BLU365
We will be the place for indebted customers (in Brazil - 60 million people) to consult and resolve their financial needs. As for companies, we will be the preferred partner for intelligent solutions based on customer behavior and A.I.
BLU365 is a debt negotiation platform that combines very unique competencies to generate value to both creditors and debtors. By combining our expertise in data science, CRM and performance-driven marketing, we help creditors find their customers in the digital channels. We use predictive statistical models heavily and help creditors enhance returns in more than 15%. On the other hand, we make available to debtors several free services which educate and help them understand what are the best alternatives for debt negotiation and financial organization.
We've more than 60M people in debt in Brazil, and when they need some help, they don't find it properly. The traditional collection approach is very ineffective and serves badly both creditors and debtors (low quality, not customer oriented, expensive, low margins, poor analytics). Although they desperately want to pay off their debts/clear their names, they're usually unemployed or had other issues, and had to prioritize other bills that cover their basic needs (electricity, rent, food). Since they're in a very weak and vulnerable financial situation, their voices aren't heard by the banks and institutions anymore, as they are no longer people of interest. This exclusion from the economy market is not only extremely detrimental to their finances but also to their self-esteem. Our main goal is to disrupt the market and change this scenario, by giving customers the option of a digital, humanized and private debt negotiation. This choice empowers people as it sets a new example of how they should expect to be treated. And since we're B2B2C, we interact daily with Enterprises (Banks, Retail, Utilities), so with proof that our model works, we end up influencing them to change their approach towards these customers as well.
We focus on customer engagement through digital channels. We have more than 22 million customers apt to negotiate in our platform. Our main focus is the integration with more lenders in order to expand our customer database. Only in Brazil we have more than 60 million people in delinquency. It represents more than 40% of the economically active population. That is a huge opportunity only in Brazil, with more than USD 60 billion in past due debt outstanding, considering only individual banking debt. It is more than a USD 3 billion in revenues to be seized. In the future, we also plan on expanding to other countries which also hold a huge debt burden and (sadly) delinquency, such as Latam, US and Canada.
- Create or advance equitable and inclusive economic growth
- Growth
- New application of an existing technology
We are the only platform that combines in one single place data science, digital channels (eg LP, messenger bot, WhatsApp bot), CRM and performance-driven marketing competencies. We hold the biggest customer database (c. 20mm) and their respective behavior-related data-points, which allow our algorithms to perform best and add more value for both creditors and debtors. Our team is also very differentiated, combining an industry solid background with digital business best practices experience.
Other organizations don't have data science strategies and use traditional debt collection approaches, that are not only inefficient, but also fear-based and harmful to the relationship between creditors and debtors.
Through technology, we are able to escalate and optimize the integration process of the B2B databases, gather behavioral data about clients to identify the right moment, channel and message to impact them with, have multiple support channels to better serve our clients (Facebook Messenger, WhatsApp, SMS, email), and offer an easy way to generate deals, liquidate debts and clear their names.
The main components in our system architecture are: Heavy use of Cloud services. Front-End/Back-end: Serverless Architecture, Lambda Functions, Docker containers/ECS, API Gateway, Message Queues, MongoDB, MySQL/Aurora, Redis, ElasticSearch, Python, NodeJS, PHP. Big Data: Presto/Athena, Hadoop/Spark/EMR, Apache Nifi, Analytics/Predictive Modeling, Python, NodeJS, Java, Groovy.
Those technology is already in production and have been used over the last couple of years to feed our data-lake with near 01 petabyte of structured and unstructured data which we intend to use to develop/train our AI and machine learning algorithms to build the next level of product and services in our company pushing the edge of industry to a new level.
- Brazil
- Brazil
We've had around 1.5 million generated deals, which represent the people we helped get out of debt in a friendly, humanized and private manner.
Although it's harder to measure the direct impact of this action, we also have a blog with financial organization tips, with around 1.5 thousand daily views. Besides that, we've carried out a few surveys to identify how else we could help our clients, which led us to develop new services and multiple partnerships with other companies that offer great solutions, such as non-bureaucratic loans with low interest rates, alternative opportunities to earn extra income, and others.
BLU will accelerate growth via robust and personalized offerings and gains of efficiency. For the next 24 months, our roadmap is focused on 4 strategic drivers: (1) New customers growth (2) Increased customers' share-of-wallet (3) Gains of efficiency (4) Attract and engage with new users.
During the next 12 months, we will capture further efficiency and growth opportunities, whilst unblocking accelerated growth afterwards: (1) Strong growth in platform access and generated deals (2) Growth of 2.6X in revenues.
As we progress further in leveraging on customer behavior patterns that only BLU holds (22m people and respective behavior patterns organized and available) we have been demanded by companies to be compliant with the new customer data protection law. Customer data protection in an important part of our culture and we have robust policies and processes to manage it. Additionally we will review all the policies in order to warranty we are compliant with the new law.
In order to comply with data protection laws, we've made data protection in an important part of our culture and we have robust policies and processes to manage it. Additionally we will review all the policies in order to warranty we are compliant with the new law.
- For-Profit
10
Alexandre Lara (Founder and CEO): computing engineer, with more than 20 years of experience in the banking industry, working in risk management, credit, debt collections, product and innovation
Paulo de Tarso (Founder and Head of Analytics): master in statistics, also have more than 20 years of experience in the banking industry, having also worked as C-Level in Credit, Collection, Risk and CRM.
Both BLU co-founders were also partners in a previous startup. We developed an analytics-as-a-service business focused on providing financial services companies with tools to rapidly capture value from the immense data-load that debt collections operations retain. After 1 yr of relative success with paying customers and positive cash flows, we did not sort out how to scale the business further as it became service-oriented / people labour intensive. However, it served as the initial data-driven framework from where we started to develop BLU 5 years ago.
Our HQ city is Sao Paulo. The company is organized in 6 different areas: Analytics (1.5 FTE) Marketing (4 FTE) IT & Data (9 FTE) Performance & Operations (12 FTE) Sales (1 FTE) Business Dev. (0.5 FTE). We have an unique team in the collection industry that believes it's possible to help indebted customers to organize their financial live.
Our business model is B2B2C. -B2B: we interact with Enterprises (Banks, Retail, Utilities, Credit Card, etc), and just launched a SME platform in the end of 2018. -B2C: we focus on people in a vulnerable financial situation, that have debts in the market.Our revenue generation model varies according to each partnership. Today we have 2 models: success fee and lead generation.
-Success fee: we receive a variable commission over the paid deals (varies on the range of debt arrears)
Lead generation: we receive a fixed commission per generated lead
If selected as a Solver, we would use the prize funding to hire data engineers, data scientists and devops to work on own algorithms to automate decisions in debt collection business based on behavioral data collected with our customers and partners with the goal to help debtors to identify the best (more sustainable) collection plan for them considering their current financial situation and prevent them to default again.
We would also invest to improve our security efforts to identify and prevent fraud and personal data protection.
Founder and CEO