How We Created the Heartbeat of TrueAccord

By on May 29th, 2018 in Industry Insights
TrueAccord Blog

The genesis of Heartbeat—the machine learning engine that makes TrueAccord debt collection a reality—is a story that demonstrates our commitment to consumers who hope to take control of their financial future. Heartbeat is how we create a more humane and thoughtful collection experience.

So What Is Heartbeat?

Heartbeat is a fully automated and reactive decision engine that uses a combination of machine learning and data-driven heuristics to determine the optimal way of interacting with each individual debtor. It tells us when we should contact them, how often, through which channel, with what content, and what specific types of offers we should provide. Most importantly, it is the engine that replaces an agent’s phone-based collection activities with a data-driven strategy, ultimately making the same decisions, but automatically, more quickly and with a bigger heart.  

How Was It Built?

We built Heartbeat with three key tenets in mind. The first is compliance: to create a pre-approved boundary for what should and shouldn’t be said to each debtor. The second is performance: how we leverage data-driven heuristics to test our assumptions and continually improve the performance of our debt collection system. And the third is the customer experience: how consumers engage with the product at every phase and how we ensure we’re seeing positive reactions. Put these all together and they constitute the core foundation of Heartbeat.

We Start with Data, Then We Test

The process starts with data, and lots of it. We’ve collected years of historical collections data to help determine the optimal way to communicate with consumers and generate the best collections model. We then set up an experimentation engine to test and refine the process for continuous improvement.

For the testing to be relevant, we ask a few key questions: Is this a problem that we can define well enough to solve and take action? Do we have enough data from different segments of our population to solve the problem for all of our customers, not just some? And does the result add value to the process? Otherwise, it’s not worth putting the time into it.

Once we decide to move forward, we establish a hypothesis (e.g. paydays are the best days to set up recurring payments) based on the intuition of our domain experts who know what an ideal customer journey should be like. We test our hypothesis with an A/B experiment to see if it performs better than our current status quo. The data we collect from these experiments shows us what tactics work best. To ensure we’re optimizing for various audiences,  we re-target the test to new segments until we have enough data to apply the new treatment to the broad audience.

Then Machine Learning Takes Over

The biggest challenge is that data and heuristics are not enough to offer highly personalized treatments at scale. At some point we have to transition, by taking the learning outcomes based on all of our initial data and programming them into a machine learning model. The goal here is to replace human heuristics with an automated decision-making model that continues to learn from multiple samples at scale. A human agent is prone to biases, such as using non-compliant language in their calls when pressed to make their monthly numbers or using the wrong tone based on a previous conversation that may have impacted their mood. A machine learning model doesn’t fall prey to these biases.

The more data we collect, the better the system gets and the more accurately it represents edge cases and special needs. Now with more than 2.5 million consumers and tens of million of interactions, we’re seeing great results and constant improvement. The larger sample sizes also allow us to reach a statistically significant result faster in large experiments, often in only 30 to 60 days.

What’s Next for Heartbeat?

Right now, only two percent of our customers still need to interact with one of our agents. That’s already a pretty impressive number, but we still want to reduce it even further.

We constantly scale the technology behind Heartbeat and improve its intelligent self-service capabilities that feature our three key tenets: better compliance (Heartbeat can navigate the legal restrictions with less risk than a person), better collections performance (50-500% better than our competition), and a better customer experience where consumers are empowered to manage their debt in a way that puts control back in their hands and treats them the way they want to be treated.  

At TrueAccord, we’ve always been committed to providing the best customer experience for a behaviorally complex debt collection process, and Heartbeat is true to its name in working to that objective.

Yes, 866-611-2731 is Our Number. Why is That so Important for TrueAccord?

By on May 23rd, 2018 in Company News, Debt Collection, Industry Insights
TrueAccord Blog

We wanted 866-611-2731 to be recognizable.

TrueAccord was built as a consumer facing brand from day one. We have one number, 866-611-2731, that we use for outbound and inbound calls. Our name is distinguishable, not a three letter acronym. We have Google reviews and an online presence. We wanted consumers to easily find, research, and comment on our presence. We want to make a difference.

You can’t help consumers if they don’t know who you are

Being in debt is scary, confusing, and generally not a great experience. When consumers are bombarded by calls from unknown numbers or worse, callers who pretend to be from their area code, their trust in phone calls erodes. Less trust leads to fewer contact rates, and disengaged consumers. Running away from your debt is a bad idea if the alternative is working with a customized, personalized, and digital first experience that actually helps you pay down what you owe. We wanted people to know who’s calling.

The thing is, debt collection can be a stepping stone. When turned into a cooperative and personalized experience, it can be a first step to getting back on your feet. People get into debt for many, diverse, largely unexpected reasons: divorce, job change, healthcare issues for them or a loved one. By making debt collection accessible, TrueAccord aims to be a part of your growth journey, not just focus on helping you pay a single debt. You’ll find customized payment options, an easy mobile experience, and a helpful customer service team (when you call our number, 866-611-2731).

Having a recognized number helps us call *less*

When consumers don’t pick up, the most common strategy is to call again. Agencies may call a number 5 times per day. At TrueAccord, we don’t think this is a good experience. When we call a consumer, even once, our recognized phone number allows them to find us online and be convinced that they want to talk. From there, going to our website or finding one of our emails in their inbox is a breeze. Self service is welcoming and easy. No more aggressive repeated phone calls when it’s least convenient.

Being customer-facing and helpful is our #1 goal. If you see 866-611-2731 in your caller ID, know that we’d love to help

Call us or click a link. Great experience in debt collection isn’t a myth anymore. That’s why we started TrueAccord, and why we want you to have an easy time finding us and talking to us.

Writing High Performing Compliant Content at TrueAccord

By on May 22nd, 2018 in Debt Collection, Industry Insights
TrueAccord Blog

Moving collection communications online means moving away from phone calls. Writing to consumers at scale draws a lot of scrutiny because of regulatory requirements and user experience considerations. Hear our Managing Paralegal and Director of PMO, Antonia Wong, discuss this with our Head of Design, Shannon Brown.

Collection Strategies and How TrueAccord Fits Into Them

By on May 15th, 2018 in Debt Collection, Industry Insights
TrueAccord Blog

New to collections? Looking to understand the moving parts? Or maybe you’re an experienced strategist looking to understand how to best use TrueAccord? Hear our Head of Business Development, Jason Hass, and Head of Client Services, Pej Azarm, talk about these important topics.

How artificial intelligence is reshaping jobs in banking

By on May 9th, 2018 in Industry Insights
TrueAccord Blog

American Banker wrote a story about the changing landscape of jobs in financial services. Following a recommendation from an industry analyst, the publication discussed how TrueAccord’s solution drives that change in debt collection.

Not everyone believes that humans are better at emotional work, like dealing with a sad or irate customer.

Sokolin argued that AI systems are good at emotional labor. He pointed to the debt-collection fintech TrueAccord, whose AI engine handles collections work for banks and card issuers.

“All they do is emotional labor, and they’re much better at it than people who call you during dinner,” he said.

Read the story here.

Comparing TrueAccord Operations with Bank Operations

By on May 8th, 2018 in Debt Collection, Industry Insights
TrueAccord Blog

Hear our Director of Operations, Lauren Sawicki, talk about the differences between running operations for a major bank versus TrueAccord. While both are collections related, the differences can sometimes be staggering.

How TrueAccord Scaled its Email Sends to Millions a Month

By on May 1st, 2018 in Data Science, Engineering and Data, Product and Technology
TrueAccord Blog

Scaling to sending millions of emails a month is a difficult task, and sending debt collection emails is exponentially harder. To prevent spam and abuse, email providers and infrastructure vendors developed tools and tactics that can easily hurt, blacklist, and eliminate not only the “bad guys” but also the uninitiated sender. Still, we scaled to sending millions of emails a month while enjoying high open and click-through rates that allow us to service consumers the way they want to be serviced (we use other channels as well, but focus on email here). We learned important lessons about scale along the way, through trial and error and calculated planning, and we’re sharing them today.

Challenges With Scaling Email

Email is one of the most penalized communication platforms. There are no filters or blockers or spam buttons when receiving a phone call, or picking up a letter from your mailbox, but email is equipped to keep the bad guys out and let the good guys in. ISPs (email inbox providers) design algorithms to keep the user happy and engaged, and an inbox full of spam is not very pleasant. Unfortunately, sometimes the algorithm gets it wrong, and what is actually an email with good intentions from a trusted sender gets filtered through as spam.

To further complicate the issue for email senders, each ISP has a different set of rules and regulations they filter for. What may be an acceptable email in Google is flagged as spam in Yahoo and vise versa. There is no clear rule book to refer to when attempting to scale emails to a very high volume. The algorithms are also always changing to react to real spammer behavior,  further complicating any attempt to create one clear step-by-step process for success.

The signals for spam prevention algorithms touch on many aspects of emails but include content, design, time, volume, and frequency of sending emails, consumer engagement, digital signatures, and many more. Getting everything right is complex, but if you get any of these wrong, you may find yourself indefinitely blacklisted and banned from emailing.

TrueAccord’s Unique Perspective

Operating in the debt collection space further complicates scaling emails. Even if consumers agreed to be contacted via email, they do not necessarily welcome them, leading to lower inbox placements than eCommerce brands. Despite this enormous hurdle, TrueAccord has similar engagement rates to that of eCommerce companies with up to 30% open rate and 14+% click through rates. IT took a lot of work and careful attention to detail to get us there.

TrueAccord uses machine learning algorithms to pick the best email to send to a specific person at the right time in their debt collections process. The team customizes content, time, and frequency of emails, slowly ramping up scale while monitoring performance. In addition, a lot of TrueAccord contact attempts are reactive, made in response to consumer action or feedback. Contacting consumers in context adds credibility and attracts consumer attention while they are still engaged, further improving their response rates. This close attention to detail coupled with engaging content and data driven targeting makes a significant difference. TrueAccord increases consumer engagement and signals to ISPs that its emails are legitimate, creating a virtuous cycle that improves inbox placement and consumer exposure to emails, again improving engagement.

Our Top Tips for Emails at Scale

We’ve polled our product and deliverability experts to offer you our top tips to follow when building a scalable email program. If you follow these you’ll have a better chance to replicate our success and experience engagement rates that will support, rather than hurt, your long term inbox placement.

Create Valuable Content

The most important aspect to scaling email is writing good content that looks reputable and is well designed. It’s important to earn the consumer’s trust and stay away from using words and phrases that trigger spam engines. TrueAccord accomplishes this by personalizing every email, and sending the right email at the right time during the debt collections process, while also passing every email through a robust approval process to maintain quality.

Consult Experts

Because consumer engagement and open rates are a cornerstone of our business practice, we work closely with a team of email deliverability experts and providers. They provide specific industry knowledge concerning each ISP and assist in the warm up strategy for each domain and IP address. Experts help audit deliverability programs as well as deal with ISP-specific challenges and knowhow.

Segment Domains and IP addresses

Utilizing segmented domains and IP addresses allows for growth and scale while limiting the risk to your reputation from a single mistake, which is one of the biggest traps for new email programs. TrueAccord segments email sends to manage sender reputation and distribute potential issues across multiple domains and IP so none of them see too many bounces or receive too many spam complaints, nor have a too high proportion of unopened emails.

Start Methodically and Slow

Scaling your program too early is heavily penalized even among high engagement senders. Most established companies who add an email strategy to an existing customer base make this mistake, which often cannot be undone. TrueAccord places strict limits on email volume growth to make sure ISPs don’t flag our systems.

This is especially important when starting out with a new client. When a new portfolio is added we will send a small group of several hundred test emails for a few days to measure general deliverability and bounce rates. This test cycle provides insight into the appropriate strategy to use for this specific portfolio. If bounce rates are normal, we can begin to send emails freely, but if the levels are higher than expected we’ll utilize high risk mitigation strategies.  

Measure Measure Measure

Set, measure, track. Data is the life blood of a scalable email program because you must track performance in of multiple indicators across multiple segments to detect any developing issue. TrueAccord created smart alerts that highlight engagement, spam issues, email features and other indicators across IPs, domains, receiver domains and several others. Together they provide us with a realistic view of how the program is doing as it scales, and where we may have opportunities for improvement.

It’s taken TrueAccord two years of trial and error and obsessing over data to scale to millions of emails sent each month. Our email scale will continue to grow as our consumer base and business grows, and we are confident that this strategy will support our growth.

How We Created Heartbeat

By on April 24th, 2018 in Data Science, Engineering and Data, Industry Insights, Machine Learning, Product and Technology
TrueAccord Blog

Sophie Benbenek, TrueAccord’s Head of Data Science, discusses the early days of building our machine learning based engine, Heartbeat, and how it has evolved since. Hear about our approach to machine learning, how we move from heuristics to statistical models, and other anecdotes from the early days of TrueAccord.

Designing A Pilot With TrueAccord

By on April 17th, 2018 in Industry Insights
TrueAccord Blog

TrueAccord beats traditional agency performance, and does so by using a machine learning based, digital first system. Since our system learns from individual consumer behavior, it requires specific pilot design to provide the right amount of data for the algorithms to tune themselves. In this episode, our Head of Client Services and Head of Data Science discuss the optimal pilot structure to make the best use of our platform.

Scaling TrueAccord’s Infrastructure

By on April 12th, 2018 in Data Science, Engineering and Data, Industry Insights, Machine Learning, Product and Technology
TrueAccord Blog

TrueAccord’s machine learning based system handles millions of consumer interactions a month and is growing fast. In this podcast, hear our Head of Engineering Mike Higuera talk about scaling challenges, prioritizing work on bugs vs. features, and other pressing topics he’s had to deal with while building our system.