The best Algorithms for Banks

The best recommendation engine for banks

The Human Touch

While we speak a lot about technology, we want to underscore that sometimes the human touch is still more valuable and remains a competitive advantage.

Of course, one day a recommendation engine will be better than a human, but not yet. The process of recommending products is an opportunity for dialogue. While machine learning can do a better job than a human at recommending a product, it cannot capture and incorporate feedback. If a customer says no to international or wealth management services, it may be because they don’t need it, because their son-in-law is in the business or because they don’t feel comfortable enough to discuss it. A human can tell the difference, the best parallel processing computer array cannot.

Choosing To Maximize Customer Satisfaction Instead of Minimizing Expenses

Efficiency is on every bank’s radar. We all want to minimize costs. However, we have to make sure that we are maximizing customer loyalty, satisfaction, engagement, and happiness. 

Every bank loves to point to the automated phone routing system that most large banks employ. Customers listen to seven different options and then have to figure out which one best fits their objective. Automated phone systems are a fantastic cost-saving measure.

But, we hate dealing with them.

We would rather talk to a pleasant voice on the end as a customer. As a bank, we would rather have that opportunity to be fully present with that customer and try to both make an impression and create an emotional connection.

Service, Then Scale

We meet so many firms that want to make our banking business more efficient. We need it. However, we also want to grow one happy customer at a time. We know that if we don’t please the next customer, we will never have a chance to please that one-millionth customer.

 That personal touch is still the best algorithm engine we have found. Banks that don’t provide value will never have to worry about how to scale.