Transforming Credit Management with Credisense and MongoDB
Credit Management is a grind -- clunky, time consuming and laden with risk.
It requires millions of dollars to capture consumer attention and nurture through the sales
cycle. And then comes the arduous credit assessment, throwing a wrench into the
promise of a seamless digital customer experience. In fact, up to 90% of bank new
customer applications drop out due to slow onboarding 1.
Even once a deal closes, there is still plenty of work to do. The next hurdle is invoice collections, with default and delinquency rates averaging anywhere between 0.2-54.5% internationally 2.
In today’s digitally-driven market, consumers are demanding quicker turnaround times
and instant approvals. This makes simplifying and streamlining the entire credit management process more critical than ever.
As MongoDB’s OEM business continues to rapidly expand, it’s a personal priority
to work with organizations who are solving serious market needs with the most
innovative technology. Credisense, our newest OEM partner, and their MongoDB-
powered, full end-to-end origination and credit decisioning solution is a phenomenal
example of this.
They’re already making splashes worldwide. For example: CTOS Data Systems
(Malaysia’s largest credit reporting agency) is enabling banks, utilities, non-bank credit
issuers, fintechs and lenders in the P2P lending space to make real time credit
decisions using the Credisense platform, enabling things like instant loan approvals for
credit cards and auto loans!
I had the opportunity to discuss the Credisense platform and the data technology behind it with Richard Brooks, Co-founder and Director.
Tell us a bit about yourself and the genesis of the company?
Our three co-founders have different, but complementary backgrounds. I have worked for bureau
and data companies my entire career and been involved in the automation side quite
extensively. Our second co-founder and CEO, Sean Hywood, is a software expert having built up several software companies over
his career focusing on low-code technologies. We combined our knowledge with the
technical expertise of our third co-founder and CTO, Waylon Turney-Mizen, with the
vision of providing enterprise grade functionality to organizations of all sizes. The aim is
to allow all businesses to make smarter decisions, faster.
For anyone that isn’t familiar with Credisense yet, could you describe why you set
out to build this and the problem it’s solving?
Credit is a highly regulated, complex, often manual and costly process. McKinsey 3
rightly points out there are five key pressures on credit providers currently:
Changing customer expectations, specifically digital and the customer experience
Tighter regulatory controls such as AML/CFT and GDPR
Data management, increasing reliance on clean data for analysis and decisions
Market disruptor such as P2P lenders and digital banks
Cost pressures driving down returns
There are some sobering stats that show how important these are, such as over $200 billion
dollars 4 of regulatory fines in the US alone since the GFC, to the fact that traditional
lenders have lost over 30 percent of personal loan market share 5 to agile financial technology
companies. All these add up to some serious issue for business, some that even threaten their very existence. Our aim when creating Credisense was to tackle these issues, both by
assisting traditional corporates to embrace this digital strategy, to providing this same
technology and expertise to smaller businesses so they can compete and level the
playing field.
How would you describe the platform and the unique advantages that Credisense gives its customers?
Our platform is born in the cloud and offers a “no-code” build capability allowing
organizations to build out the functionality internally and grow the solution with their
business. We have a unique graphical interface, and this coupled with the “no-code”
technology allows business people -- not IT -- to build, own and manage the system.
The platform itself revolves around the decision and scoring engine which powers the
advanced assessment and risk decisions for organizations.
Our MongoDB backend means we can confidently scale to handle millions of credit applications and still support real-time workflow and decision making in seconds.
How did you land on MongoDB to help you solve these challenges?
We needed a database to support a minimum of 100,000 transaction a day across a
cloud platform. There are only a handful of NoSQL databases that can support the level
of transaction with the ability to further scale if required. MongoDB ticked all the boxes. Add that to MongoDB’s great documentation security, tooling, support and APIs, and it made MongoDB the right choice for our development teams.
What advice would you give someone who is considering using MongoDB for their next project?
MongoDB offered us extensibility to be on-premises, which is something other cloud database platforms would not offer. It made sense to go with a database platform that offered both so that we could in turn offer this to our customers that require data to be held within their own environments for security reasons. Also, reach out and talk to MongoDB early in your process. The support they give you up front will help ensure you’re making the best decisions.
How are you securing MongoDB?
We utilize MongoDB Atlas for our Continuous Integration and Testing environment and will have a managed service offering. This is secured with an IP whitelist, secure password and SSL connection which was easy with Atlas and Atlas Professional.
We also have a customer-managed deployment secured out of the box behind a VPN that connects the app server to the MongoDB server. It also utilizes a strong username/password combination with minimum length and character requirements.
Through our OEM arrangement with MongoDB, we package MongoDB Enterprise as part of our product to ensure our customers have highly secure and enterprise-grade solutions.
Where have you deployed MongoDB? On-premises, in the cloud, via MongoDB
Atlas? What tools are you using to deploy, monitor MongoDB?
All! The requirement for extensibility across platforms without any changes to the code was one of the key reasons for MongoDB selection.
MongoDB Atlas removes operational overhead and mitigates risk through automating many of the manual processes (configuring operating system, upgrades, backups and restores). This means we can focus on ensuring our customers have the robust platform they need to provide instant loan approvals.
We also have a production environment on-premises. Soon, we will introduce the use of MongoDB Cloud Manager for monitoring and alerts of on-premises production environments. With over 100 metrics and proactive alerting, we’ll be able to catch issues before they arise.
References:
https://thefinancialbrand.com/66143/7-steps-to-improved-customer-onboarding/
https://data.worldbank.org/indicator/FB.AST.NPER.ZS?year_high_desc=true
https://www.mckinsey.com/business-functions/risk/our-insights/the-value-in-digitally-transforming-credit-risk-management
https://www.mckinsey.com/business-functions/risk/our-insights/the-value-in-digitally-transforming-credit-risk-management
https://qz.com/1334899/personal-loans-are-surging-in-the-us-fueled-by-fintech-startups/
December 13, 2018Applied