Hugo Salvado



It all started in 2005, when I joined the biggest banking group in Portugal.

The initial challenge was to develop/improve tools which would better the lives of the 100+ people who worked in the bank’s real estate department (then Sogrupo IV, later Sogrupo GI).

Real Estate

From day one, it was clear that a new focus had to be given to our online presence. Our website was somewhat of “a dinosaur” (some ASP pages connected to an asynchronous MDB, manually updated/uploaded on a once-a-week basis).
Clearly, that was not enough.

I take pride in what our small team developed and made available to the public (Caixa Imobiliário and Imóveis Parceiros Caixa) and to the organisation (Imonet), for those were all solutions ahead of their times.

All aspects of the real estate marketing were covered (from outdoors to flyers, from newsletters to social media, from campaigns to live events) and, repeatedly, it felt like this team of 2~3 were putting out the numbers of a 10-man team.

Operational Risk

I welcome challenges and given the fact that my work had little to do with the banking business itself, I jumped off of my comfort zone and joined the Operational Risk team, where the downside of banking presents itself every day.

In the early 2000’s, with all the changes stemmed from the subprime crisis, banking model paradigma shift, and even the aftermath of the 9/11 attacks, banques were urged to take measures to address the risk of a change in value caused by the fact that actual losses, incurred for inadequate or failed internal processes, people and systems, or from external events (including legal risk), differ from the expected losses in their operation/activity.

After the Basel II Committee, seven types of operational risk were defined:

  1. Internal Fraud – misappropriation of assets, tax evasion, intentional mismarking of positions, bribery;
  2. External Fraud – theft of information, hacking damage, third-party theft and forgery;
  3. Employment Practices and Workplace Safety – discrimination, workers compensation, employee health and safety;
  4. Clients, Products, and Business Practice – market manipulation, antitrust, improper trade, product defects, fiduciary breaches, account churning;
  5. Damage to Physical Assets – natural disasters, terrorism, vandalism;
  6. Business Disruption and Systems Failures – utility disruptions, software failures, hardware failures;
  7. Execution, Delivery, and Process Management – data entry errors, accounting errors, failed mandatory reporting, negligent loss of client assets.

There was a vast amount of knowledge that I gained in those 3 years, especially related to remarkably relevant situations, procedures, strategies that banques undertake, which are as mandatory as publicly invisible.

Model Validation

If I were to describe model validation in a single sentence/expression, I would say “the Google algorythm”.
Just imagine the person in front of you in any bank branch, asking you your basic data in order to pre-aprove your credit card, your house mortgage, etc.
When a certain group of data is collected, an “OK” button is pressed and a giant machine, loaded with Big Data is put to work with the sole purpose of deciding if there will be a mutually profitable relationship between the bank and the cliente regarding a certain bank product (remember, banks are “money shops” that serve the interest of their clients, in a similar way that supermakets have groceries, hygiene products, or ice-cream available).

Within the Risk Management department, I have crossed paths with the highest talented people and, at the same time, the ones with the deepest and intricate knowledge of the banking industry.
The impact that high-level management may have in the bank strategy and course of action is based on data, data interpretation, modelling, forecast, etc.

So, repeating myself, “the Goog…”, errrrr… “the banking (product) algorythm“.
Obvioulsy, more than one. Quite obviously, a big big world to live in.

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