As the bailouts continue and banks and large corporations go under, the excuse is always the same. "We did not adequately understand or estimate our risk exposure to these securities, banks, clients, policies, etc." In many cases, the beleaguered executives are telling the truth. They didn't see it coming because they operate their multibillion corporations in silos with little visibility across the enterprise. 
Until now, this has meant lost revenue and poor customer service as organizations are unable to efficiently market to and service their customers. For example, large global organizations with multiple divisions or business units generally have clients and trading partner information scattered across multiple transactional systems. Each division will have its own customer relationship management system. Even within the same division, customer information may be fragmented across billing, fulfillment and call centers. As a result, companies do not have the knowledge they need about their customers to effectively target or service them. Customer service and targeting have, by and large, driven the demand for a single view of client data. Companies addressing the issue in a variety of ways, typically with large, highly centralized CRM or data warehousing projects that often fail to solve the problem. 
Add to this what is now surfacing as the larger problem of risk management. 
Simply put, if you do not know your customers or trading partners intimately, you cannot accurately understand your risk exposure to them. Consider the example of a large global oil company that trades with thousands of counterparties every day. Many of those counterparties have investments in each other or are outright subsidiaries of each other. If the traders don’t understand the relationships within the counterparty information, they will trade on terms using a risk profile that is not accurate. Consequently, an organization could underestimate their risk exposure or grant clients overly generous terms of credit. 
When a bank is offering a customer a loan or an insurance company is underwriting a policy, the company needs to know all the business they are doing with that individual to accurately understand both the customer's value to them and the risk they are exposed to. If the customer has defaulted on payments in the past from a different account that is not properly linked, the customer may receive unduly favorable rates and the organization will have increased the risk of its portfolio without realizing it or without being compensated for the risk.

Financial Risk Management

Understanding the risk every new customer, trade or policy creates can be difficult, so it’s easy to see how difficult it is at an aggregate level for organizations to adequately understand their overall risk exposure and financial health. One cause is a backward-looking view of financial information. Large organizations often have multiple disparate financial systems due to M&A or system proliferation over time. To address this complexity, the office of the CFO employs an army of people who work around the clock at the end of the day, month, quarter and year to manually reconcile transactions across all the disparate financial systems, each with its own taxonomy. In this scenario, it is impossible for a CFO to get a real time or even near real-time snapshot of key financial ratios to assess risk, evaluate performance and take corrective action where necessary. 
This problem is further complicated by the poor quality of information in these systems. Client information is typically plagued with duplication, and the relationships and hierarchies between the legal entities is poorly understood. Even if information could be consolidated from a technology perspective by overcoming different application formats and data models, the business understanding to link two customers together because one is the corporate parent of the other is simply not there. And the problem is always increasing, as this data is typically fast changing. Without the ability to link clients to each other and to revenue and costs, it is impossible to tell which parts of the business are risky versus profitable. The result is executives managing by intuition. While this may work during good economic times, we’ve seen that it is far from failsafe in bad economic times where every risk is heightened due to market shocks. As a result, companies don't know their business is in trouble until it's too late. 

How Can Master Data Management Help?

By reconciling disparate master data (clients, products, vendors, chart-of-accounts, reference data) across the enterprise, MDM can provide organizations with a comprehensive and accurate view of their businesses, helping them understand their risk exposure to clients and vendors and their overall financial health. 
The first challenge is cleansing and aggregating the fragmented financial information. This is more challenging than it sounds, as the data is typically managed in multiple taxonomies across multiple diverse financial applications. For example, one system may categorize America into four territories, north, south, east and west, while another may categorize it into 10 territories including midwest, southwest, southeast, etc. Similarly, product categories and hierarchies will be represented differently. Cost center codes will be different in each system. Revenue and cost allocation methodology will be different. All this information must be accessed and then mapped into a common information format so it can be aggregated to provide an enterprise-encompassing financial picture. Manual processes to accomplish this are simply not good enough anymore, as the market has proven. The information is available too late to be of any value, and, in extreme cases, too late to save the company from financial disaster. 
During the aggregation process, a data quality and enrichment exercise is typically conducted. This includes cleansing the data with a focus on deduplicating the information, merging pieces of data into a global record, and resolving overlaps and inconsistencies. The next step is to enrich information by adding relationship and hierarchy information. There are many automated tools to assist with this process, but it can still be a services-intensive effort. Many companies shy away from such an exercise, but the cost of failure has become too high for organizations to continue to ignore it. While the initial project can seem time-consuming, it saves time in the long run by making it possible to automate business processes that depend on this data and by requiring less human intervention to decipher inaccurate or inconsistent data during everyday business activities. 
Once the initial consolidated view is created, it must be maintained on an ongoing basis. This has been the undoing of many solutions. Companies have become jaded because data cleansing and aggregation efforts didn’t hold up over time. Until the challenge of keeping clean data clean can be solved, benefits will be short-lived and future projects will not get funded. 
Mapping the diverse financial taxonomies into a common format involves business rules that are typically stored in the head of the finance users and, to make matters worse, are always changing. Finance departments have been averse to handing this over to IT, because it would encode the rules in a rigid manner and force finance to channel changes through a lengthy IT test and deployment procedure. To retain flexibility, business users sidestep the process and maintain and work from one-off spreadsheets and databases. In order for IT to bring the business users on board, they must provide a flexible solution that they can put back in the hands of those users. If business users had an easy-to-use interface to manage rules and data mapping, they wouldn’t have to circumvent the system, and it would speed up the process of aggregating financial information and building reports. 
Business rules aren’t the only thing in flux. The data itself is changing as businesses undergo reorganizations, mergers and acquisitions, and expansion into new geographies and businesses. Business users must be empowered to make updates in an efficient manner while IT and Operations retain visibility into the process to ensure security and compliance. 
Any consolidated financial repository must be kept in sync with all the individual financial systems where the transactions are being executed, and a detailed audit trail of all changes must be maintained for business and regulatory compliance. This can be accomplished by leveraging a real-time integration infrastructure. 
By aggregating financial information into a consolidated snapshot and empowering business users to manage ongoing rules and data changes, executives can have visibility into both risk and returns in shorter time cycles than current reporting technologies allow. They can respond to issues before they escalate into crises and can have active visibility into business operations at a global level. 
With MDM of financial data, c-level executives have actionable information in real time and no longer have the that they could not estimate exposure and risk.

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