See how New York Life reduced more than 400,000 calls per year using VERINT’s solution and perform voice analysis

New York Life is one of the largest mutual life insurance companies in the entire world and the largest mutual life insurer in the United States today. We have over 6 million customers, 500 billion in assets, and we have the highest strength rating of all financial institutions. Our original business drives revolved around workforce management, optimisation, and forecasting. We track things on spreadsheets, which is very manual and doesn’t give you a lot of insight as you’re tracking.

It actually evolved from there to call recording, gone into quality monitoring. We use a lot of the Verint suite today into speech analytics, desktop analytics, and we’re going to be migrating probably to text analytics within the next 18 months.

Some of the cool things that we’re doing with the speech analytics system today to provide better business insight is building out what I would call a consumer health index. Most companies measure their health of their customers or their business based on typical means that you get from your financial accounting backgrounds. How’s our ROI? How’s our shareholder value? Since we’re a mutually-owned company, we’re a little more creative.

Consumer health index by using the speech analytics categories can tell you the percentage of times that a customer is dissatisfied, they’re confused, how many data processing errors they’re telling us we have, how much effort they have to go with. Things like that and how the agents are responding to the situation, such as agent ownership, displaying confidence in their phone calls, and most importantly being very professional at all times. We can scale that out and standardise the process to create a very positive customer service experience.

We have the ability to mine out and find those conversations where we don’t want agents talking like this, we don’t talk like that. The things that are egregious that you never want to hear on a phone call, we can mine those really quickly. Then there’s, most importantly, providing transparency and accountability all the way down the chain to make sure that our upper-level management, senior leadership is aware of that information. It’s mined down to the managers, mined down to the agents, and they’ve got to turnaround coaching in a respectable time frame, and as well as look for the positive answers, what drives a very positive experience when a customer says something like, “You did a great job. Thank you so much today.” How do you increase those interactions, which at the end of the day, goes back to the customer experience and keeping those customers for life.

We see from using this speech analytics platform to automate our quality solution, we found a 40% save on our FTEs on our quality assurance agents, with the people like analysts, that are checking those calls. Also, we run speech analytic studies by studying repeat phone calls so we can drive down our repeat calls on a month-over-month basis, which is a huge savings ROI.

We measured it out to over 400,000 calls a year for our sales organisation, sales effectiveness. If we could standardise our sales process and bring the lower tier agents, the ones that are struggling a little bit, to make them even mid-tier, the sales benefit is tremendous. We’ve seen, by studying that environment, an increase over six figures. New York Life, we have a need for both Verint support and as well as their professional services.

What I mean by that is there’s a need for planning. You need to review your data architecture, you need to make sure that when you’re in your own environment, that you’re not going to, for a lack of a better term, mess anything up because at the end of the day you don’t want to go backwards in your organisation, you want to keep moving forward. Professional service is something we highly engage with in our speech analytics process because there was definitely a need to make sure that when we were building out new KPIs, Key Performance Indicators, and then on top of that, establishing new adapters within the environment itself, that we did it all correctly so we were set up for success.