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Financial institutions that want to get value from their transaction data often face a dilemma: invest heavily in building in-house technology or partner with a fintech company to buy a ready-made solution. Often referred to as the ‘build vs buy’ decision, this choice can determine a bank’s ability to meet customer expectations, drive innovation and remain competitive.
Our view is that partnering with a fintech like Bud always emerges as the smarter path forward. AI-driven and highly personalized banking experiences must be built on accurately enriched transaction data to succeed. We believe it’s not cost-effective or sensible to attempt to build these models and capabilities with an in-house technology team.
Speed can be really important when you need to respond to market demands or customer expectations and get ahead of the competition.
We help our clients to achieve this much-needed agility by providing transactional data analysis solutions with easy integration options or no-code dashboard and widget solutions.
Bringing new features and tools into financial institutions requires substantial investment in infrastructure, talent and development time. Partnering with a well-established fintech like Bud means banks can sidestep these high upfront costs to bring transactional data analysis into their business.
At Bud, you get access to ready-to-go transaction data enrichment solutions based on advanced technology that combines LLMs, AI models, and scalable and robust infrastructure. You also get the benefits of SaaS pricing: a known recurring cost and usage-based ‘pay as you go’ fees.
Not all financial data enrichment vendors share the same focus on understanding data and using the latest technology. Bud has worked in this field for a decade, using machine learning to build enrichment models many years before AI went mainstream.
At Bud, we’re proud of the market-leading enrichment which is at the core of all of our flagship products. We use sophisticated natural language processing and generative models for transaction data enrichment accuracy and granularity that is hard to beat, nevermind build yourself.
In the past, many institutions adopted a MCC-based approach (using merchant category codes, a market standard for card networks and other payment providers) or other static databases. Those were not fit-for-purpose. On the face of it, they might have seemed a cheap way to categorise transactions based on the business classification of the merchant. But the reality is that those codes weren’t developed with transaction enrichment in mind: they’re rarely updated, often inaccurate and don’t neatly map to consumer-facing categories.
More recently, it may have been tempting to experiment with more advanced solutions, including LLM foundation models. We explored the pitfalls of this approach in detail in this Finextra blog. TL;DR: the quality won’t be adequate, especially if you consider the fact that there’s more to enrichment than simple categorisation. Transactional data holds information about patterns and customer habits, and dealing with those requires the highest possible quality at every step of the process.
Another complexity to note is that building a transaction enrichment model is not a ‘one and done’ project. Our dedicated data scientists work hard to constantly refine our models, taking into account the likes of:
This is our ‘secret sauce’ and, put bluntly, banks simply won’t have the right ingredients.
Bud’s solutions are built with scalability in mind, enabling financial institutions to get immediate value from their transaction data without major infrastructure overhauls.
You can think of our products as modules or components.
With our customer money management solution Engage, for example, you can drop our white-labelled PFM widgets into your existing online or app-based digital banking experiences, adopting your business’ branding for a seamless look and feel.
Similarly, our customer data analytics platform, Drive, can take in data from a range of sources (such as transactional data or account data from banking platforms and cores, product outcomes and credit scores) and provide insights that can be consumed by the likes of Salesforce, Braze, MailChimp and other CRM or communication platforms.
All of these benefits also apply to institutions that have already built an enrichment platform. The granularity of Bud’s approach means it’s possible to map it back to any existing taxonomies, including even having the model to return MCC-aligned results. This, of course, should always be a temporary solution since MCC is not fully fit-for-purpose, but, as a way of giving a boost to an existing infrastructure, mapping is a feasible first step.
An additional benefit of using Bud’s enrichment engine is its ability to learn. This means that it can instantly leverage any already processed transactions and use them as one of the training inputs. No work is lost and migration to a new solution has a guarantee of improvement in quality.
Building a transaction data enrichment or analytics solution from the ground up is a long and resource-intensive process. You might struggle to allocate sufficient time and personnel to these projects, particularly when balancing them with day-to-day operations and other priorities.
The industry’s demand for skilled professionals far exceeds supply.
To build an in-house model for transactional data analysis, you would need dedicated staff, including data, ML, engineering and QA roles, as well as data labellers. Finding and retaining experts with these specialized skills is not for the faint-hearted.
Technology moves fast, and in-house systems can quickly become outdated without ongoing innovation and maintenance. This is particularly true when it comes to achieving and maintaining highly granular and accurate transaction categorisation and merchant identification.
While the advantages of fintech partnerships for financial data enrichment are clear, some remain hesitant.
Here are the three concerns we hear most often at Bud, and how we provide reassurance:
Bud has passed due diligence with some of the largest FIs in the world. They trust us with their transactional data. Our approach to security is not just limited to SOC 2 and ISO 27001 certification but is evident through the security features we offer such as our bring-your-own-key (BYOK) technology.
We often advise our clients on how to run a transaction data enrichment benchmarking exercise because we’re confident our market-leading categorization will come out on top.
Our streamlined process ensures a quick and smooth go-live experience, and we have a proven track record of working with companies of all sizes and maturity levels.
AI-driven experiences and hyper-personalized banking are becoming the norm, driven by consumers’ growing expectations for seamless, intuitive digital banking.
These expectations can only be met with high-quality, enriched transaction data. As the saying goes: “Rubbish in, means rubbish out…”.
Collaboration between financial institutions and fintechs will continue to grow as firms recognise that building sophisticated transaction enrichment models in-house is both resource-intensive and unsustainable in the long run.
In the ‘build vs buy’ debate, partnering with fintechs often offers banks a faster, more cost-effective and less risky path to innovation.
In the translation data enrichment space, AI models require constant iteration and ongoing refinement to remain accurate and effective. Bud, with our dedicated teams and years of expertise, provides a scalable solution that ensures financial institutions stay ahead of the curve without the burden of maintaining complex data enrichment systems.
By working with Bud, banks can build their capabilities, better serve their customers and secure a competitive edge.
The smartest way to build the intelligent financial institution of the future is to buy a transaction API.
Building an in-house solution requires significant time and talent, as well as constant updates to maintain accuracy.
Banks and fintechs often underestimate the upfront and ongoing resources needed to build and maintain a transaction data enrichment service.
Buying transaction data enrichment (instead of attempting to build it) means faster deployment. Businesses can focus on innovation rather than infrastructure.
Bud’s ready-to-go transaction data enrichment solutions are built with advanced technology that combines LLMs, AI models, and scalable and robust infrastructure for market-leading accuracy.
Many financial institutions start by building a transaction data enrichment solution but later turn to a specialist for efficiency, accuracy and cost-effectiveness.
Contact us for a no-obligation demo of our transaction enrichment and analytics capabilities.
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