Stop Chasing Bank Statements: The Open Banking Efficiency Case for Mortgage Brokers

Ask any mortgage broker where their time goes, and the answer is rarely "advising clients." More often, it is chasing documents. Requesting bank statements. Waiting for the client to locate three months of payslips. Re-requesting incomplete PDFs. Manually cross-referencing income figures against self-assessment returns.

This administrative drag has a measurable cost: in hours per case, cases per adviser and ultimately the number of clients a firm can serve in a year. In 2025, the average time from mortgage application to formal offer across UK lenders surveyed by YesCanDo Money was 12.8 days, the first year-on-year slowdown since 2022. The culprit was a surge in applications combined with lenders struggling to scale manual processing fast enough.

Open banking changes the equation. And in 2026, with the FCA having published its Open Finance Roadmap in April and mortgage lending named as a priority use case, this technology is moving from early-adopter territory to mainstream expectation.

The numbers behind the bottleneck

Manual bank statement collection is not just inconvenient; it is expensive. Consider what happens when a broker has to request, receive, validate and interpret six months of bank statements across two or more applicants. There are delays from clients. Statements arrive in inconsistent formats. Transactions require explanation. Non-standard income — freelancers, contractors, company directors, those with multiple income streams — requires additional corroboration.

With an estimated 5.3 million people in the UK in some form of self-employment or non-standard work, this is not an edge case. It is an increasingly common one. And with Making Tax Digital for Income Tax Self Assessment (MTD ITSA) now live, the volume of self-employed applicants presenting more complex financial pictures is only growing.

The downstream effect on the wider market was visible in 2025: some of the UK's largest lenders were working through processing queues for weeks following each Bank of England base rate change. Brokers found themselves chasing lenders for updates on cases that should have been straightforward.

The 2026 data tells a different story for firms that have invested in automation. YesCanDo Money reported in May 2026 that the industry average is already recovering, back below 11 days. But the real gap is widening between firms using automated income verification and those that have not. Top performers are now issuing offers in under eight days on average.

Application to offer: 12.8 days (UK average, 2025) vs. under 8 days for lenders with automated income verification (May 2026). Statement retrieval: 4 days → minutes with open banking API integration (SBS, November 2025).

What actually changes with open banking

Open banking gives brokers and lenders secure, real-time access to an applicant's bank transaction data, categorised, verified and delivered through an API connection in minutes. The alternative — four days of back-and-forth to gather manual statements — is effectively eliminated.

In November 2025, SBS launched Core MSS7, a new release of its Mortgage and Savings Suite specifically designed to bring open banking capabilities to UK building societies and banks. The platform, which powers one in five UK mortgages through institutions including Hinckley & Rugby Building Society, Newbury Building Society, Scottish Building Society, Swansea Building Society, and The Co-operative Bank, cited a reduction of over 50% in application-to-offer processing time following open banking integration.

Leeds Building Society and L&C Mortgages ran a joint pilot demonstrating that open banking integration accelerates the mortgage process and reduces friction for brokers submitting cases. Broker feedback consistently cited fewer document requests and faster case progression as the primary benefits.

For the broker, this means less time in document limbo and more time in front of clients. A case that previously required multiple email chains and manual interpretation can now be assessed within the same day the client gives consent through a secure, one-time authorisation.

"Top-performing lenders are now issuing mortgage offers in under eight days. The differentiator, consistently, is automated income verification powered by open banking."

The client retention connection

Speed and reduced friction are not just operational wins; they translate directly into client experience. Clients who go through a smooth, fast process refer their peers. Clients who spend three weeks chasing documents do not.

Research on broker practice management consistently shows that clients rate responsiveness and process clarity as the primary drivers of satisfaction and repeat business. A broker who can say "we will have your affordability picture ready tomorrow morning" is a broker who wins referrals at renewal time.

The freed-up time matters too. When document chasing drops from hours to minutes per case, advisers can either handle more cases without hiring additional administrative staff, or redirect that capacity into proactive remortgage outreach, reaching clients ahead of their fixed-rate expiry rather than waiting for them to call.

In a market where the acquisition cost of a new mortgage client consistently outweighs the cost of retaining an existing one, the efficiency gains from open banking are not just operational. They are a client loyalty investment.

The regulatory tailwind

The commercial case for open banking in mortgage broking is now reinforced by an explicit regulatory direction of travel. On 14 April 2026, the FCA published its Open Finance Roadmap, a formal strategy for extending open banking principles across a wider range of financial products, including mortgages, by 2030. Mortgages are named as a priority use case.

The roadmap specifically calls out open finance-powered tools that combine current account data with market interest rate data to give consumers and advisers personalised, real-time affordability insights. A Policy Sprint on mortgages is planned for Q2 2026, with a regulatory discussion paper to follow in Q4.

Consumer Duty reinforces this further. The FCA has shifted the standard for lenders from "are our policies compliant?" to "does our process inadvertently exclude customers who could be served responsibly?" That is a meaningful distinction, and one that real-time, categorised transaction data is uniquely positioned to answer, in a way that income multiples and six-month-old payslips never could.

This is not a future regulatory risk. It is the direction the market is already moving. Firms that build open banking into their workflows now will be ahead of firms that treat it as a future IT project.

What brokers should look for in an integration

Not all open banking integrations are equal, and for brokers the implementation details matter as much as the headline technology.

• No large IT project. An API-first design should sit alongside existing CRM and sourcing tools, not require replacing them. If a vendor quotes a 12-month implementation timeline, keep looking.
• Categorised output, not raw data. Raw transaction feeds are not useful. What brokers need is data that has already been interpreted: income sources identified, recurring commitments flagged, anomalies highlighted.
• Lender-ready report format. The output should be something an underwriter can act on directly, without asking the broker to re-interpret the data in a separate document.
• Transparent methodology. With Consumer Duty expectations rising, brokers need to be able to explain to clients, and if necessary to the FCA, how an affordability assessment was reached. A black-box score does not meet that standard.

Working with Moxim

Moxim is a UK SaaS affordability layer built specifically for mortgage brokers and lenders that want better data without a major technology project. Moxim connects to your existing workflow via API, delivers categorised transaction analysis and affordability scoring, and outputs lender-ready reports that underwriters can act on immediately.

We built Moxim for firms of all sizes, with particular focus on those that do not have a technology department to manage complex integrations. Our methodology is transparent, our deployment is measured in weeks not months, and our output is designed to meet the data quality expectations that Consumer Duty and the FCA's Open Finance Roadmap are moving the market towards.

We are currently onboarding our first lender and broker partners and would be glad to show you how it works in practice. Moxim collates a client's income, spending, credit, identity and property data into a clean affordability assessment the moment they share access, removing manual data entry and document chasing from case prep.

Join the broker pilot →

What a broker can do with the time back

Take a firm with three advisers, each handling around 15 cases a month. If document chasing currently consumes an average of three hours per case, that is roughly 135 hours a month across the team spent on statement requests, chasing missing pages and manually cross-checking figures against declared income. This is an illustrative model built from the processing-time data already cited in this piece, not a specific case study, but the order of magnitude is consistent with what firms report.

Redirecting even half of that time changes what a firm can plausibly commit to. It is the difference between telling a client "we will get back to you once we have chased your statements" and telling them the affordability picture will be ready the same day, without adding headcount to do it. For a broker principal weighing whether to hire another case handler or invest in better data tooling, that is a real capacity decision, not a marginal one.

The same maths scales past a three-adviser firm. A network of 20 self-employed advisers each running a similar caseload is sitting on well over 2,000 hours a month of admin time that a categorised, API-delivered data feed can largely remove, freeing advisers to spend that time on advice, on client acquisition, or simply on taking on more cases without the proportional increase in support staff that manual processing usually demands.