I Knew You Were Trouble When You Walked In…

Unfortunately, most organizations don’t share the same powers of perception as Taylor Swift.

My bank doesn’t have a clue when trouble walks in, let alone when trouble takes out a loan, applies for a credit card, or goes on a shopping trip.

For decades, banks have relied on traditional credit scores to try and decide who to do business with, how much business to do, and how much to charge for it.

Banks have the almost unique capability to decide how much to charge each customer, based upon their credit score - and the discretion of the local branch manager. So business should be healthy, but time and time again banks choose to lend to those with little chance of paying their debts, and often decline business from people who would make good long-term customers.

Why is this?

Banks are constantly looking for high margin customers in the so-called ’sweet spot’ - those with low credit scores, but who have just enough means to keep paying back their debts, people who ‘max out’ on their credit cards, and take on extra credit to go shopping - often for luxury items.

This quest for the high margin customer is fraught with danger, often circumstances change, and the banks are left with bad debts.

What could banks do better?

In most cases, banks don’t have a good system for decision making with all of the relevant data in a single place - leaving business managers to make decisions based on incomplete information.

Check out #Qlik's James Fisher's analysis on how to build a relationship between the user and machine intelligence

Credit officers have to approve customer loans based on only the minimal amount of data points while the same customers demonstrate little loyalty, and can switch providers easily - and so the number of products sold to each customer is low, and information on customer behavior is thin.

Banks should strive to cross-sell better, to sell more products to each customer and build a richer set of information about each relationship. Instead of trying to push the boundaries in looking for the high margin loans, they should look to maximize profits through longer relationships, and build a better set of data around those relationships to drive decisions.

When banks get their decision-making systems in order they will be able to stop ‘trouble’ before it walks through the door, and make higher margins while talking less risk.

Longer relationships lead to higher product uptake and lower risk.

See more about what I mean and take a look at some of the solutions banks can deploy here.

Photo credit: JABMW14 via Foter.com / CC BY

Learn how data can help you avoid financial services troubles before they walk in the door at Visualize Your World. Coming to a city near you! Register here: http://go.qlik.com/VYW2016


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