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Originally contributed by: Bill Britto Smart meters have made possible new services for customers, such as automated budget assistance and bill management tools, energy use notifications, and "smart pricing" and demand response programs. It is estimated that more than 50 million smart meters have been deployed as of July 2014. Utilities and customers alike are benefiting from these smart meter deployments. It is now obvious the world of utilities is changing, and companies are beginning to cater more to their customers by offering them tools to keep their energy costs lower. For example, several companies offer prepay to some of their customers who do not have bank accounts. For many of those "unbanked" customers, prepay could be the only way to sign up for a utility services. Understanding the value of prospects and the need to automate decisions to achieve higher revenue and curb losses is imperative to the utility. It is here where a decisioning solution, like PowerCurve OnDemand> can make a real difference for utility customers by providing modified decision strategies based on market dynamics, business and economic environments. Imagine what a best of class decision solution can do by identifying what matters most about consumers and business and by leveraging internal and external data assets to replace complexity with cost efficiency? Solutions like PowerCurve OnDemand deliver the power and speed-to-market to respond to changing customer demands, driving profitability and growing customer lifetime value – good for business and good for customers.

A new comarketing agreement for MainStreet Technologies’ (MST) Loan Loss Analyzer product with Experian Decision Analytics’ Baker Hill Advisor® product will provide the banking industry with a comprehensive, automated loan-management offering. The combined products provide banks greater confidence for loan management and loan-pricing calculations. Experian Decision Analytics Baker Hill Advisor product supports banks’ commercial and small-business loan operations comprehensively, from procuring new loans through collections. MST’s Loan Loss Analyzer streamlines the estimation and documentation of the Allowance for Loan and Lease Losses (ALLL), the bank’s most critical quarterly calculation. The MST product automates the most acute processes required of community bankers in managing their commercial and small-business loan portfolios. Both systems are data-driven, configurable and designed to accommodate existing bank processes. The products already effectively work together for community banks of varying asset sizes, adding efficiencies and accuracy while addressing today’s increasingly complex regulatory requirements. “Experian’s Baker Hill Advisor product-development priorities have always been driven by our user community. Changes in regulatory and accounting requirements have our clients looking for a sophisticated ALLL system. Working with MainStreet, we can refer our clients to an industry-leading ALLL platform,” said John Watts, Experian Decision Analytics director of product management. “The sharing of data between our organizations creates an environment where strategic ALLL calculations are more robust and tactical lending decisions can be made with more confidence. It provides clients a complete service at every point within the organization.” “Bankers, including many using our Loan Loss Analyzer, have used Experian’s Baker Hill® software to manage their commercial loan programs for more than three decades,” said Dalton T. Sirmans, CEO and MST president. “Bankers who choose to implement Experian’s Baker Hill Advisor and the MST Loan Loss Analyzer will be automating their loan management, tracking, reporting and documentation in the most comprehensive, user-friendly and feature-rich manner available.” For more information on MainStreet Technologies, please visit http://www.mainstreet-tech.com/banking For more information on Baker Hill, visit http://ex.pn/BakerHill

This is the first post in a three-part series. You’ve probably heard the adage “There is a little poison in every medication,” which typically is attributed to Paracelsus (1493–1541), the father of toxicology. The trick, of course, is to prescribe the correct balance of agents to improve the patient while doing the least harm. One might think of data governance in a similar manner. A well-disciplined and well-executed data governance regimen provides significant improvements to the organization. So too, an overly restrictive or poorly designed and/or ineffectively monitored data governance ecosystem can result in significant harm; less than optimal models/scorecards, inaccurate reporting, imprecise portfolio outcome forecasts and poor regulatory reports, subsequently resulting in significant investment and loss of reputation. In this blog series, we will address the issues and best practices associated with the broad mandate of data governance. In its simplest definition, data governance is the management of the availability, usability, integrity and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures and a plan to execute those procedures. Well, upon quick reflection, effective data governance is not simple at all. After all, data is ubiquitous, is becoming more available, encompasses aspects of our digital lives not envisioned as little as 15 years ago and is constantly changing as people’s behavior changes. To add another level of complexity, regulatory oversight is becoming more pervasive as regulations passed since the Great Recession have become more intrusive, granular and demanding. When addressing issues of data governance lenders, service providers and insurers find themselves trying to incorporate a wide range of issues. Some of these are time-tested best practices, while others previously were never considered. Here is a reasonable checklist of data governance concerns to consider: Who owns the data governance responsibility within the organization? Is the data governance group seen as an impediment to change or is it a ready part of the change management culture? Is the backup and retrieval discipline — redundancy and recovery — well-planned and periodically tested? How agile/flexible is the governance structure to new data sources? How does the governance structure document and reconcile similar data across multiple providers? Are there appropriate and documented approvals and consents from the data provider(s) for all disclosures? Are systemic access and modification controls and reporting fully deployed and monitored for periodic refinement? Does the monitoring of data integrity, persistence and entitled access enable a quick fix culture where issues are identified and resolved at the source of the problem and not settled by downstream processes? Are all data sources, including those that are proprietary, fully documented and subject to systemic accuracy/integrity reporting? Once obtained, how is the data stored and protected in both definition and accessibility? How do we alter data and leverage the modified outcome? Are there reasonable audits and tracking of downstream reporting? In the event of a data breach, does the organization have well-documented protocols and notification thresholds in place? How recently and to what extent have all data retrieval, manipulation, usage and protection policies and processes been audited? Are there scheduled and periodic reports made to the institution board on issues of data governance? Certainly, many institutions have most of these aspects covered. However, “most” is imprecise medicine, and ill effects are certain to follow. As Paracelsus stated, “The doctor can have a stronger impact on the patient than any drug.” As in medical services, for data governance initiatives those impacts can be beneficial or harmful. In our next blog, we’ll discuss observations of client data governance gaps and lessons learned in evaluating the existing data governance ecosystem. Make sure to read Compliance as a Differentiator perspective paper for deeper insight on regulations affecting financial institutions and how you can prepare your business. Discover how a proven partner with rich experience in data governance, such as Experian, can provide the support your company needs to ensure a rigorous data governance ecosystem. Do more than comply. Succeed with an effective data governance program.
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