How Financial Firms Can Choose the Right AI Provider
George Ralph of RFA outlines the key considerations financial firms should weigh when selecting an AI provider, from security and compliance to scalability, transparency, and vendor risk.
At this point, it’s no longer news that AI is driving one of the biggest shifts in technology we’ve seen in decades. Every industry, including the financial sector, is evolving to adapt to the new possibilities brought by AI. With major players like Microsoft, Google, and OpenAI developing foundational models, competition is fierce, and we’re seeing new improvements almost every week.
We also have hundreds of other companies, such as Perplexity and Cursor, building impressive AI products using foundational models from these big players. With so many AI providers available, it can sometimes be challenging to determine which one best fits your needs. For financial firms in particular, the choice of provider can have major implications for operations, security, and privacy.
In today’s article, my goal is to share the key factors you must carefully consider before choosing an AI provider or product for your firm’s operations. So, without wasting any more time, let’s dive in!
What to Consider When Choosing an AI Provider or Product
Let’s explore some of the key factors you must consider before choosing an AI product:
Understand Your Firm’s AI Needs
Before choosing a provider, your firm must clearly define what it wants to achieve with AI. Are you looking to improve risk assessment, summarise complex documents, automate client onboarding, detect fraud, or generate portfolio insights? A clear understanding of your goals will help narrow down providers that specialise in your use cases.
It’s also important to remember that your firm may have multiple tasks for which it plans to use AI, so make sure to list all of them. Next, understand your data requirements such as where your data resides, its quality, and how it integrates with your existing systems. Some AI models perform better with specific data types, so ensure your provider can work with your infrastructure, whether cloud-based or on-premises.
Vendor Lock-In
Since we are still in the early days of AI, many companies may try to make it difficult to switch to another AI product once you start using theirs. Therefore, it’s crucial to assess the risk of vendor lock-in before choosing a provider. Some vendors use proprietary models or closed ecosystems that limit flexibility and make it hard to migrate your data later.
Opt for platforms that support data portability and API-based integrations so your firm maintains control and flexibility if you ever decide to change providers. The AI solution you choose should allow you to export all your data easily, ensuring you can move to another platform if it offers better value than your current one.
Prioritise Security and Compliance
If you’re in the finance sector, security and regulatory compliance are two things you must never ignore when choosing a product to integrate into your operations. Ensure your AI provider meets recognised industry standards such as ISO 27001, SOC 2, and GDPR. These certifications indicate that the provider follows best practices for data protection and risk management.
Ask specific questions about how your data will be stored, processed, and anonymised. For example: Is your data encrypted at rest and in transit? Who has access to it? Can you audit their data-handling practices?
It is also crucial to know where your data is stored. For instance, if you choose a product like DeepSeek, your data will likely be stored in China, and regulations in some regions may not allow that. Also, don’t rely only on what the company tells you - dig deeper, as companies may not always reveal full details about data residency.
Online vs Offline Models
Since financial firms handle a lot of sensitive data, it’s important not to trust just any vendor with it. Assess whether your provider offers an offline option. Many major AI providers now have capable models that can run offline. While offline models may not always match the full capabilities of cloud-based ones, they are ideal when your use case demands maximum privacy and data control.
Offline models such as Llama 3, Mistral, GPT4All, Vicuna, and Phi-3 are typically open source. They also require significantly powerful local hardware to run efficiently. So, take time to review their hardware requirements carefully before deciding which one best fits your firm’s setup and security needs.
Evaluate Model Transparency and Explainability
When you choose to use AI in your operations, you must ensure that the outcomes of these systems can be explained whenever required. In finance, regulators and clients expect transparency. If your firm relies on an AI-driven decision such as loan approvals or fraud detection, you must be able to justify how that decision was made.
For instance, if your AI system denies someone a loan or assigns a high interest rate, you must be in a position to clearly explain why the AI made that decision. Also, keep in mind that users do not even know you are using AI to make some of these decisions. Having the ability to clearly explain the reasoning behind an AI’s actions is crucial to maintain transparency with all your firm’s stakeholders.
Transparency also helps with compliance, builds trust, and allows your teams to validate and fine-tune models when necessary.
Check Scalability and Integration
Your firm’s use of AI today may not be the same in five or ten years - it will likely grow. Therefore, when adopting AI tools, ensure they have the capacity to scale with your firm’s needs.
Your team should evaluate how easily your AI provider’s tools can scale as your data volume, user base, or analytical needs increase. A scalable AI platform ensures consistent performance even as your operations expand.
In addition to scalability, integration is equally vital. The provider’s technology should work seamlessly with your existing systems such as CRM platforms, trading systems, or risk management tools. You’ll also enjoy a smoother experience if you use AI tools from the same ecosystem as your other products. For example, if your firm already uses Microsoft solutions, adopting AI tools like Microsoft Copilot 365 will make your workflow more seamless and efficient.
Assess Support, Training, and Customisation
AI systems, especially foundational models, often require fine-tuning to fit unique business workflows. Check whether your provider offers customisation options to align the system with your firm’s specific goals.
Strong technical support and training are also essential. Look for providers that offer onboarding programs, responsive customer service, and detailed documentation. A vendor that helps your team understand and use the system effectively can significantly improve your return on investment.
Ideally, your AI provider should offer a trial period so you can test whether their product and services meet your expectations. During this period, evaluate their support responsiveness, documentation quality, and how well they address any issues you encounter while using their tools.
Compare Pricing Models
No matter how advanced an AI product is, it still needs to fit within your firm’s budget. This doesn’t mean choosing the cheapest option - that might actually cost you more in the long run due to poor performance or limited scalability. Instead, compare prices among products that offer a similar set of features and reliability.
Beyond the price tag, also examine the pricing model. Some vendors provide flexible plans like pay-as-you-go or subscription-based options, while others use traditional licensing. Be cautious of hidden costs, such as extra charges for advanced features, data migration, or ongoing maintenance.
Transparent and predictable pricing helps your firm make informed decisions and plan effectively for the long term.
Key Takeaway
Taking time to assess all these key factors will be worth it, as it will help you choose a product that solves your firm’s problems without violating regulations, and at the best possible price. Yes, it does take time to think through, and you may need to try out different products before finding the one that best fits your firm. That’s why choosing providers that offer free trials is highly recommended.
At the end of the day, the choice of which AI solution to use largely depends on what’s happening in your firm - your values, use cases, and compliance needs. So, the time it takes to make this decision is truly worth it.
For firms that may not have the internal expertise to make the right choice or to implement AI in their operations, RFA is here to help. Our experienced AI team has supported hundreds of firms in safely and securely adopting AI, without breaking the bank or violating regulations.
Future-Ready IT for Financial Leaders.
RFA delivers advanced cybersecurity and IT solutions tailored to the financial sector's needs. With a focus on white glove service, RFA ensures that their technology supports their clients' complex demands, enhancing security and business operations.
