Tag Archives: Compliance
According to Accenture – 2013 Global Consumer Pulse Survey, “85 percent of customers are frustrated by dealing with a company that does not make it easy to do business with them, 84 percent by companies promising one thing, but delivering another; and 58 percent are frustrated with inconsistent experiences from channel to channel.”
Consumers expect more from the companies they do business with. In response, many companies are shifting from managing their business based on an application-, account- or product-centric approach to a customer-centric approach. And this is one of the main drivers for master data management (MDM) adoption. According to a VP of Data Strategy & Services at one of the largest insurance companies in the world, “Customer data is the lifeblood of a company that is serious about customer-centricity.” So, better managing customer data, which is what MDM enables you to do, is a key to the success of any customer-centricity initiative. MDM provides a significant competitive differentiation opportunity for any organization that’s serious about improving customer experience. It enables customer-facing teams to assess the value of any customer, at the individual, household or organization level.
Amongst the myriad business drivers of a customer-centricity initiative, key benefits include delivering an enhanced customer experience – leading to higher customer loyalty and greater share of wallet, more effective cross-sell and upsell targeting to increase revenue, and improved regulatory compliance.
To truly achieve all the benefits expected from a customer-first, customer-centric strategy, we need to look beyond the traditional approaches of data quality and MDM implementations, which often consider only one foundational (yet important) aspect of the technology solution. The primary focus has always been to consolidate and reconcile internal sources of customer data with the hope that this information brought under a single umbrella of a database and a service layer will provide the desired single view of customer. But in reality, this data integration mindset misses the goal of creating quality customer data that is free from duplication and enriched to deliver significant value to the business.
Today’s MDM implementations need to take their focus beyond mere data integration to be successful. In the following section, I will explain 3 levels of customer views which can be built incrementally to be able to make most out of your MDM solution. When implemented fully, these customer views act as key ingredients for improving the execution of your customer-centric business functions.
Trusted Customer View
The first phase of the solution should cover creation of trusted customer view. This view empowers your organization with an ability to see complete, accurate and consistent customer information.
In this stage, you take the best information from all the applications and compile it into a single golden profile. You not only use data integration technology for this, but also employ data quality tools to ensure the correctness and completeness of the customer data. Advanced matching, merging and trust framework are used to derive the most up-to-date information about your customer. You also guarantee that the golden record you create is accessible to business applications and systems of choice so everyone who has the authority can leverage the single version of the truth.
At the end of this stage, you will be able to clearly say John D. who lives at 123 Main St and Johnny Doe at 123 Main Street, who are both doing business with you, are not really two different individuals.
Customer Relationships View
The next level of visibility is about providing a view into the customer’s relationships. It takes advantage of the single customer view and layers in all valuable family and business relationships as well as account and product information. Revealing these relationships is where the real value of multidomain MDM technology comes into action.
At the end of this phase, you not only see John Doe’s golden profile, but the products he has. He might have a personal checking from the Retail Bank, a mortgage from the Mortgage line of business, and brokerage and trust account with the Wealth Management division. You can see that John has his own consulting firm. You can see he has a corporate credit card and checking account with the Commercial division under the name John Doe Consulting Company.
At the end of this phase, you will have a consolidated view of all important relationship information that will help you evaluate the true value of each customer to your organization.
Customer Interactions and Transactions View
The third level of visibility is in the form of your customer’s interactions and transactions with your organization.
During this phase, you tie transactional information, historical data and social interactions your customer has with your organization to further enhance the system. Building this view provides you a whole new world of opportunities because you can see everything related to your customer in one central place. Once you have this comprehensive view, when John Doe calls your call center, you know how valuable he is to your business, which product he just bought from you (transactional data), what is the problem he is facing (social interactions).
A widely accepted rule of thumb holds that 80 percent of your company’s future revenue will come from 20 percent of your existing customers. Many organizations are trying to ensure they are doing everything they can to retain existing customers and grow wallet share. Starting with Trusted Customer View is first step towards making your existing customers stay. Once you have established all three states discussed here, you can arm your customer-facing teams with a comprehensive view of customers so they can:
- Deliver the best customer experiences possible at every touch point,
- Improve customer segmentation for tailored offers, boost marketing and sales productivity,
- Increase cross-sell and up-sell success, and
- Streamline regulatory reporting.
Achieving the 3 views discussed here requires a solid data management platform. You not only need an industry leading multidomain MDM technology, but also require tools which will help you integrate data, control the quality and connect all the dots. These technologies should work together seamlessly to make your implementation easier and help you gain rapid benefits. Therefore, choose your data management platform. To know more about MDM vendors, read recently released Gartner’s Magic Quadrant for MDM of Customer Data Solutions.
Gartner’s official definition of Information Governance is “…the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival and deletion of information. It includes the processes, roles, standards, and metrics that ensure the effective and efficient use of information in enabling a business to achieve its goals.” It therefore looks to address important considerations that key stakeholders within an enterprise face.
A CIO of a large European bank once asked me – “How long do we need to keep information?”
Keeping Information Governance relevant
This bank had to govern, index, search, and provide content to auditors to show it is managing data appropriately to meet Dodd-Frank regulation. In the past, this information was retrieved from a database or email. Now, however, the bank was required to produce voice recordings from phone conversations with customers, show the Reuters feeds coming in that are relevant, and document all appropriate IMs and social media interactions between employees.
All these were systems the business had never considered before. These environments continued to capture and create data and with it complex challenges. These islands of information that seemingly do not have anything to do with each other, yet impact how that bank governs itself and how it saves any of the records associated with trading or financial information.
Coping with the sheer growth is one issue; what to keep and what to delete is another. There is also the issue of what to do with all the data once you have it. The data is potentially a gold mine for the business, but most businesses just store it and forget about it.
Legislation, in tandem, is becoming more rigorous and there are potentially thousands of pieces of regulation relevant to multinational companies. Businesses operating in the EU, in particular, are affected by increasing regulation. There are a number of different regulations, including Solvency II, Dodd-Frank, HIPAA, Gramm-Leach-Bliley Act (GLBA), Basel III and new tax laws. In addition, companies face the expansion of state-regulated privacy initiatives and new rules relating to disaster recovery, transportation security, value chain transparency, consumer privacy, money laundering, and information security.
Regardless, an enterprise should consider the following 3 core elements before developing and implementing a policy framework.
Whatever your size or type of business, there are several key processes you must undertake in order to create an effective information governance program. As a Business Transformation Architect, I can see 3 foundation stones of an effective Information Governance Program:
Assess Your Business Maturity
Understand the full scope of requirements on your business is a heavy task. Assess whether your business is mature enough to embrace information governance. Many businesses in EMEA do not have an information governance team already in place, but instead have key stakeholders with responsibility for information assets spread across their legal, security, and IT teams.
Undertake a Regulatory Compliance Review
Understand the legal obligations to your business are critical in shaping an information governance program. Every business is subject to numerous compliance regimes managed by multiple regulatory agencies, which can differ across markets. Many compliance requirements are dependent upon the numbers of employees and/or turnover reaching certain limits. For example, certain records may need to be stored for 6 years in Poland, yet the same records may need to be stored for 3 years in France.
Establish an Information Governance Team
It is important that a core team be assigned responsibility for the implementation and success of the information governance program. This steering group and a nominated information governance lead can then drive forward operational and practical issues, including; Agreeing and developing a work program, Developing policy and strategy, and Communication and awareness planning.
But it’s not as easy as a couple of queries. The reality is that the body of knowledge in question is seldom in a shape recognizable as a ‘body’. In most corporations, the data regulators are asking for is distributed throughout the organization. Perhaps a ‘Scattering of Knowledge’ is a more appropriate metaphor.
It is time to accept that data distribution is here to stay. The idea of a single ERP has long gone. Hype around Big Data is dying down, and being replaced by a focus on all data as a valuable asset. IT architectures are becoming more complex as additional data storage and data fueled applications are introduced. In fact, the rise of Data Governance’s profile within large organizations is testament to the acceptance of data distribution, and the need to manage it. Forrester has just released their first Forrester Wave ™ on data governance. They state it is time to address governance as “Data-driven opportunities for competitive advantage abound. As a consequence, the importance of data governance — and the need for tooling to facilitate data governance —is rising.” (Informatica is recognized as a Leader)
However, Data Governance Programs are not yet as widespread as they should be. Unfortunately it is hard to directly link strong Data Governance to business value. This means trouble getting a senior exec to sponsor the investment and cultural change required for strong governance. Which brings me back to the opportunity within Regulatory Compliance. My thinking goes like this:
- Regulatory compliance is often about gathering and submitting high quality data
- This is hard as the data is distributed, and the quality may be questionable
- Tools are required to gather, cleanse, manage and submit data for compliance
- There is a high overlap of tools & processes for Data Governance and Regulatory Compliance
So – why not use Regulatory Compliance as an opportunity to pilot Data Governance tools, process and practice?
Far too often compliance is a once-off effort with a specific tool. This tool collects data from disparate sources, with unknown data quality. The underlying data processes are not addressed. Strong Governance will have a positive effect on compliance – continually increasing data access and quality, and hence reducing the cost and effort of compliance. Since the cost of non-compliance is often measured in millions, getting exec sponsorship for a compliance-based pilot may be easier than for a broader Data Governance project. Once implemented, lessons learned and benefits realized can be leveraged to expand Data Governance into other areas.
Previously I likened Regulatory Compliance as a Buy One, Get One Free opportunity: Compliance + a free performance boost. If you use your compliance budget to pilot Data Governance – the boost will be larger than simply implementing Data Quality and MDM tools. The business case shouldn’t be too hard to build. Consider that EY’s research shows that companies that successfully use data are already outperforming their peers by as much as 20%.[i]
Data Governance Benefit = (Cost of non-compliance + 20% performance boost) – compliance budget
Yes, the equation can be considered simplistic. But it is compelling.
A few weeks ago, a regional US bank asked me to perform some compliance and use case analysis around fixing their data management situation. This bank prides itself on customer service and SMB focus, while using large-bank product offerings. However, they were about a decade behind the rest of most banks in modernizing their IT infrastructure to stay operationally on top of things.
This included technologies like ESB, BPM, CRM, etc. They also were a sub-optimal user of EDW and analytics capabilities. Having said all this; there was a commitment to change things up, which is always a needed first step to any recovery program.
As I conducted my interviews across various departments (list below) it became very apparent that they were not suffering from data poverty (see prior post) but from lack of accessibility and use of data.
- Vendor Management & Risk
- Commercial and Consumer Depository products
- Credit Risk
- HR & Compensation
- Private Banking
- Customer Solutions
This lack of use occurred across the board. The natural reaction was to throw more bodies and more Band-Aid marts at the problem. Users also started to operate under the assumption that it will never get better. They just resigned themselves to mediocrity. When some new players came into the organization from various systemically critical banks, they shook things up.
Here is a list of use cases they want to tackle:
- The proposition of real-time offers based on customer events as simple as investment banking products for unusually high inflow of cash into a deposit account.
- The use of all mortgage application information to understand debt/equity ratio to make relevant offers.
- The capture of true product and customer profitability across all lines of commercial and consumer products including trust, treasury management, deposits, private banking, loans, etc.
- The agile evaluation, creation, testing and deployment of new terms on existing and products under development by shortening the product development life cycle.
- The reduction of wealth management advisors’ time to research clients and prospects.
- The reduction of unclaimed use tax, insurance premiums and leases being paid on consumables, real estate and requisitions due to the incorrect status and location of the equipment. This originated from assets no longer owned, scrapped or moved to different department, etc.
- The more efficient reconciliation between transactional systems and finance, which often uses multiple party IDs per contract change in accounts receivable, while the operating division uses one based on a contract and its addendums. An example would be vendor payment consolidation, to create a true supplier-spend; and thus, taking advantage of volume discounts.
- The proactive creation of central compliance footprint (AML, 314, Suspicious Activity, CTR, etc.) allowing for quicker turnaround and fewer audit instances from MRAs (matter requiring attention).
MONEY TO BE MADE – PEOPLE TO SEE
Adding these up came to about $31 to $49 million annually in cost savings, new revenue or increased productivity for this bank with $24 billion total assets.
So now that we know there is money to be made by fixing the data of this organization, how can we realistically roll this out in an organization with many competing IT needs?
The best way to go about this is to attach any kind of data management project to a larger, business-oriented project, like CRM or EDW. Rather than wait for these to go live without good seed data, why not feed them with better data as a key work stream within their respective project plans?
To summarize my findings I want to quote three people I interviewed. A lady, who recently had to struggle through an OCC audit told me she believes that the banks, which can remain compliant at the lowest cost will ultimately win the end game. Here she meant particularly tier 2 and 3 size organizations. A gentleman from commercial banking left this statement with me, “Knowing what I know now, I would not bank with us”. The lady from earlier also said, “We engage in spreadsheet Kung Fu”, to bring data together.
Given all this, what would you suggest? Have you worked with an organization like this? Did you encounter any similar or different use cases in financial services institutions?
In a recent survey of Informatica customers,
• Over 60% of companies had a security audit in the last year
• 35% of the companies had an internal security audit
• 16% of the companies had both an internal security audit and one performed by an external auditor
• In addition, many of these organizations saw that another company in their same industry suffered a data breach.
These results are reinforced by the discussions I had with Audit and Compliance IT owners from various industries. Audits are on the rise as more customers require these audits before purchase. Compliance IT requires reports at a database or system level showing that the data has been protected. And they want to see these reports on a regular basis as data, including test data pulled from production environments, changes frequently.
Driving these audits and Informatica projects to protect data were the following top regulatory drivers (as reported by customers):
These results are reinforced by the increasing use of Informatica’s regulatory and industry packs (containing pre-built rules and metadata), including PCI, PHI and PII. In addition to these areas, organizations I’ve spoken to are implementing projects to also protect non-public information, or confidential company information. For example, last week I spoke to a company about how they share detailed financial information about their company as part of the data they said to an outsourced partner. This financial information could be easily used to estimate company’s revenues and profits for any given quarter—before that information is released to the street, if at all.
In this same survey, the top benefits customers said that Informatica’s solution addressed included:
• Increasing productivity by leveraging pre-built masking techniques, accelerators and purpose-built tools
• Reducing the time it took to identify and capture optimal test cases, therefore reducing overall testing time
• Reducing the risk of data breach
Are you ready for your data security audit?
For more information on Informatica’s data security solutions for non-production environments, please join us for an upcoming webinar:
For more information on Informatica’s data security solutions in general, please see:
Data volumes are exploding. We see it all around us. The problem is that too much data can have a very negative impact on user productivity. Think about how long it takes to sift through emails after returning from vacation? Consider how long it takes to complete a purchase on an Ecommerce sight on Black Friday? The more data, the longer any of these processes take and the more time spent combing through more and more data. Informatica has been successfully working with Symantec and our customers through our partnership to help them find ways to control the impact of ‘too much data’. We are helping them to define projects that improve their ability to meet SLAs and application performance, reduce costs and mitigate any compliance risks – all while IT budgets remain relatively flat. (more…)
In this video, Peter Ku, director of solution marketing, Global Financial Services, Informatica, discusses the data challenges associated with FATCA compliance.
The Foreign Account Tax Compliance Act (FATCA) was signed into U.S law in March 2010 and is coming into effect on January 1, 2014. The new law will require Foreign Financial Institutions to report the names of U.S. persons and owners of companies who have bank accounts in these banks for tax reporting and withholding purposes.
Peter answers the following questions:
1) What is FATCA and what are the requirements financial services companies must comply with?
2) What must financial institutions do to successfully meet these requirements?
3) What do financial institutions need to address the data-related challenges and comply with FATCA?
The findings of the Cloud Market Maturity study, a survey conducted jointly by Cloud Security Alliance (CSA) and ISACA, show that government regulations, international data privacy, and integration with internal systems dominate the top 10 areas where trust in the cloud is at its lowest.
The Cloud Market Maturity study examines the maturity of cloud computing and helps identify market changes. In addition, the report provides detailed information on the adoption of cloud services at all levels within global companies, including senior executives. (more…)
The next facet of our data governance framework focuses on the three intentionally simplified dependent processes that constitute the data lifecycle. When educating your business sponsors and evangelists on the data lifecycle, I like to categorize it into these three broad areas: upstream processes, stewardship processes, and downstream processes. If you’re an enterprise or data architect, you’ll likely have a much more granular set of steps in a data lifecycle, which is perfectly fine. But when engaging with your business partners, keep it simple and they may actually listen! (more…)