How to Avoid Silo Analytics for Improved Credit Decisioning (Part 2)

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.


Manage the analytic infrastructure

Doing so can reduce costs, integrate business processes and synchronize your risk appetite with consistent factors across functions.

All analytic decisions can be managed holistically rather than with a silo approach. From the analytic repository of attributes to the decisions tools use to do the analysis, streamlining across the enterprise can help organizations reduce product costs and increase implementation speed.

The analytic repository, as an example, should contain the necessary set of audited and documented attributes that can support a wide range of model and strategy development processes. The attributes would have all been tested for implementation, so their usage in new strategies poses no delay to implementation. A robust repository may contain 250–500 attributes that can be used to predict applicants with a high likelihood to default, which consumers are most likely to open a new account, or who is most likely to make a large purchase in the next six to 12 months. Because these attributes have been fully vetted up front, the timeline from business needs to analytics and implementation is drastically shorter than silo approaches where each analytic project is treated as an entirely new initiative.

Don't ignore implementation considerations

Can you implement the solution? Can you make changes? Do you have the environment to efficiently test changes and implement the changes quickly? These are essential questions you should ask to properly consider implementation.
We stress that lenders allocate time to vetting the cost and feasibility before developing new strategies or models. After development of a new solution, some lenders find themselves at a roadblock with implementation that can last several months and delay expected performance results. Lenders should look for ways to leverage simple, easy-to-implement solutions rather than solutions that bring unnecessary complexity to the table.

Moving forward

Getting the most out of your analytics solutions is critical to maximizing profits while minimizing exposure to unwanted risk. Unless your institution can afford to staff its own analytics department, this means you have to find a proven and trusted provider to guide you along the way.

The MeridianLink Achieve Analytics and Business Consulting team provides financial institutions of all sizes an affordable, yet industry-trusted, way to outsource your analytics department or ad-hoc projects. Custom scorecards are one of the most popular ways analytics are leveraged today to drive credit decisioning efficiency and profitability. If you'd like to learn more about how this is accomplished, please click the button below to download our eBook regarding the importance of custom scorecards.

Download Our eBook Today

Also, don't forget about next week's webinar on how analytics can be used to boost indirect lending success. Click here to register.

Photo Credit: Andrew K.