MGA software: the complete buyer's guide for 2026

The best MGA software exists to prevent a scene that plays out in insurance boardrooms more often than anyone likes to admit. A managing general agent spots a gap in the market. The numbers are good, the capacity is there and the window is maybe six months wide before a competitor works out the same trade. Then someone from IT explains that launching the product will take eighteen months and a seven-figure budget, because the platform underneath the business was built for a different decade.

That is the whole problem MGA software has to solve. The opportunity is real and the technology cannot move fast enough to catch it.

KPMG research puts a number on how widespread this is. Three quarters of insurance leaders are trying to cut operational costs by 10% before 2030, and only around a quarter expect to manage it.³ The thing standing in the way is rarely the market or the regulator. It is the software. Matthew Smith, KPMG's Global Lead for Insurance Strategy and Transformation, summed it up: big technology budgets do not necessarily lead to big cost improvements.³

This guide covers what separates the best MGA software from the legacy systems quietly throttling growth across the sector: the UK market context, the operating model that makes MGAs a category of their own, the economics that make efficiency non-negotiable, the capabilities that matter, the data and compliance pressures bearing down on delegated authority right now, the platforms buyers shortlist and a practical framework for choosing. If you are about to make this decision, it is the most consequential technology call your business will make this decade.

MarketThe UK MGA market, and why this decision matters now

Start with the size of the thing, because it changes how seriously to take the buying decision.

The MGAA's 233 member MGAs wrote £13.2 billion of gross written premium across the UK and Republic of Ireland in 2024, spanning more than 250 product lines.¹ Membership has grown fast: up from 206 MGAs in 2023 and 187 in 2022, a 58.5% rise since 2019.⁵ By August 2025 the count had reached 249, and the MGAA now represents over 460 members in total, including MGAs writing in excess of £18 billion across 300-plus product classes.⁵ Milliman's 2025 analysis found over 300 MGAs placing more than 10% of the UK's £47 billion general insurance market,¹ a figure McKinsey reaches independently.² MarshBerry counts over 350 MGAs operating across the country.⁴

Worth flagging the measurement basis here, because the numbers get repeated loosely. The £47 billion figure recurs across MarshBerry, Milliman and McKinsey but ultimately traces to MGAA framing of the market. Other sources size UK general insurance above £90 billion on a wider scope. These are not contradictions so much as different counting rules, so when you read "10% of £47 billion", that is the basis being used.

Michael Keating, the MGAA's chief executive, described the picture in August 2025: the MGA sector continues to flourish in the UK, Ireland, Europe and internationally, and remains the fastest-growing property and casualty segment.¹¹ The global figures back the claim. Insuramore reported the worldwide MGA sector generated over $250 billion in written premiums and $29.25 billion in revenue in 2024 across roughly 3,000 MGA enterprises.⁶ In the United States, AM Best reported MGA premium grew 15% year on year to $89.9 billion in 2024,⁷ and McKinsey found US direct premiums placed through MGAs nearly doubled from $47 billion in 2020 to $97 billion in 2024.⁸

Then there is Lloyd's, where a lot of this premium actually lands. Lloyd's reported £55.5 billion of gross written premium in 2024, up 6.5% on the prior year, with an expense ratio of 34.4%.⁹ Delegated authority is now central to that market rather than a sideshow. Oxbow Partners found DA business at Lloyd's more than doubled from £10.4 billion in 2018 to £22.1 billion in 2023, taking its share of the market from 30% to over 40%, and they expect it to pass 45% by 2027.¹⁰ Rachel Turk, Lloyd's chief underwriting officer, put the current figure at 39% of gross written premium generated through delegated arrangements.¹⁰

So the model is growing, it is taking share, and it now carries a large slice of one of the world's most important insurance markets. That growth is not luck. MGAs win because they specialise in niche and complicated risks that traditional carriers often cannot price internally, and because the model is a structural response to rising risk volatility and carriers retreating from certain lines.² None of that specialisation survives contact with a platform that cannot adapt. The MGAs replacing legacy core systems and investing in innovation report growth between 1.16 and 1.98 times higher than those who do not.²

The modelWhy MGA insurance software is its own category

An MGA holds underwriting authority delegated directly by a carrier. That single fact pulls the technology requirement away from anything a traditional insurer or broker would buy.

Insurers carry the risk and the capital, and they tend to run broad standardised lines on large, departmentalised IT estates. Brokers sit on the distribution side, managing client relationships and quoting across multiple carriers, without binding in their own right. An MGA does something stranger. It underwrites like a carrier, distributes like a broker, frequently administers claims, and does all of it with a lean team across multiple carrier partners and diverse product lines. The structure demands MGA insurance software that is highly configurable by design, able to support different lines of business, complex rulesets and awkward workflows without an IT project every time something changes.

Speed is the obvious pressure. For an MGA, getting to market first is the competitive edge, which means the software has to support new product launches in days rather than months. Regulatory change has to be absorbed immediately, and that is only realistic if underwriters can configure and test changes themselves without writing code. The moment product logic lives in a developer's backlog, the MGA's core advantage is gone.

The underwriting itself is harder than standard rating engines were built for. MGAs make their money on risks that off-the-shelf raters cannot accommodate, which is precisely why the software has to carry predictive modelling, risk scoring and data enrichment from third-party sources. The point is to sustain an underwriting advantage rather than relying purely on distribution efficiency, and that needs a data architecture capable of handling complex datasets and the analysis that goes with them, without slowing the submission down.

Connectivity is the other structural demand. An MGA sits between carriers and agents, so the platform has to bridge both ends cleanly. Fragmented or outdated systems create silos, and silos create the communication delays and data errors that quietly erode an MGA's relationship with its capacity providers. The system is the connective tissue, or it is a liability.

Compliance scales badly without the right software, and this is where lean teams and rising regulatory demand collide. An MGA operating across jurisdictions or carrier panels needs pre-built regulatory frameworks, comprehensive regulatory data capture, rule-based engines and automated form generation for region-specific rates, rules, fees and taxes. It needs role-based access controls and detailed audit trails as standard. Done manually, compliance eats a lean team alive. Automated, it lets an MGA scale without adding compliance headcount in lockstep with premium. For a small team carrying delegated authority, that is the difference between growing and stalling.

There is a useful way to frame the contrast. A traditional insurer runs deep in-house rating on rigid legacy systems with large internal regulatory teams. A broker runs client and policy management with a focus on agent licensing. An MGA needs configurable, adaptable product capability, seamless multi-carrier integration, advanced underwriting tooling, automated multi-jurisdiction compliance and an affordable, scalable cost base from day one, all operated by business users rather than a standing IT department. Different job, different software for MGAs.

The cost base point deserves a moment on its own, because it is where MGAs most often get this wrong. A traditional insurer carries high fixed IT infrastructure as a cost of doing business, absorbed across a vast premium base. An MGA has neither the premium base nor the appetite for that kind of fixed cost. It needs technology that is cheap to start and scales with the book, which in practice means SaaS and cloud rather than owned infrastructure and long capital projects. Buy an enterprise carrier suite priced and sized for a tier-one insurer and the licence and implementation alone can swallow a young MGA's margin before it has written meaningful premium.

EconomicsThe economics that make every efficiency count

The MGA financial model is tight enough that software inefficiency comes straight out of profit.

McKinsey's breakdown of MGA revenue is the cleanest primary source on this. Commissions and overrides paid by insurers typically make up 60% to 80% of an MGA's revenue. Profitability contingents, the performance-based commissions, add 20% to 30%. Additional services such as claims administration and inspection bring the final 5% to 10%. McKinsey puts MGA EBITDA margins in the high twenties to low thirties.²

The headline commission rate flatters the reality, though. When business is placed through an MGA or wholesaler, the commission reaching the downstream agent or broker is often one half to one third less than a direct carrier appointment would pay. Strip out what flows downstream, subtract the MGA's own running costs and the retained margin can be thin enough that every operational saving matters.

You will see a figure quoted that the average UK MGA commission is around 30% of gross written premium. Treat that one with care, because it traces only to weak secondary sources and there is no clean named primary behind it, so it is not a number to build a business case on. The better-evidenced data sits at Lloyd's. The ICMR and LMA's "Lloyd's 2025 Insights Report", published in April 2025 and covering 2024, found that the gross acquisition cost ratio climbs from 20.1% for syndicates writing the least binder business to 25.8% for those writing the most, a spread of more than five percentage points, with gross combined ratios across those bands running from 77.1% to 84.2%.¹² The report is direct about why: delegated business carries significantly higher acquisition costs than, say, reinsurance.¹² Whichever view you take, the squeeze on acquisition cost is real and it lands on the MGA.

Now put the legacy bill next to those margins. PwC, in work with Ignatica, found that maintaining legacy systems eats roughly 70% of an organisation's IT budget on average, against a base where global insurers spent almost $101 billion on IT in 2015.¹³ The underlying data dates from 2015, so the 70% is best read as a long-standing benchmark rather than a current figure. The direction of travel is not improving either. Deloitte's 2026 Global Insurance Outlook found IT's share of total operating cost for the average property and casualty carrier rose from 17% to 24% over five years, and for life carriers from 26% to 29%.¹⁴

The waste is not only in maintenance. Accenture surveyed 430 underwriting executives and found the average underwriter spends 70% of their time on activities that are not underwriting: 40% on administration, 30% on negotiation and sales support, leaving only 30% for the actual job.¹⁵ Accenture puts the industry-wide efficiency loss at $85 billion to $160 billion over five years.¹⁵ That is what manual process and poor tooling cost, expressed as underwriter time burned on the wrong work.

McKinsey's modernisation research gives the upside. Modernising legacy systems can cut IT cost per policy by 41% and lift operations productivity by 40%, with faster processes and better customer experience adding 0.5% to 1.0% to premiums.¹⁶ BCG's 2024 analysis found around 35% of insurance applications still run on legacy stacks that are not cloud-ready, which is the gap the modernisers are closing.¹⁷ The shape is consistent across firms: legacy is expensive, modern is cheaper per unit of work, and for a business running on high-twenties margins the difference is not academic.

The shiftHow MGAs buy software now

The way MGAs buy technology has changed, and the change tells you what to look for.

The COVID-19 pandemic forced a digital overhaul across insurance, and investors rewarded the firms that used technology to operate differently. MGAs were well placed for that moment. They are smaller and more adaptable than carriers, with flatter leadership that can make investment decisions quickly, which makes them natural places to trial digital processes and new tools. For a while, insurtech funding chased novelty for its own sake.

That ended. Insurtech funding fell in 2023 on a broader market downturn and a run of businesses that could not show consistent profitability. The interest in technology-led MGAs did not vanish, but its character changed. Investment now favours durability and proven efficiency over experiment, which shifts the technology question from "what is the most cutting-edge thing we can buy" to "what gives us a robust, efficient core we can run profitably". MGAs need software that demonstrates operational efficiency and supports disciplined underwriting, with core functionality established first and the clever stuff layered on afterwards.

The subtlety worth holding onto is that disciplined does not mean static. The reason MGAs make good testing grounds for new technology is the same reason their platforms should stay flexible. A system chosen for today's products has to absorb tomorrow's, and technologies like AI as they mature, without a rebuild. Pick a platform solid enough to bet the business on and open enough to keep experimenting with, and you avoid the trap of buying something cutting-edge in 2026 that you are ripping out in 2029.

CapabilitiesThe capabilities that define great MGA software

Strip away the marketing and the best MGA software comes down to a handful of capabilities that have to be present together. Miss one and the others lose value.

Connectivity through an API-first design. MGA software has to act as the central nervous system of the operation, wired into external systems and data sources without custom plumbing each time. API-first architecture is the requirement, not the bonus. It means every component is reachable by external systems, so the MGA can connect to third-party data providers, insurtech tools and service partners and build the integrated ecosystem that real-time underwriting and claims depend on. Without it, every integration becomes a project, and an MGA does not have the time or the team for that.

Configurability that puts control in business hands. Low-code and no-code tooling is what lets an underwriter or product manager build and deploy without waiting on developers. It changes who creates the technology. Pre-built visual components let non-technical staff design, build and deploy with little or no code. The build-speed claims are striking: low-code platforms let teams build applications six to 20 times faster than traditional coding.¹⁸ The exact multiple comes from a trade publication rather than a consultancy study, so treat it as illustrative, but the direction is not in doubt. An MGA that can test a market idea cheaply and adjust on real feedback moves at a different speed to one filing change requests.

A cloud-native foundation for reliability and security. MGA volumes swing with seasons and with the deals they win, so the platform has to scale automatically and hold performance across regions and regulatory regimes. Cloud-native architecture gives the resilience to keep running and add resources on demand, and the security model that comes with managed cloud infrastructure handles sensitive data in a compliant way. McKinsey estimates the EBITDA run-rate impact of cloud on the insurance sector could reach $70 billion to $110 billion by 2030, among the top five of all sectors it analysed.¹⁹

Speed-to-market as a designed-in property. Agile operating models can let insurers launch products up to five times faster than traditional methods.²⁰ McKinsey's AI work shows where this is heading: specialty risk-engineering tools have cut quoting from more than a month to days, and commercial and specialty P&C models with predictive win rates can return quotes in one to two hours instead of two to three days.⁸

AI and automation as a native layer. This has moved from experiment to expectation. Accenture's figures are the clearest insurance-specific numbers available: 29% of working hours in the insurance industry can be automated by generative AI, and a further 36% can be augmented by it.²¹ In underwriting specifically, Accenture finds up to 65% of working hours are subject to automation or augmentation, with up to 30% productivity gains at stake, and senior underwriting executives expect AI adoption to climb from 14% today to 70% within three years.¹⁵ McKinsey estimates generative AI could unlock $50 billion to $70 billion in industry revenue.⁸ These are projections rather than booked results, so read them as the size of the prize rather than money already earned.

The proof that it works is already in the UK. Aviva rolled out more than 80 AI models in claims, cutting complex liability assessment time by 23 days, improving routing accuracy by 30%, reducing complaints by 65% and saving over £60 million in 2024, according to McKinsey.²² That is what a native AI layer delivers when it sits inside the core platform rather than hanging off the side as a bolt-on.

For an MGA specifically, the places AI earns its keep are concrete. Intelligent underwriting support that pre-fills and pre-scores a submission so an underwriter spends time on the risk rather than the data entry. Predictive analytics that flag which submissions are likely to bind, so effort goes where it converts. Automated claims routing and fraud detection that move a claim to the right hands without a human reading every line first. Document and correspondence generation that turns a bound risk into the paperwork it needs without anyone retyping anything. Set against Accenture's finding that underwriters lose 70% of their time to non-underwriting work,¹⁵ every one of these is time handed back to the part of the job that makes money.

There is a caveat that separates the winners from the disappointed. Capgemini found only 10% of property and casualty insurers, the ones it calls intelligence trailblazers, treat AI as a core operating capability, and those firms achieved 21% higher revenue growth and 51% greater share-price gains between 2021 and 2024.²³ Among P&C leaders, 40% say AI is meeting expectations while 42% have not measured AI outcomes at all.²³ Deloitte found 76% of organisations had already implemented generative AI, yet fewer than half believed the benefits clearly outweighed the risks.²⁴ The lesson sits underneath all of it: AI does not rescue a weak foundation. Clean accessible data and well-defined processes come first, then AI makes them better. Plug a model into a mess and you get a faster mess.

Data accessibility and real-time reporting. Too many MGAs still run on manual extraction into spreadsheets, which McKinsey notes is no longer effective for decision-making.² Good MGA software gives real-time access to operational, third-party and customer data, with the kind of centralised cloud repository and business intelligence dashboards Deloitte case studies link to improved accuracy and completeness.²⁴ That is what lets decisions get made with confidence from the underwriting floor to the board.

Scalability and portability. Growth should not require an infrastructure project. Cloud-based platforms scale storage and compute on demand, so an MGA can meet rising demand without slow rollouts or costly hardware, and the same flexibility works in reverse when a line contracts.

ComplianceData, bordereaux and the compliance reckoning

If there is one area where MGA software earns or loses its keep right now, it is data and delegated authority reporting. The pressure here is current, it is UK-specific, and it is getting sharper.

Start with bordereaux, the reporting that flows risk and claims data from MGAs up to carriers and reinsurers. InsTech describes it plainly: bordereaux reporting is a major drag on the delegated authority market, with manual inconsistent processes delaying data, restricting capital flow and undermining trust across MGAs, carriers and reinsurers.²⁵ Reporting typically lags by 30, 60 or even 90 days.²⁵ Rachel Turk at Lloyd's called it bizarre that syndicates are still receiving bordereaux data that is out of date.²⁵ When DA is already 39% of Lloyd's premium and heading past 45%, stale data on that volume is a structural problem rather than an admin annoyance.

Lloyd's has been trying to fix the data plumbing through Blueprint Two, which targets £800 million of savings for market participants and introduces the Core Data Record as a single source of standardised, quality transactional data linking accounting, payment, claims and reporting.²⁶ Open market and delegated authority together account for 80% of premium and 90% of contracts placed at Lloyd's, so the standard matters across the whole market.²⁶ The wrinkle for MGAs and managing agents came in September 2024, when Lloyd's removed the Delegated Data Manager, the central bordereaux processing platform that had run since 2018, as a mandated core service.²⁶ Each managing agent now has to choose its own bordereaux platform. That decision pushes the responsibility for structured, timely, standards-compliant delegated data straight onto the software an MGA and its partners run.

The regulator is moving in the same direction. The FCA set out its insurance priorities in February 2026, and from the second quarter of 2026 it will expand its oversight review to include delegated authority models and remuneration arrangements, with findings expected in early 2027.²⁷ It will also assess how firms use AI in underwriting, claims and consumer services.²⁷ This is not the regulator's first look at delegated authority. Its 2015 thematic review, TR15/7, found that insurers did not always treat delegated arrangements as outsourcing and that oversight of product performance and service delivery was insufficient.²⁸ Linda Woodall, then at the FCA, was clear that all firms must have appropriate oversight of outsourced arrangements and meet their wider responsibilities to deliver fair customer outcomes.²⁸ The 2026 review is that concern, returning with remuneration in scope.

Two more pieces complete the picture. The FCA's operational resilience rules under PS21/3 reached full compliance in March 2025, requiring firms to identify important business services, set impact tolerances and run scenario testing.²⁹ And in September 2025, under PS25/21, the FCA declined to extend sole manufacturer status to MGAs, which keeps accountability shared across delegated frameworks rather than letting it sit with one party.³⁰ Against all this, the operational reality is that over 90% of the MGAA's MGA members outsource claims to a third party,¹¹ which multiplies the number of relationships that need oversight and clean data running between them.

Pull it together and the software requirement writes itself. MGA insurance software now has to produce structured, standards-aligned delegated data on time, carry the audit trails and access controls that fair-outcome oversight depends on, survive operational resilience testing, and give carriers the visibility the FCA increasingly expects. Software that treats bordereaux as an export-to-spreadsheet afterthought is software that will fail an oversight review in 2027.

It is worth being clear about who is applying this pressure, because it is not only the regulator. Carriers delegating their pen are tightening their own oversight in parallel, partly because the FCA has told them to and partly because stale, inconsistent data makes it impossible to manage the risk they have handed over. A carrier that cannot see how a binder is performing until the bordereaux lands two months late is flying blind on its own book, and capacity providers have started pricing that uncertainty into their willingness to renew. For an MGA, clean and timely data is no longer just a compliance line. It is a capacity-retention tool, and the platform is what makes that possible or impossible.

VendorsThe best software for MGAs: the platforms buyers shortlist

When an MGA runs a serious procurement, a familiar set of names lands on the shortlist. Each one solves a different version of the problem, and the differences matter more than the feature grids suggest. Treat what follows as a map of where each platform sits rather than a ranking, because the right answer depends on the size and shape of the MGA buying.

Guidewire is the heavyweight of the carrier world. Its PolicyCenter, ClaimCenter and BillingCenter suite, delivered through Guidewire Cloud, is deep, mature and widely deployed across large insurers, and its Advanced Product Designer lets product and IT teams co-develop and visualise a product during design. The trade-off is scale. Guidewire is engineered for large carriers, and the cost, implementation length and operational weight that come with it can be more platform than a lean MGA needs or wants to fund.

Duck Creek sits in similar territory, a cloud-native SaaS suite for property and casualty with a strong configuration model and an OnDemand delivery approach. It is capable and modern, with a clear enterprise orientation. The same question applies as with Guidewire: an MGA has to weigh whether it is buying capability it will use or capability it will pay to carry.

Vertafore comes from a different heritage. Its strength is agency and distribution management, with products such as AMS360 and Sagitta rooted in the US agency market. For distribution-heavy operations that lean on broker and agency workflows, that pedigree is genuine. For an MGA whose core need is configurable underwriting authority and delegated data, the fit depends on how much of the job is distribution versus underwriting.

Majesco offers broad cloud core systems across both property and casualty and life and annuity, with a wide product footprint and a largely US-centric base. It is a credible enterprise option with reach across lines, and as with the other enterprise suites the buying question is about fit to the MGA's actual scale rather than raw capability.

Genasys is built for the brief this guide describes. It is a cloud-native platform covering policy administration, claims and billing in a single configurable system, designed for insurers, MGAs and brokers rather than only the largest carriers. It is API-first, configurable by business users without code, and it runs across multiple territories including the UK, South Africa and Australia, which matters for MGAs operating across jurisdictions and reporting regimes. The positioning is speed-to-market and connectivity at a cost base an MGA can carry from day one.

The honest framing is this. The enterprise suites are powerful and proven, and for a large complex carrier they earn their cost. For an MGA running lean margins, multiple carrier partners and a need to launch fast, the best software for MGAs is rarely the heaviest suite. The deciding factor is whether the platform's weight, cost and configurability match how the business actually operates. Buy the system that fits the team you have, not the team a tier-one carrier has.

SelectionHow to choose MGA software

A demo will always look good. The best MGA software is the one that survives three years of real trading, so the buying process has to dig past the showcase.

Start with speed-to-market, and make it concrete. Ask to see a new product configured and deployed, end to end, by a business user rather than a developer. If launching a product still needs an IT project, the platform fails the core MGA test no matter how it markets itself. Time the change to a rating rule, not just the build of a new line.

Interrogate the data and bordereaux story directly, because this is where the 2027 oversight review will bite. Ask how the platform produces delegated data, whether it aligns to the Core Data Record, how it handles the move off the Delegated Data Manager, and how it gets carrier-ready reporting out without a 60-day lag. A vendor that cannot answer this clearly is selling you a future compliance problem.

Pressure-test the AI claims against the foundation underneath them. Capgemini and Deloitte both found that adoption runs well ahead of measurable benefit,^{23 24} so the real question is whether the platform has the clean accessible data and defined processes that make AI worth anything. Ask what is automated natively versus bolted on, and ask for outcomes that have been measured rather than promised.

Map the cost against your margin honestly. If the MGA runs on high-twenties EBITDA and the platform's total cost of ownership, implementation included, is sized for a tier-one carrier, the maths does not work however impressive the system. Total cost of ownership over five years tells you more than the licence fee.

Check the connectivity model rather than taking API-first as a slogan. Ask which third-party data providers and partners are already integrated, what a new integration actually takes, and whether the architecture genuinely exposes its components or just ships with a few endpoints.

And weigh configurability against your own team. The whole argument for low-code and no-code is that business users hold the controls. If using the platform still routes every change through a developer, you have bought enterprise software with a friendlier login screen. Have an underwriter try to configure something in the evaluation, and watch what happens.

One more check, and it is the one buyers skip most often. Talk to an MGA of roughly your size that already runs the platform, and ask them what broke. Not what works in the demo, what broke in year two when they launched a line the vendor had not anticipated, or when a carrier changed its bordereaux format, or when they tried to scale the book three times over. The difference between a good platform and a painful one shows up there rather than in the sales deck.

At launchThe MGA software non-negotiables at launch

For an MGA standing up its platform, a working set of features has to be present on day one. These are the capabilities that let the business operate, comply and grow rather than the extras that can wait.

A configurable product and rating engine that supports niche and complex risks, built so underwriters can create and adjust products without code. Workflow configuration in the same no-code mould, so process changes do not become IT tickets. API-first integration that connects cleanly to carriers, agents, third-party data and insurtech partners. A cloud-native architecture that scales with volume and holds up across regions. Delegated authority and bordereaux reporting that produces structured, standards-aligned, carrier-ready data without the 30 to 90 day lag the rest of the market is still fighting.

Compliance built in rather than added later: regulatory data capture, rule-based engines, automated form generation for region-specific rates and taxes, role-based access controls and detailed audit trails that stand up to an FCA oversight review. Automated document generation across the policy lifecycle. Business intelligence and dashboards giving real-time visibility into submission-to-bind ratios, producer performance, carrier profitability and claims patterns. Claims administration capability, given how many MGAs run claims and how closely the FCA is watching outsourced arrangements. And a security and resilience posture that satisfies operational resilience requirements and keeps sensitive data compliant.

Get those right and the MGA has a platform that does the job the model demands: fast to market, configurable by the people who run the business, clean on data, defensible on compliance and affordable enough to leave the margin intact. That is what the best MGA software is for.