AI in Banking: Which is Better? Result or Ethics Driven?

What do you think about AI in banking? Have you ever wondered how do modern banks make underwriting decisions?

I read an inspiring article today:The AI-Bias Problem And How Fintechs Should Be Fighting It: A Deep-Dive With Sam Farao (by Annie Brown), which made me think about AI’s increasing power in the financial industry. AI is a great invention in the technology field, it’s convenient, it’s sufficient, and it’s more thoughtful than humankind; or does it?

Machine Ethics

While industry players are enjoying the fruits of big data, AI, and machine learning these days, we can not deny that AI bias is indeed the elephant in the room. I think we all agree that “diversity and inclusion” should be valued in the workplace. Especially since it’s one of the UN’s SDG (Sustainable Development Goals) Goals. Then, does that apply to “machine ethics” as well?

In the article, the author pointed out that the FinTech sector should address the bias issue when deploying AI in banking. I believe the implication is much more severe. The financial industry should be more careful when making data-driven decisions, especially when involving credit card or loan applications.

Have you watched Will Smith’s 2004 sci-fi movie “I, Robot“? At the beginning of the film, there was a scene when the robot made a judgment call and rescued Will Smith’s character,Detective Spooner. After comparing the survival rate of both, the robot used its AI brain and decided to let go of a little girl. The moral issue here was whether a result-driven decision is always the best cause of action.

Implications in Banking and Beyond

When it comes to credit linesduring underwriting, account balance, monthly income, industry, bank product holdings, and credit records are all common criteria. So what will happen when the engineer or the system itself decides to widen its parameters after we introduce AI in banking? When it starts to consider gender, education level, social interaction, activity participation, and more factors, can those disadvantaged people still have a fighting chance? (Is anyone also thinking of the “Nosedive” episode in Black Mirror?)

No doubt, AI in banking can speed up the decision-making process and make it more efficient and cost-effective. We see many FinTech companies already benefit from it, such as InsurTech Lemonade and China’s Ant Finance. In the past few years, the incumbents have been trying to increase their leverage and start a hiring spree for data scientists or machine learning experts. Along with the rapid development in machine learning, not all the underwriting and account opening decisions may be subject to AI’s call one day.

We can only urge that both players carefully embed AI-ethics when building their algorithms. Result-driven and high predicting power may not always contradict ethically-driven decisions. Banks must find a middle ground and reach a win-win situation, especially when financial inclusion is a topic highly valued nowadays.

What’s your view on AI in Banking? Give me a shout-out below, or drop me an email to let me know what you think.

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