Why ‘Explainability’ is Vital When it Comes to Financial Institutions

Sansa Stark from Game of Thrones probably couldn’t care less about why your financial institution values its credit card portfolio at $43.5 billion.

But the “tell me why” question is routinely posed to financial institutions by potential investors, auditors, and even customers when they ask about your financial calculations and asset valuations.

And you better have a good answer.

Explaining Explainability

Back in the good ‘ole days, explainability was easier.

Why did the Bank of This Here Wild West Town value its assets at $10,000? Because they counted up the cash that local cowpokes had deposited with them… and there was $10,000 in cash. Maybe they even took into account the potential interest they were going to make on money they had loaned out.

Fast forward to the good new days.

The number of financial assets that require valuation now far exceeds the total population of This Here Wild West Town (even if you include the cows).

Stocks and bonds. Negotiable investment securities. Credit card portfolios. Goodwill. Insurance liabilities. Intellectual property. Commercial intangible assets.

The valuation of entire banks, insurance companies, investment houses and other financial institutions is a commonly expected figure.

That all means lots, and lots, and lots of “tell me why” interrogations: Why did you give that number? What data points was it based on? Where did that data come from? How do you know that data is accurate? What logic was used to calculate and aggregate the data?

The Proof is in the Data

A valid calculation is pure data.

A valid valuation is data plus a professional eye to know how to evaluate the data.

If either are not based on data — or based on inaccurate data — you and your financial institution are in trouble.

Even if they are based on accurate data, if you can’t prove it, you’re in the same leaky boat.

You need to be able to trace the data path that led you to your decision — and the backstory for each of those data points. But sometimes trying to reconstruct the trail you took to get to a particular valuation makes you feel like the birds ate your trail of breadcrumbs.

That’s why you want to have data lineage in your back pocket. Automated data lineage.

Data lineage is the complete backstory of every piece of data: where it originated, where it ended up, what changes it underwent, and any other data that affected it along the way.

While this can be done manually, the speed and accuracy of manual data lineage falls just short of trying to trace your personal lineage back to the Middle Ages.

Enter automated data lineage.

That Explains it All

Automated data lineage creates an end-to-end map of your data’s journey through your entire BI environment. And it can usually do so more quickly than you can trace your lineage back to your great-great-grandmother.

Automated data lineage is a financial institution’s key partner when it comes to explainability. Not only does it enable you to quickly and easily show how you arrived at any calculation or valuation, but automated data lineage facilitates cleaner and more accurate data, leading to better calculations and valuations from the outset!

Data Lineage and Compliance

The last decade has seen significant regulatory changes with “why?” at their base. This is often inspired by the messy results of the lack of explainability on the part of financial institutions.

BCBS 239 followed the Great Recession of 2008–2009, to strengthen the data architectures supporting banks and their risk management systems.

IFRS 17 is an accounting standard introduced to solve the lack of transparency and consistency that was plaguing financial reporting when it came to insurance contracts. Investors and auditors couldn’t compare insurance contracts — even contracts issued by the same insurance provider!

The year 2020 saw the Securities Exchange Commission update their rules on how investment houses or funds must perform “Good Faith Determinations of Fair Value.” Proper valuation “promotes the purchase and sale of fund shares at fair prices, and helps to avoid dilution of shareholder interests,” while “improper valuation can cause investors to pay fees that are too high or to base their investment decisions on inaccurate information.”

Your financial institution’s credibility, compliance ability, and reputation are at stake if you can’t accurately answer the “why” question.

When you use automated data lineage for regulatory compliance, you can answer accurately and quickly every time, while using a minimum of BI team time and resources.

Getting to the Why

With the ability for explainability that automated data lineage provides, your institution can build your reputation with clients, increase trust with other financial institutions, and pass regulatory compliance bars with ease.

And if Sansa Stark does walk into your financial institution and demand that you tell her why you value your credit card portfolio at $43.5 billion, you’ll have an answer.