other change agents, CFOs have the power of the purse. However, to do this their financial transformations need to ensure business agility and improve their and the businesses ability to get and use data.

Related links:

CFOs Move to Chief Profitability Officer

CFOs Discuss Their Technology Priorities

The CFO Viewpoint upon Data

How CFOs can change the conversation with their CIO?

New type of CFO represents a potent CIO ally

Competing on Analytics

The Business Case for Better Data Connectivity

Twitter: @MylesSuer

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How to Improve Cross Sell and Customer Experience in Banking

Customer Experience in Banking

Customer Experience in Banking

I recently refinanced an existing mortgage on an investment property with my bank. Like most folks these days, I went to their website from my iPad, fill out an online application form, and received a pre-approval decision. Like any mortgage application, we stated our liabilities and assets including credit cards, auto loans, and investment accounts some of which were with this bank.  During the process I also entered a new contact email address after my email service was hacked over the summer.  The whole process took quite a bit of time and being an inpatient person I ended up logging off and coming back to the application over the weekend.

I walked into my local branch the following week to do a withdrawal with my bank teller and asked how my mortgage application was going. She had no clue what I was talking about as though I was a complete stranger.  When I asked her if they had my updated email address that I entered online, she was equally puzzled stating that any updates to that information would require me to contact all the other groups that held my brokerage, credit card, and mortgage services to make the change. That experience was extremely frustrating and I felt like my bank had no idea who I was as a customer despite the fact my ATM card as printed on it “Customer Since 1989″! Even worse, I expected someone to reach out to me after entering my entire financial history on my mortgage application about moving my investment accounts to their bank however no one contacted me about any new offers or services. (Wondering if they really wanted my business??)

2015 will continue to be a challenge for banks large and small to grow revenue caused by low interest rates, increasing competition from non-traditional segments, and lower customer loyalty with existing institutions.  The biggest opportunity for banks to grow revenue is to expand the wallet with existing customers.  Though times are ahead as many bank customers continue to do business with a multitude of different financial institutions.

The average U.S. consumer owns between 8-12 financial products ranging from your basic checking, credit card, mortgages, etc. to a wider range of products from IRA’s to 401K’s as they get closer to retirement.  On the flip side the average institution has between 2-3 products per customer relationship.  So why do banks continue to struggle in gaining more wallet share from existing customers?  Based on my experience and research, it stems down to two key reasons including:

  • Traditional product-centric business silos and systems
  • Lack of a single trusted source of customer, account, household, and other shared data syndicated and governed across the enterprise

The first reason is the way banks are set up to do business. Back in the day, you would walk into your local branch office. As you enter the doors, you have your bank tellers behind the counter ready to handle your deposits, withdrawals, and payments. If you need to open a new account you would talk to the new accounts manager sitting at their desk waiting to offer you a cookie. For mortgages and auto loans that would be someone else sitting in the far side of the building equally eager to sign new customers. As banks diversified their businesses with new products including investments, credit cards, insurance, etc. each product had their own operating units. The advent of the internet did not really change the traditional “brick and mortar” business model. Instead, one would go to the bank’s website to transact or sign up for a new product however on the back end the systems, people, and incentives to sell one product did not change creating the same disconnected customer experience.  Fast forward to today, these product centric silos continue to exist in big and small banks across the globe despite CEO’s saying they are focused on delivering a better customer experience.

Why is that the case? Well, another reason or cause are the systems within these product silos including core banking, loan origination, loan servicing, brokerage systems, etc. that were never designed to share common information with each other. In traditional retail or consumer banks maintained customer, account, and household information within the Customer Information File (CIF) often part of the core banking systems. Primary and secondary account holders would be grouped with a household based on the same last name and mailing address. Unfortunately, CIF systems were mainly used within retail banking. The problem grows expotentially as more systems were adopted to run the business across core business functions and traditional product business silos. Each group and its systems managed their own versions of the truth and these environments were never set up to share common data between them.

This is where Master Data Management technology can help.  “Master Data” is defined as a single source of basic business data used across multiple systems, applications, and/or processes.  In banking that traditionally includes information such as:

  • Customer name
  • Address
  • Email
  • Phone
  • Account numbers
  • Employer
  • Household members
  • Employees of the bank
  • Etc.

Master Data Management technology has evolved over the years starting as Customer Data Integration (CDI) solutions providing merge and match capabilities between systems to more modern platforms that govern consistent records and leverage inference analytics in to determine relationships between entities across systems within an enterprise. Depending on your business need, there are core capabilities one should consider when investing in an MDM platform. They include:

Key functions: What to look for in an MDM solution?
Capturing existing master data from two or more systems regardless of source and creating a single source of the truth for all systems to share. To do this right, you need seamless access to data regardless of source, format, system, and in real-time
Defining relationships based on “business rules” between entities. For example: “Household = Same last name, address, and account number.” These relationship definitions can be complex and can change over time therefore having the ability to create and modify those business rules by business users will help grow adoption and scalability across the enterprise
Governing consistency across systems by identifying changes to this common business information, determining whether it’s a unique, duplicate, or update to an existing record, and updating other systems that use and rely on that information. Similar to the first, you need the ability easily deliver and update dependent systems across the enterprise in real-time. Also, having a flexible and user friendly way of managing those master record rules and avoid heavy IT development is important to consider.

Now, what would my experience have been if my bank had capable Master Data Management solution in my bank? Let’s take a look:

Process Without MDM With MDM Benefit with MDM
Start a new mortgage application online Customer is required to fill out the usual information (name, address, employer, email, phone, existing accounts, etc.) The online banking system references the MDM solution which delivers the most recent master record of this customer based on existing data from the bank’s core banking system and brokerage systems and pre-populates the form with those details including information for their existing savings and credit card accounts with that bank.
  • Accelerate new customer on-boarding
  • Mitigating the risk of a competitor grabbing my attention to do business with them

 

New email address from customer Customer enters this on their mortgage application and gets entered into the bank’s loan origination system MDM recognizes that the email address is different from what exists in other systems, asks the customer to confirm changes.The master record is updated and shared across the banks’ other systems in real-time including the downstream data warehouse used by Marketing to drive cross sell campaigns.
  • Ensure every part of the bank shares the latest information about their customer
  • Avoids any disruptions with future communication of new products and offers to grow wallet share.

The banking industry continues to face headwinds from a revenue, risk, and regulatory standpoint. Traditional product-centric silos will not go away anytime soon and new CRM and client onboarding solutionsmay help with improving customer engagements and productivity within a firm however front office business applications are not designed to manage and share critical master data across your enterprise.  Anyhow, I decided to bank with another institution who I know has Master Data Management.   Are you ready for a new bank too?

For more information on Informatica’s Master Data Management:

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The 3 Little Architects and the Big Bad Mr. Wolf – A Data Parody for today’s Financial Industry

The 3 Little Architects and the Big Bad Wolf

The 3 Little Architects

Once upon a time, there were 3 Information Architects working in the financial services industry, each with different firms and backgrounds but all responsible for recommending the right technology solutions to help their firms comply with industry regulations including ongoing bank stress testing across the globe.  Since 2008, bank regulators have been focused on measuring systemic risk and requiring banks to provide transparency into how risk is measured and reported to support their capital adequacy needs.

The first architect grew through the ranks starting as a Database Administrator, a black belt in SQL and COBOL programming. Hand coding was their DNA for many years and thought of as the best approach given how customized their business and systems were vs. other organizations. As such, Architect #1 and their team went down the path of building their data management capabilities through custom hand coded scripts, manual data extractions and transformations, and dealing with data quality issues through the business organizations after the data is delivered.   Though their approach and decisions delivered on their short term needs, the firm realized the overhead required to make changes and respond to new requests driven by new industry regulations and changing market conditions.

The second architect is a “gadget guy” at heart who grew up using off the shelf tools vs. hand coding for managing data. He and his team decides not to hand code their data management processes, instead adopt and built their solution leveraging best of breed tools, some of which were open source, others from existing solutions the company had from previous projects for data integration, data quality, and metadata management.  Though their tools helped automate much of the “heavy lifting” he and is IT team were still responsible for integrating these point solutions to work together which required ongoing support and change management.

The last architect is as technically competent as his peers however understood the value of building something once to use across the business. His approach was a little different than the first two. Understanding the risks and costs of hand coding or using one off tools to do the work, he decided to adopt an integrated platform designed to handle the complexities, sources, and volumes of data required by the business.  The platform also incorporated shared metadata, reusable data transformation rules and mappings, a single source of required master and reference data, and provided agile development capabilities to reduce the cost of implementation and ongoing change management. Though this approach was more expensive to implement, the long term cost benefit and performance benefits made the decision a “no brainer’.

Lurking in the woods is Mr. Wolf. Mr. Wolf is not your typical antagonist however is a regulatory auditor whose responsibility is to ensure these banks can explain how risk is calculated as reported to the regulatory authorities. His job isn’t to shut these banks down, instead making sure the financial industry is able to measure risk across the enterprise, explain how risk is measured, and ensure these firms are adequately capitalized as mandated by new and existing industry regulations.

Mr. Wolf visits the first bank for an annual stress test audit. Looking at the result of their stress test, he asks the compliance teams to explain how their data was produced, transformed, calculated, to support the risk measurements they reported as part of the audit. Unfortunately, due to the first architect’s recommendations of hand coding their data management processes, IT failed to provide explanations and documentation on what they did, they found the developers that created their systems were no longer with the firm. As a result, the bank failed miserably, resulting in stiff penalties and higher audit costs.

Next, Architect #2’s bank was next. Having heard of what happened to their peer in the news, the architect and IT teams were confident that they were in good shape to pass their stress test audit. After digging into the risk reports, Mr. Wolf questioned the validity of the data used to calculate Value at Risk (VaR). Unfortunately, the tools that were adopted were never designed nor guaranteed by the vendors to work with each other resulting in invalid data mapping and data quality rules and gaps within their technical metadata documentation. As a result, bank #2 also failed their audit and found themselves with a ton of on one-off tools that helped automate their data management processes but lacked the integration and sharing of rules and metadata to satisfy the regulator’s demand for risk transparency.

Finally, Mr. Wolf investigated Architect #3’s firm. Having seen the result of the first two banks, Mr. Wolf was leery of their ability to pass their stress test audits. Similar demands were presented by Mr. Wolf however this time, Bank #3 provided detailed and comprehensive metadata documentation of their risk data measurements, descriptions of the data used in each report, an comprehensive report of each data quality rule used to cleanse their data, and detailed information on each counterparty and legal entity used to calculate VaR.  Unable to find gaps in their audit, Mr. Wolf, expecting to “blow” the house down, delivered a passing grade for Bank 3 and their management team due to the right investments they made to support their enterprise risk data management needs.

The moral of this story, similar to the familiar one involving the three little pigs is about the importance of having a solid foundation to weather market and regulatory storms or the violent bellow of a big bad wolf.  A foundation that includes the required data integration, data quality, master data management, and metadata management needs but also supports collaboration and visibility of how data is produced, used, and performing across the business. Ensuring current and future compliance in today’s financial services industry requires firms to have a solid data management platform, one that is intelligent, comprehensive, and allows Information Architects to help mitigate the risks and costs of hand coding or using point tools to get by only in the short term.

Are you prepared to meet Mr. Wolf?

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Posted in Architects, Banking & Capital Markets, Data Governance, Data Integration, Data Integration Platform, Data Quality, Enterprise Data Management | Tagged , , , , | Leave a comment

Data Security – A Major Concern in 2015

Data Security

Data Security – A Major Concern in 2015

2014 ended with a ton of hype and expectations and some drama if you are a data security professional or business executive responsible for shareholder value.  The recent attacks on Sony Pictures by North Korea during December caught everyone’s attention, not about whether with Sony would release “The Interview” but how vulnerable we as a society are to these criminal acts.

I have to admit, I was one of those who saw the movie and found the film humorous to say the least and can see why a desperate regime like North Korea would not want their leader admitting they love margarita’s and Katy Perry. What concerned me about the whole event was whether these unwanted security breaches were now just a fact of life?  As a disclaimer, I have no affinity over the downfall of the North Korean government however what transpired was fascinating and amazing that companies like Sony continue to struggle to protect sensitive data despite being one of the largest companies in the world.

According to the Identity Theft Resource Center, there were 761 reported data security breaches in 2014 impacting over 83 million breached records across industries and geographies with B2B and B2C retailers leading the pack with 79.2% of all breaches. Most of these breaches originated through the internet via malicious WORMS and viruses purposely designed to identify and rely back sensitive information including credit card numbers, bank account numbers, and social security information used by criminals to wreak havoc and significant financial losses to merchants and financial institutions. According to the 2014 Ponemon Institute Research study:

  • The average cost of cyber-crime per company in the US was $12.7 million this year, according to the Ponemon report, and US companies on average are hit with 122 successful attacks per year.
  • Globally, the average annualized cost for the surveyed organizations was $7.6 million per year, ranging from $0.5 million to $61 million per company. Interestingly, small organizations have a higher per-capita cost than large ones ($1,601 versus $437), the report found.
  • Some industries incur higher costs in a breach than others, too. Energy and utility organizations incur the priciest attacks ($13.18 million), followed closely by financial services ($12.97 million). Healthcare incurs the fewest expenses ($1.38 million), the report says.

Despite all the media attention around these awful events last year, 2015 does not seem like it’s going to get any better. According to CNBC just this morning, Morgan Stanley reported a data security breach where they had fired an employee who it claims stole account data for hundreds of thousands of its wealth management clients. Stolen information for approximately 900 of those clients was posted online for a brief period of time.  With so much to gain from this rich data, businesses across industries have a tough battle ahead of them as criminals are getting more creative and desperate to steal sensitive information for financial gain. According to a Forrester Research, the top 3 breach activities included:

  • Inadvertent misuse by insider (36%)
  • Loss/theft of corporate asset (32%)
  • Phishing (30%)

Given the growth in data volumes fueled by mobile, social, cloud, and electronic payments, the war against data breaches will continue to grow bigger and uglier for firms large and small.  As such, Gartner predicts investments in Information Security Solutions will grow further 8.2 percent in 2015 vs. 2014 reaching $76.9+ billion globally.  Furthermore, by 2018, more than half of organizations will use security services firms that specialize in data protection, security risk management and security infrastructure management to enhance their security postures.

Like any war, you have to know your enemy and what you are defending. In the war against data breaches, this starts with knowing where your sensitive data is before you can effectively defend against any attack. According to the Ponemon Institute, 18% of firms who were surveyed said they knew where their structured sensitive data was located where as the rest were not sure. 66% revealed that if would not be able to effectively know if they were attacked.   Even worse, 47% were NOT confident at having visibility into users accessing sensitive or confidential information and that 48% of those surveyed admitted to a data breach of some kind in the last 12 months.

In closing, the responsibilities of today’s information security professional from Chief Information Security Officers to Security Analysts are challenging and growing each day as criminals become more sophisticated and desperate at getting their hands on one of your most important assets….your data.  As your organizations look to invest in new Information Security solutions, make sure you start with solutions that allow you to identify where your sensitive data is to help plan an effective data security strategy both to defend your perimeter and sensitive data at the source.   How prepared are you?

For more information about Informatica Data Security Solutions:

  • Download the Gartner Data Masking Magic Quadrant Report
  • Click here to learn more about Informatica’s Data Masking Solutions
  • Click here to access Informatica Dynamic Data Masking: Preventing Data Breaches with Benchmark-Proven Performance whitepaper
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Posted in Application ILM, Banking & Capital Markets, Big Data, CIO, Data masking, Data Privacy, Data Security | Tagged , , | Leave a comment

Happy Holidays, Happy HoliData.

Happy Holidays, Happy HoliData

In case you have missed our #HappyHoliData series on Twitter and LinkedIn, I decided to provide a short summary of best practices which are unleashing information potential. Simply scroll and click on the case study which is relevant for you and your business. The series touches on different industries and use cases. But all have one thing in common: All consider information quality as key value to their business to deliver the right services or products to the right customer.

HappyHoliData_01 HappyHoliData_02 HappyHoliData_03 HappyHoliData_04 HappyHoliData_05 HappyHoliData_06 HappyHoliData_07 HappyHoliData_08 HappyHoliData_09 HappyHoliData_10 HappyHoliData_11 HappyHoliData_12 HappyHoliData_13 HappyHoliData_14 HappyHoliData_15 HappyHoliData_16 HappyHoliData_17 HappyHoliData_18 HappyHoliData_19 HappyHoliData_20 HappyHoliData_21 HappyHoliData_22 HappyHoliData_23 HappyHoliData_24

Thanks a lot to all my great teammates, who made this series happen.

Happy Holidays, Happy HoliData.

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Posted in B2B, B2B Data Exchange, Banking & Capital Markets, Big Data, CIO, CMO, Customers, Data Governance, Data Quality, Enterprise Data Management, Financial Services, Governance, Risk and Compliance, Manufacturing, Master Data Management, PaaS, PiM, Product Information Management, Retail, SaaS | Tagged , | Leave a comment

Are The Banks Going to Make Retailers Pay for Their Poor Governance?

 

Retail and Data Governance

Retail and Data Governance

A couple months ago, I reached out to a set of CIOs on the importance of good governance and security. All of them agreed that both were incredibly important. However, one CIO retorted a very pointed remark by saying that “the IT leadership at these breached companies wasn’t stupid.” He continued by saying that when selling the rest of the C-Suite, the discussion needs to be about business outcomes and business benefits.  For this reason, he said that CIOs have struggled at selling the value of investments in governance and security investment. Now I have suggested previously that security pays because of the impact on “brand promise”.  And, I still believe this.

However, this week the ante was raised even higher. A district judge ruled that a group of banks can proceed to sue a retailer for negligence in their data governance and security. The decision could clearly lead to significant changes in the way the cost of fraud is distributed among parties within the credit card ecosystem. Where once banks and merchant acquirers would have shouldered the burden of fraud, this decision paves the way for more card-issuing banks to sue merchants for not adequately protecting their POS systems.

Accidents waste priceless time

Accidents waste priceless time

The judge’s ruling said that “although the third-party hackers’ activities caused harm, merchant played a key role in allowing the harm to occur.” The judge also determined that the bank suit against merchants was valid because the plaintiffs adequately showed that the retailer failed “to disclose that its data security systems were deficient.” This is interesting because it says that security systems should be sufficient and if not, retailers need to inform potentially affected stakeholders of their deficient systems. And while taking this step could avoid a lawsuit, it would likely increase the cost of interchange for more risky merchants. This would effectively create a risk premium for retailers that do not adequately govern and protect their IT environments.

There are broad implications for all companies who end up harming customer, partners, or other stakeholders by not keeping their security systems up to snuff. The question is, will this make good governance have enough of a business outcome and benefit that businesses will actually want to pay it forward — i.e. invest in good governance and security? What do you think? I would love to hear from you.

Related links

Solutions:

Enterprise Level Data Security

Hacking: How Ready Is Your Enterprise?

Gambling With Your Customer’s Financial Data

The State of Data Centric Security

Twitter: @MylesSuer

 

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Posted in Banking & Capital Markets, CIO, Data Governance, Data Security, Financial Services | Tagged , , , | Leave a comment

If Data Projects Weather, Why Not Corporate Revenue?

Every fall Informatica sales leadership puts together its strategy for the following year.  The revenue target is typically a function of the number of sellers, the addressable market size and key accounts in a given territory, average spend and conversion rate given prior years’ experience, etc.  This straight forward math has not changed in probably decades, but it assumes that the underlying data are 100% correct. This data includes:

  • Number of accounts with a decision-making location in a territory
  • Related IT spend and prioritization
  • Organizational characteristics like legal ownership, industry code, credit score, annual report figures, etc.
  • Key contacts, roles and sentiment
  • Prior interaction (campaign response, etc.) and transaction (quotes, orders, payments, products, etc.) history with the firm

Every organization, no matter if it is a life insurer, a pharmaceutical manufacturer, a fashion retailer or a construction company knows this math and plans on getting somewhere above 85% achievement of the resulting target.  Office locations, support infrastructure spend, compensation and hiring plans are based on this and communicated.

data revenue

We Are Not Modeling the Global Climate Here

So why is it that when it is an open secret that the underlying data is far from perfect (accurate, current and useful) and corrupts outcomes, too few believe that fixing it has any revenue impact?  After all, we are not projecting the climate for the next hundred years here with a thousand plus variables.

If corporate hierarchies are incorrect, your spend projections based on incorrect territory targets, credit terms and discount strategy will be off.  If every client touch point does not have a complete picture of cross-departmental purchases and campaign responses, your customer acquisition cost will be too high as you will contact the wrong prospects with irrelevant offers.  If billing, tax or product codes are incorrect, your billing will be off.  This is a classic telecommunication example worth millions every month.  If your equipment location and configuration is wrong, maintenance schedules will be incorrect and every hour of production interruption will cost an industrial manufacturer of wood pellets or oil millions.

Also, if industry leaders enjoy an upsell ratio of 17%, and you experience 3%, data (assuming you have no formal upsell policy as it violates your independent middleman relationship) data will have a lot to do with it.

The challenge is not the fact that data can create revenue improvements but how much given the other factors: people and process.

Every industry laggard can identify a few FTEs who spend 25% of their time putting one-off data repositories together for some compliance, M&A customer or marketing analytics.  Organic revenue growth from net-new or previously unrealized revenue is what the focus of any data management initiative should be.  Don’t get me wrong; purposeful recruitment (people), comp plans and training (processes) are important as well.  Few people doubt that people and process drives revenue growth.  However, few believe data being fed into these processes has an impact.

This is a head scratcher for me. An IT manager at a US upstream oil firm once told me that it would be ludicrous to think data has a revenue impact.  They just fixed data because it is important so his consumers would know where all the wells are and which ones made a good profit.  Isn’t that assuming data drives production revenue? (Rhetorical question)

A CFO at a smaller retail bank said during a call that his account managers know their clients’ needs and history. There is nothing more good data can add in terms of value.  And this happened after twenty other folks at his bank including his own team delivered more than ten use cases, of which three were based on revenue.

Hard cost (materials and FTE) reduction is easy, cost avoidance a leap of faith to a degree but revenue is not any less concrete; otherwise, why not just throw the dice and see how the revenue will look like next year without a central customer database?  Let every department have each account executive get their own data, structure it the way they want and put it on paper and make hard copies for distribution to HQ.  This is not about paper versus electronic but the inability to reconcile data from many sources on paper, which is a step above electronic.

Have you ever heard of any organization move back to the Fifties and compete today?  That would be a fun exercise.  Thoughts, suggestions – I would be glad to hear them?

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Posted in Banking & Capital Markets, Big Data, Business Impact / Benefits, Business/IT Collaboration, Data Governance, Data Integration, Data Quality, Data Warehousing, Enterprise Data Management, Governance, Risk and Compliance, Master Data Management, Product Information Management | Tagged , | 2 Comments