Fintech Solutions for Banking & Financial: What Should Change Before the Next Technology Investment?

Fintech Solutions for Banking & Financial: What Should Change Before the Next Technology Investment?

Most banks have no shortage of fintech solutions, only a blurry view of what stops them from working. A sound digital transformation strategy starts by fixing that before the next purchase.

Why the Last Technology Investment Often Falls Short

Many banks have bought a mobile app, a lending platform, or a payments tool and still see the same slow processes behind the screen. The new tool works, but the work around it has not changed.

A 2024 survey from the core banking vendor 10x Banking found that 55% of banks see their existing core systems, the main platforms that hold accounts and transactions, as the biggest obstacle to their digital goals.

The same research reported that 53% of banks running legacy cores struggle to scale because of data silos, meaning information trapped in separate systems, and production bottlenecks. Because the vendor sells core platforms, read the figures as a signal, not a verdict.

The pattern is familiar. A tool is chosen for its features, installed on top of old foundations, and then blamed when the results are modest.

What usually sits underneath the problem

• Customer data held in several systems that do not match.
• Processes that depend on manual checks, spreadsheets, or email approvals.
• Core platforms that cannot share data quickly with newer tools.
• No single person who is accountable for the result.

Start With the Problem, Not the Product

A digital transformation strategy is a plan for changing how the bank works, not a list of tools to buy. It begins with one problem that customers or staff feel every day.

Good examples are loan approvals that take days, onboarding that loses applicants halfway, or month end reconciliation, the matching of records between systems, that ties up a full team. Each one can be measured before and after the change.

Write the target in plain numbers, such as the time to approve a loan or the share of applicants who finish onboarding. If nobody can state today's figure, measuring it is the first task.

Larger changes to core platforms need their own plan, and a phased approach to legacy modernization keeps daily operations running while the work happens.

Fix the Data Foundation First

Every fintech tool depends on data that is complete, consistent, and easy to reach. If the same customer appears with three spellings in three systems, no analytics or automation layer will repair that.

Start by listing the fields that matter for your chosen problem, such as customer identity, account status, and transaction history. Then note where each field lives and who is responsible for it.

Payments show why structure matters. The coexistence period for older MT messages ended on 22 November 2025, and Swift now requires ISO 20022 for cross border payment instructions.

That standard carries richer, more structured data than the old format did. Banks that tidy their data now can put that detail to work in reconciliation and compliance checks.

Ownership helps here. Give each key field a named data owner, so that when two systems disagree there is someone who can decide which one is right.

Data work is slow and rarely exciting, but it is the cheapest place to find problems. A tool bought before this step inherits every gap.

Connect Systems Before You Replace Them

Replacing a core platform is expensive, risky, and slow, so it should not be the default answer. In many cases the first job is simply getting existing systems to share data with each other and with new tools.

This is where APIs help. An application programming interface lets one system request data or trigger an action in another without staff retyping anything.

A bank can wrap an older core system with a clean API layer and let new tools use that layer. The core keeps running while the experience around it improves.

Cost is easier to judge this way too. Connecting two systems has a clear scope and a short timeline, while a core replacement often runs for years and touches every product line.

Sometimes this is not enough. If the core cannot return data quickly or cannot scale, replacement may be the honest answer, but it should come after the need has been proven.

What good connection work looks like

• One agreed data format between systems, with a written record of any change.
• Clear rules on who can read or change each piece of data.
• Monitoring that shows when a connection fails, before a customer notices.
• A fallback plan for the day a connected system goes offline.

A Hypothetical Example

This is a hypothetical case, not a real customer story. A mid sized lender buys a digital loan application tool, but staff still key each approved application into the core system by hand.

Approval times barely move. The delay was never the form; it was the manual retyping and two systems that disagreed about customer records.

A better order would be to match customer records first, connect the tool to the core through an API, and then measure approval time again. The same tool, placed after those steps, would be judged fairly.

Decide Who Owns the Result

Technology projects in banks often sit between IT, operations, risk, and the business line. When all four share responsibility, none of them is accountable.

Name one owner for the outcome and give that person authority over scope and timing. Others advise, but one person decides.

Bring compliance and risk teams in at the design stage, not at sign off. Their questions about data handling and audit trails are far cheaper to answer before a build than after it.

Frontline staff matter just as much. Branch teams and service agents know where customers get stuck, and they will tell you quickly if a new flow adds work.

Build Security and Compliance In From the Start

Every new connection to a bank's data is a new place where something can go wrong. Security reviews should cover each tool, each connection, and each partner that touches customer data.

Rules on data protection, payments, and reporting differ by country, so check the ones that apply where you operate. Ask your compliance team which duties stay with the bank when a vendor handles part of a process.

Keep a simple register of every fintech tool in use, what data it touches, and who approved it. It makes audits calmer and exits easier.

A Practical Sequence Before the Next Investment

1. Name the problem and the number. Pick one process, record today's figure, and set a target the team agrees on.
2. Map the process as it really runs. Walk through each step with the staff who do the work, including their workarounds.
3. Audit the data. List the fields involved, where they live, and which copy is correct.
4. Check the connections. Note which systems must share data and whether they can do so today.
5. Run a small pilot. Test one product line or one branch with real users for a fixed period.
6. Review, then scale. Compare results with the starting number before widening the rollout.

At Hubops, we connect older systems with newer platforms through integration work, so we treat the fourth step as a design task, not a quick fix.

Common Mistakes to Avoid

Most stalled projects repeat a small set of errors, and each one is avoidable with a little planning.

• Choosing a product from a polished demo before the problem is clearly defined.
• Treating a pilot as a launch and skipping the measurement that justifies scaling.
• Leaving compliance and risk teams out until the final sign off.
• Ignoring the cost of support, training, and upgrades after launch.
• Letting each department buy its own tool, which creates new silos.

Questions to Ask Any Fintech Vendor

A demo shows the best case. These questions show the everyday case.

• How does your product connect to our core system, and who builds that connection?
• Where is our data stored, and who owns it if we leave?
• Which regulatory requirements does the product help us meet, and which stay with us?
• What does a failed update or an outage look like for our customers?
• What happens to our data and workflows if we end the contract?

How to Tell Whether the Investment Worked

Judge the result against the number you wrote down at the start. If approval time, error rate, or cost per transaction has not moved, the tool has not yet earned its place.

Look at staff behavior as well. If employees keep a spreadsheet on the side, the new system is missing something they need.

Use the same measure and time period each round, or the comparison means little.

Review after the first quarter and again after the second. Early numbers show whether the setup works, and later numbers show whether people adopt it.

Final Thoughts

The next technology investment will work best when the problem, the data, and the connections are ready for it. Most of what needs to change sits around the tool, not inside it.

Start small, measure honestly, and let each result decide the next step. If it helps to talk through your own sequence, our team is happy to have that conversation.