Tag: Data Analytics

Learn From A Pirate - Negotiating Bank Products With Customers

Those Somali pirates are a wily bunch. While pirate attacks off the coast of East Africa are down, the average ransom is up. Most of the increase can be attributed to going after more modern ships and with better negotiating tactics.  The Economics of Security research initiative looked at 179 hijackings and interviewed professional pirate negotiators to see what can be gleaned. The results were not only interesting; they hold the keys for bankers looking to negotiate bank acquisition, a branch purchase, product pricing or a loan workout.

How Banks Can Make Better Use of Google Analytics

In 2017, Google Analytics is entry level stuff, but we are floored by how many banks are not taking advantage of the service on their website. We know when a bank isn’t using Google Analytics (GA) as we can see the source code on every bank’s site and see if it has the Javascript on it that communicates with GA.

Using Sentiment Analysis For Reputation Risk Management

Data Driven Reputation Risk Management

When it comes to risk management, one of the major pillars to monitor and manage is reputational risk. Unlike credit or interest rate risk, reputational risk is hard to define and even harder to quantify. Given the number of discussions on various news platforms, social media channels, and forums, there are hundreds and usually thousands of discussions taking place without a bank’s knowledge.

What Data Banks Use To Personalize Their Marketing

Personalized Marketing

When it comes to bank marketing, nothing is more important than directing your message at the right audience. In most cases, it is necessary to know a potential customer on a level deeper than their account number in order to earn their business and trust. Banks today are facing more competition than ever before, so treating someone as an individual rather than a one-dimensional account can be the deciding factor between gaining a life-long brand champion and losing one.

Why 3 and 5-Year Loan Maturities May Not Be The Best Idea

Loan Structuring

If truth be told, banks think very little on where to set their commercial loan maturities. That could be a mistake as setting maturity not only impacts credit and liquidity risk, but also has a significant impact on profitability. Today, we will step through two different loan structures to demonstrate the difference in both credit risk and risk-adjusted return. By understanding the finer points of setting future loan maturities, banks can improve performance.

 

An Example

 

MSA Home Price Stress Test Data

Interesting research from JP Morgan below using CoreLogic data that shows their stress test (similar to the Fed's CCAR scenarios) to various negative, severe and depression scenarios ranked by what city would suffer the most. Makes us remember what a 20% retrenchment would look like.  

 

Stress Test

The LTV vs. Pricing For Commercial Real Estate (2015 Edition)

LTV and Loan Pricing

Loan pricing depends on many things including cash flow, geography, property type, tenant mix, lease structure, borrower, loan structure and leverage. While loan pricing is primarily driven off cash flows, banks spend an inordinate amount of time worrying about loan-to-value (LTV), but little time adjusting for pricing. Today, we look at the relationship between LTV and loan pricing using data from the month of March.

 

The Data

 

Using Algorithmic Models To Train Your Bank Staff

Bank Performance  Models

One problem with training bank staff is the proverbial “Man with a hammer syndrome.” If you only have a hammer, then every problem appears to be a nail. In other words, if your bank has only solved problems one way, then it is a fair bet to say that they will keep on solving problems the same way. The problem is that bank staff needs to be trained with new mental (or physical) models so that they have more tools than just a hammer.

 

Why Some Banks Are More Profitable Than Others – The Nonlinear Customer Equation

Customer Profitability Equation

Why do some banks grind it out and struggle to produce a 9% return on equity ("ROE"), while other banks such as Bank of America and Chase produce 30% plus ROE for the same business segment? One answer is that banks that produce an above average ROE either have a more profitable customer segment focus, more profitable products or a more profitable business model. While we have covered the first two in previous blogs, today we highlight an aspect of a more profitable model known in bank profitability circles as the “non-linear customer equation.”

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