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Have you ever noticed how defensive some people can be when it comes to their favorite or family recipes? Depending on the food and the people involved, certain debates can get pretty passionate in a moment’s notice. Some swear their recipes are the gold standard for things such as chili, barbecue ribs, pies, cakes or any other food where contests are held to crown the best reign supreme. It even goes beyond individuals and spreads to different regions or communities for how things are done best.  Duels between award-worthy recipes are one thing, but what about the person who’s convinced blueberries belong in lasagna?

Following last week’s blog post regarding silo analytics, we’re going to take it one step further this week.  As opposed to last week’s topic, which centered on using a single piece of (or incomplete) information to represent a holistic view of the consumer, silo analytics also refers to decentralized or fragmented process for analytics. In this example, each department within the same organization (such as marketing, credit risk, acquisitions and collections) often rebuilds its analytic infrastructure from data gathering to the creation of analytic attributes rather than partnering across divisions to improve the speed to implementation. For the second part of this two-part series, this week's blog post will take a deeper look at what institutions can do to avoid such a decentralized and fragmented process.

Analytics can be an extremely profitable investment – assuming efficiency and completion. Financial institutions, whether they handle it in house or turn things over to a trusted provider, need to know if they’re victims of leveraging or being served silo analytics to dictate their credit decisioning.

For all of the football fans who subscribe to our blog, Sunday's big game will have your full attention. Even if you're not a football fan, the odds are pretty likely that you'll check it in some form or fashion to see the commercials or whoever performs at halftime. In last year's game, one team took a calculated risk by running a trick play that ultimately led it to victory (Philly special). Success on the football field, much like the real world, involves limiting risk while also at times using it to an advantage. Risk can come from anywhere. It can change at any moment and often be difficult to predict. For many financial institutions these days, risk management and control are split across multiple departments within an organization. Because these departments need structure, as well as checks and balances to properly management risk, the most successful institutions use a risk management strategy/model based on three lines of defense. This approach is an effective way to assign duties and coordinate various teams involved in the risk management and control process.

Security remains one of the most important topics for consumers as businesses continue to evolve in the digital age. As data breaches appear to become more commonplace, financial institutions everywhere are ratcheting up their security efforts to identify, assess and prevent fraud.  As someone who’s had his identity stolen a few years ago, I experienced the feeling of pure panic that crashes over you when realizing credit was fraudulently established in your name and you’re left to pick up the pieces. Despite the fact that most sophisticated thieves seem to always be one step ahead, it’s a battle that needs to be fought by every financial institution to maintain a level of trust with its customers or members. There are a number of different types of credit fraud. With a focus on origination of a loan, this blog post will describe the two most prevalent versions with regards to credit decisioning.

The 2008 financial crisis brought more attention to one crucial aspect of the financial system, which was the delay in the recognition of losses by financial institutions. At the peak of the crisis and under stressed conditions, it became clear that the methodologies and procedures in place at that time (and still in place today within some financial institutions) to estimate reserves resulted in inaccurate, underestimated and untimely allowances for losses.