Neo Financial
One of the largest, fastest growing, and most popular digital banks in Canada
Valuation > USD 1bn (unicorn status)
Website: https://www.neofinancial.com/
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"Neo is built on the belief that Canadians who put in the work deserve to get what they've earned. Whether that's a first credit card approval, a secured card that builds their credit score, or a high-interest savings account that actually rewards their discipline. Financial victory is built one decision at a time. TaranDM gives us the decisioning infrastructure to deliver that at scale, catching the signals legacy banks miss without the constraints that slow most companies down. That's the kind of partnership that moves the mission forward."
Andrew Chau, Co-founder, Neo Financial
"As a fast-growing fintech, we need tools and partners that are going to support us in our growth while allowing us to move at a fast pace. Taran has enabled us to implement a wholistic credit adjudication strategy to effectively gain new customers and give our team the tools to manage our existing portfolio."
Brent Bishop, Chief Credit Risk Officer
"We are now leveraging more data to enhance our decision-making process. With TaranDM, we can utilize 20× more data points in the adjudication process, and adding new ones has become incredibly easy and efficient. Previously, incorporating new data sources required several months, but now it's much quicker.
Our credit risk management has also seen significant advancements. We've transitioned from a broad adjudication path to having multiple, tailored paths for various segments. This allows us to be more targeted and adapt to unique situations with greater precision. Additionally, our ability to implement changes has greatly improved.
What once took weeks of discussion and planning can now be achieved within a day. We prepare, simulate, and deploy new experiments rapidly, collecting actual data and obtaining answers almost immediately. This has allowed us to iterate at an impressive speed."
Christian Rosati, Director of Risk Analytics and Credit Decisioning
Neo Financial’s adjudication goals
- Replace the existing credit decisioning infrastructure with an enterprise decision engine which allows a high level of flexibility to credit risk managers in designing and testing multiple adjudication strategies and processes simultaneously
- Allow for faster time-to-market when deploying new decisioning logic or its changes
- Eliminate dependency on engineering and developer teams and give credit risk managers the ability to have end-to-end ownership of their processes
Why has Neo Financial chosen TaranDM
- Platform-as-a-service” way of delivery – the decision engine runs at the client’s infrastructure (either cloud or on-prem), no sensitive data is shared with the vendor (customers’ personal details, etc.)
- Streamlined implementation & process migration, measured in weeks, and not in many months or years
- Modern technology stack – containerized, Python-based decision engine with microservices architecture
- Multiple out-of-the-box functionalities usually not available in other decision engines, such as Impact Report (simulation of decisioning logic’s changes against the status quo), batch decisioning, or Decision Optimizer
Implementation highlights
- TaranDM implemented and Neo Financial’s existing credit adjudication process migrated in less than 3 months
- Continuous knowledge transfer during the implementation & phase-in, along with TaranDM’s general customizability, has ensured that Neo Financial’s internal teams will not be overly dependent on us as the vendor going forward
- Higher flexibility when deploying new decisioning logic, for example:
- Credit product pricing now determined by the strategy and client historical profile/credit bureau record
- Specific strategies for selected partners which allow fine-tuning of approval rates/risk profiles and support of marketing actions and rollout plans
- Seamless A/B testing of strategies for various client segments
- Includes hundreds of pre-defined aggregations and it’s customizable further (client can create additional aggregations)
