Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
Table of Contents
- What does a fraud detection AI agent in customer support actually need to do?
- 1. It spots the conversations that aren't normal tickets
- 2. It gives only your approved safety steps
- 3. It keeps a review confidential
- 4. It answers verification-status questions from the account itself
- 5. It hands over with the details the fraud team needs
- 6. It reaches the right person fast, at any hour
- How did I score these fraud detection AI agents?
- The 6 fraud detection AI agents for customer support at a glance
- Where does AI go wrong on fraud and scam conversations?
- Failure mode 1: It answers a fraud report like a routine question
- Failure mode 2: It says the wrong thing
- Failure mode 3: It hands over empty-handed, to the wrong place
- Can My AskAI handle fraud and scam conversations safely?
- How does My AskAI handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using My AskAI for fraud and account-review conversations?
- What does My AskAI cost at 1,000 conversations a month?
- Can Fini handle fraud and scam conversations safely?
- How does Fini handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using Fini for fraud and account-review conversations?
- What does Fini cost at 1,000 conversations a month?
- Can Intercom Fin handle fraud and scam conversations safely?
- How does Intercom Fin handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using Intercom Fin for fraud and account-review conversations?
- What does Intercom Fin cost at 1,000 conversations a month?
- Can Zendesk AI agents handle fraud and scam conversations safely?
- How do Zendesk AI agents handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using Zendesk AI agents for fraud and account-review conversations?
- What does Zendesk AI agents cost at 1,000 conversations a month?
- Can Decagon handle fraud and scam conversations safely?
- How does Decagon handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using Decagon for fraud and account-review conversations?
- What does Decagon cost at 1,000 conversations a month?
- Can Ada handle fraud and scam conversations safely?
- How does Ada handle a fraud report end to end?
- How it handles the 6 things a support team needs
- Who's using Ada for fraud and account-review conversations?
- What does Ada cost at 1,000 conversations a month?
- What does handling fraud and verification conversations with AI save you? (worked example)
- So which fraud detection AI agent is best for customer support?
- FAQs
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My AskAI scores 66 out of 80 and ranks first of six fraud detection AI agents for customer support on fraud, scam and verification-status conversations. Fini is second on 57 with the fullest fraud-report flow on its pages.
A customer writing about a payment they didn't make can sound almost exactly like one asking about a transfer or a PIN reset, so your agents have to read every message closely, find the approved wording and write up a careful handover for your fraud team. Scam stories, questions about a stuck verification check and messages from customers whose accounts are under review need the same care. An AI agent can tell them apart once someone sets it up, and I scored six tools on how well that setup works.
In customer support, a fraud detection AI agent is one that recognizes a fraud report, a scam or a stuck account review, sends only the safety wording you signed off on and keeps any review private. It then passes the conversation to your fraud team with what they need to act. It works on conversations with customers you already have, and it doesn't monitor transactions or run signup checks.
I'm Mike, co-founder of My AskAI. We help 200+ ecommerce and SaaS businesses run AI customer service inside the helpdesk they already use, and My AskAI is one of the six tools reviewed here.
I priced every tool against my estimate of $2,400 a month to handle 1,000 of these conversations by hand. Our human handoff roundup covers handover in general. One of our customers, a creator-monetization platform, keeps its trust and safety tickets with people while the AI takes the routine work.
My AskAI leads the scoreboard at about $313 a month for 1,000 of these conversations on its Pro plan, counting the Task and AI Tagging charges. Here's the team each tool suits best:
- My AskAI (best for fraud and scam topics set in plain language inside your helpdesk) - Sends your approved safety wording word for word and hands over with a summary. Its tags and handovers set off your helpdesk's own priority and after-hours rules.
- Fini (best for fintech teams that want a ready-made fraud-report flow) - Captures the report, locks the account and routes it to your risk team. Its pricing page doesn't show the plan fee, which is the whole bill at this volume.
- Intercom Fin (best for sending each escalation type to a different team) - Splits when to escalate from where the conversation goes. The fraud team's questions get asked after the handover.
- Zendesk AI agents (best for escalating by email when nobody is online) - Lays out the after-hours switch step by step. Its pay-as-you-go bill is about three times ours.
- Decagon (best for enterprise fintechs that want every conversation checked after the fact) - Names fraud alerts and dispute workflows and transfers calls with a summary. Its homepage and product pages lead to a demo, with no price shown.
- Ada (best for enterprise teams that want sign-in before sensitive answers) - Documents off-hours handoff paths and handoff summaries. Pricing comes from sales.
What does a fraud detection AI agent in customer support actually need to do?
TL;DR: Six jobs: spot the conversations that aren't normal tickets, give only your approved safety steps, keep any review confidential, answer verification-status questions, hand over with the details, and reach the right person fast at any hour.
A tool can be strong on one of these jobs and weak on the next, so I score every vendor on all six separately.
1. It spots the conversations that aren't normal tickets
"Where is my payment?" and "I didn't make this payment" use almost the same words. So do "my card doesn't work" and "my card was stolen". An unrecognized payment, a customer who was tricked into sending money, someone claiming to be from your bank, a frozen account: the AI has to recognize each one and stop treating it as routine.
You should be able to name those topics in plain language and have the AI follow them. A wallet app might list "a payment I didn't make", "someone asked me for a code" and "my account is frozen" as topics that leave the routine path the moment they appear.
2. It gives only your approved safety steps
The customer needs the right first step now: freeze the card through the proper route, change a password, never share a code. The AI should give the steps your team has approved, word for word, and never guess whether the money will come back.
The AI never asks for a PIN, password or one-time code, and it tells the customer so. Scammers pose as the bank's fraud team and ask for exactly those codes, which is why consumer-protection guidance says:
"Never share a verification code. Ever." From US consumer-protection guidance on bank-fraud calls.
3. It keeps a review confidential
When an account is under a fraud or compliance review, the AI gives your approved status wording and doesn't reveal that a review exists or why. It doesn't speculate, and it doesn't read out whatever it can see on the account.
For a bank this is also a legal matter. US banking rules say a bank and its staff must not disclose a suspicious activity report or any information that would reveal one exists, so your compliance lead will want to sign off on the exact words.
4. It answers verification-status questions from the account itself
"Why is my verification still pending?" reaches every inbox that checks new customers. When the AI can read the customer's real status from your systems, it can say what's outstanding (a missing document, or a normal wait) and close the conversation. When the status shows a review or a rejection, it hands over with the approved wording from job 3.
5. It hands over with the details the fraud team needs
Before handing over, the AI collects what your fraud or compliance team asks for: which payment, when, how the customer was contacted and whether they shared a code. A scam victim who has to repeat their story to a second person loses faith fast. I mark a tool down when its handover leaves the fraud team asking again.
The handover includes a summary and a record of what the AI already said and did. Once a person has the conversation, the AI stays out of it.
6. It reaches the right person fast, at any hour
A fraud report goes to the fraud team ahead of routine work, and a 3am report doesn't sit until morning. Where nobody is on shift, the customer is told clearly what happens next and when. Asking for a person always works, whatever the topic, and I treat that as mandatory.
How did I score these fraud detection AI agents?
TL;DR: Eight criteria, each scored out of 10: the six jobs above, plus how much work setup takes and what it costs a month at 1,000 conversations, summed to a total out of 80.
The scores come from each vendor's own help articles, product pages, pricing pages and customer stories. A job missing from a vendor's pages is scored on the nearest control those pages describe.
The eight criteria are:
- Spots fraud and scam conversations - whether you can name the topics that aren't routine and the AI reliably treats them differently
- Gives only approved safety steps - whether the AI can be held to your exact approved wording on these topics
- Keeps a review confidential - whether you control exactly what the AI says about an account under review
- Answers verification-status questions - whether the AI can read the customer's real status, answer it and hand over the cases it should
- Hands over with the details - whether the AI gathers what the fraud team needs and passes on a summary and what it did
- Reaches the right person fast - routing to the right team, priority over routine work, what happens after hours, and a route to a person that always works
- Setup effort - the time and people needed to go live, assuming your team uses AI to draft the rules and wording
- Monthly cost at 1,000 conversations - the lowest plan that covers the volume, monthly, on one declared basis
The scores cover chat and email only. Fraud reports can also arrive by phone, so I note which tools take calls where their pages show it.
The 6 fraud detection AI agents for customer support at a glance
TL;DR: 66 out of 80 puts My AskAI top. Fini's written-out fraud-report flow earns it 57, a point ahead of Intercom Fin, whose 56 rests on sending fraud reports and stuck verifications to different teams.
Here are the eight scores for each tool, ordered by total from left to right:
(scores out of 10) | My AskAI | Fini | Intercom Fin | Zendesk AI agents | Decagon | Ada |
Spots fraud and scam conversations | 9 | 9 | 8 | 7 | 8 | 7 |
Gives only approved safety steps | 9 | 7 | 7 | 6 | 7 | 7 |
Keeps a review confidential | 8 | 7 | 7 | 6 | 6 | 6 |
Answers verification-status questions | 8 | 9 | 7 | 6 | 7 | 7 |
Hands over with the details | 9 | 8 | 6 | 7 | 8 | 7 |
Reaches the right person fast | 7 | 7 | 8 | 8 | 7 | 7 |
Setup effort | 8 | 5 | 7 | 6 | 4 | 5 |
Monthly cost at 1,000 conversations | 8 | 5 | 6 | 4 | 2 | 2 |
Overall (out of 80) | 66 (83%) | 57 (71%) | 56 (70%) | 50 (63%) | 49 (61%) | 48 (60%) |
Same eight criteria, in plain words:
Criterion | My AskAI | Fini | Intercom Fin | Zendesk AI agents | Decagon | Ada |
Spots fraud and scam conversations | Named topics, per-tag reply setting | Report, lock, route flow | Attribute rules, plain-language guidance | Automatic email screen | Fraud alerts named, escalation rules | Instructions and context routing |
Gives only approved safety steps | Custom Answers, word for word | Reply rules, set policies | Guidance and Procedures | Template replies in flows | Guardrails on responses | Instructions within constraints |
Keeps a review confidential | Say-nothing or notes-only setting | No-reply rules per condition | Matched rule gives no answer | Screened emails get no reply | No named control | No named control |
Answers verification-status questions | Live status via User Data | Clears verification holds | Reads account data | Payment status, signed-in answers | Balance and account issues | Sign-in, then account lookups |
Hands over with the details | One pass of questions, summary | Full context on escalation | Details gathered after handover | Gathers details, no summary | Transfer with concise summary | Summary on listed platforms |
Reaches the right person fast | Your helpdesk's routing rules | Routes to risk team | Workflow branch per type | After-hours email escalation | Around the clock, routing unshown | Off-hours paths, five handoffs |
Setup effort | Helpdesk app, one week | Live in 14 days | Admin switches, plain rules | Flow builder, developer step | Vendor-led implementation | Enterprise implementation |
Monthly cost at 1,000 conversations | About $313 on Pro | Plan fee, not shown | $495 to $990 | $712.50 to $950 plus seats | Demo, no price shown | Demo, no price shown |
We lead on approved wording sent word for word, a say-nothing setting for accounts under review, and a handover with the fraud team's details and a summary. We also have the lowest published bill at this volume. Intercom Fin and Zendesk AI agents both beat us on reaching the right person fast, because their help articles show routing steps inside the AI setup (Zendesk's adds an after-hours step), where ours run in your helpdesk's own rules.
Fini is second on the strength of its finance page, which describes a fraud report from capture to lock to the risk team and names clearing verification holds as a job. If your bank or fintech also takes fraud reports by phone, Fini outscores Decagon and Ada, which take calls too.
Where does AI go wrong on fraud and scam conversations?
TL;DR: Three ways: it treats a fraud report as a routine payments question, it says the wrong thing (asks for a code, promises money back or reveals a review), or it hands the conversation over empty-handed to the wrong place.
The three failures follow the order of a conversation, from the first reply to the handover.
Failure mode 1: It answers a fraud report like a routine question
A customer writes "I didn't make this payment" and gets "payments can take 3 to 5 business days". The AI matched the word "payment" and answered the question it sees most often.
Human teams make the same mistake. A regulator's findings on how banks handle scam reports found slow replies, mishandled reports and confusing messages to customers who'd been scammed, along with front-line staff who hadn't been trained to support them.
To test it, type "I didn't make this payment" into the demo and see whether you get a timing answer. A good setup takes that message off the routine path the moment it appears.
Failure mode 2: It says the wrong thing
The AI asks for a one-time code "to check", guesses whether the money will come back, or tells a customer under review why their account is frozen. The first one does the most damage, because a real bank's fraud team never asks for the code. An AI that asks for one teaches your customers to hand codes over.
Ask it "can you check my code?" and "why is my account frozen?" in the demo. You should get your approved wording on these topics, word for word, and nothing else.
Failure mode 3: It hands over empty-handed, to the wrong place
The report lands in the general inbox behind routine tickets with no summary. At night it waits until morning, and when the fraud team finally picks it up, they ask the customer everything again. One customer stuck in a verification check wrote that the chat kept ending because of their account status, so they couldn't even get a number to complain to.
To me, it should always be easy to reach a person, whether the customer asks, the AI can't answer, they're clearly upset or it's a topic a person should handle. Every handover should also include a summary of the conversation so far. Test it by reporting a fraud at night and checking where it lands, what it carries and what the customer was told.
Can My AskAI handle fraud and scam conversations safely?
TL;DR: My AskAI works inside your existing helpdesk and covers 5 of the 6 jobs fully, strongest on approved wording and on handing over with the fraud team's details. Its tags and handovers drive your helpdesk's own routing and after-hours rules, and 1,000 conversations cost about $313 a month on Pro.
We built My AskAI to work inside the helpdesk your team already runs: Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot. It installs as an app from each helpdesk's marketplace, so replies, internal notes, tags and handovers all stay where your fraud team already works.
Routine payment questions get answered from your help content, Custom Answers and historic tickets. You take the fraud, scam and review topics out of that path.
How does My AskAI handle a fraud report end to end?
You name the topics in Guidance, using plain-language Handover & Escalation rules such as "a customer says they didn't make a payment", and the rule forces a handover whenever that topic comes up. AI Tagging is our second control. Each tag has a setting to reply to the customer, draft an internal note for a person to send, or say nothing at all, and a blocked tag forces a handover too. Both controls take plain words and you aim each one at your fraud topics, so spotting these conversations gets a 9 from me.
Custom Answers return the exact answer your team approved, so the safety steps go out word for word. That pinned wording, already in use at the creator-monetization platform, is why approved steps get a 9. For an account under review, the say-nothing or internal-note setting keeps the AI off the category and a Custom Answer holds the status line. Because you aim those two general controls at your review topics yourself, I score this job 8.
When your helpdesk has already identified the customer, our User Data feature gives the AI that customer's account record, including verification status if your system holds it. A Task then asks for the missing document. Your developer connects your account system once, and from then on the AI reads live status. Our 8 on status questions sits a point behind Fini, whose page names clearing verification holds as a job outright.
Before handing over, a Task asks the fraud team's questions in one pass (which payment, when, how they were contacted, whether they shared a code), and the answers stay in the ticket history. The AI writes a summary before every escalation, a step that can't be switched off, then stays out of the ticket until your team hands it back. We score 9 here because nobody on the fraud team has to ask the customer again.
The fraud tag or the handover sets off the routing, priority and after-hours rules you already run in your helpdesk, and customers can ask for a person at any time. Intercom Fin and Zendesk beat us by a point here, 8 to our 7, because their articles show the routing steps inside the AI setup. Topic alerts give early warning of a scam wave: we can email or Slack you when a topic comes up a set number of times in a set window.
If you want the AI to freeze a card, it does that through a Tool connected to your card system, and you choose per action whether it acts alone or drafts the action for an agent to approve. Afterwards, your team can ask Echo, the assistant in our dashboard, what the AI said and why.
Setup scores 8. Most teams see draft replies within 15 minutes of installing and go live within a week, and every integration starts in internal-note mode. Paste your fraud team's current scripts into an AI tool and it will draft the Guidance rules and Custom Answers in an afternoon, leaving connecting User Data or a Tool as the one developer step.
How it handles the 6 things a support team needs
My AskAI covers 5 of the 6 jobs fully, and on the sixth its tags and handovers drive your helpdesk's own routing.
Job | My AskAI |
Spots the conversations that aren't normal tickets | ✅ Guidance rules and per-tag reply settings |
Gives only your approved safety steps | ✅ Custom Answers, word for word |
Keeps a review confidential | ✅ say-nothing or internal-note setting, approved status line |
Answers verification-status questions | ✅ User Data reads the record, a Task asks for what's missing |
Hands over with the details | ✅ one pass of questions, a summary every time |
Reaches the right person fast, at any hour | ⚠️ partial: tags drive your helpdesk's routing, a person on request |
Who's using My AskAI for fraud and account-review conversations?
Four of our customer stories show these controls at work for companies that handle their customers' money:
- A creator-monetization platform on Zendesk - runs a separate trust and safety team, and those tickets stay human-only, as do payout disputes and account security. Custom Answers pin replies to the exact text the team approved, and it widens the AI one category at a time with Zendesk tags and triggers.
- An iGaming operator on Intercom - feeds live player data into the AI through User Data, which powers two payments Tasks for deposits and payouts. It went from internal notes to a test audience, then to direct replies in batches.
- A high-volume prop-trading platform on Intercom - handles about 105,000 tickets a month with Custom Answers for payout policy and account-status explanations, while the team keeps anything sensitive.
- A crypto-tax software company on Intercom - spent a setup phase getting the escalation behavior right, so the agent stopped cleanly once a person took over, before it switched to direct replies.
What does My AskAI cost at 1,000 conversations a month?
Pro is $199 a month with 1,000 credits included, then $0.12 a credit. I've assumed 600 conversations arrive by chat and 400 by email, with about two AI replies each. Two chat replies use one credit and an email with one follow-up uses 1.5, so the month uses 1,200 credits: $199 plus 200 extra credits at $0.12, or $223.
Tasks and AI Tagging bill on top on every plan. Tasks cost $0.02 for each AI reply made while a Task runs, and I've assumed two per conversation, which adds $40. AI Tagging costs $0.05 per attribute per ticket, so one attribute adds $50 and brings the month to about $313, or $0.31 a conversation. We bill the same whether the AI finishes the conversation or hands it over.
Cost is an 8, and the $90 of add-ons in this example is what keeps it off a 10. Our 30-day free trial unlocks every feature with no card, so you can prove it on your own fraud and status conversations before you pay.
Choose My AskAI for fraud and scam conversations if:
- Your team works in Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot and wants fraud topics handled there.
- You want your approved safety steps and status lines sent word for word.
- You want a summary on every handover, and the fraud team's details collected first on live chat.
- You want the lowest published bill at this volume.
Don't choose My AskAI for fraud and scam conversations if:
- Most of your fraud reports arrive by phone and you want the AI to take the calls.
- You want the vendor to hand you a ready-made fraud-report flow, with no rules of your own to write.
- You want after-hours routing configured inside the AI itself.
Can Fini handle fraud and scam conversations safely?
TL;DR: Fini's finance page describes the fullest fraud-report flow here, capturing the report, locking the account and routing it to your risk team, and it covers 3 of the 6 jobs fully. Fini bills $0.89 for each resolution past the plan's monthly allowance.
Fini is an AI agent that covers chat, email and voice. Its finance page is written for fintech teams and lists disputes, fraud claims and fraud reporting among the jobs it takes on.
How does Fini handle a fraud report end to end?
For fraud reporting, Fini's page lists three steps in one line: "Capture the report, lock the account, and route to your risk team."
Fini's page writes out the fullest fraud-report flow of the six vendors, and that flow puts Fini level with us on 9 for spotting these conversations. For a disputed charge, the agent will "Verify the customer, pull the transaction, and check it against your fraud rules before anyone is paged."
The same page lists walking customers through document upload and clearing verification holds, and Fini pulls live payment, transfer and payout status. Naming verification holds as a job outright puts Fini on 9 for status questions.
Wording controls are less specific. Fini's reply rules decide whether the agent replies, adds an internal comment or stays silent when set conditions match, and the finance page says its actions run inside your policies. Its pages show no pinned answer your team writes word for word, so approved safety steps score 7 (the same reply rules put reviews at 7 too).
On handover, the page says Fini "Escalates to a human with the full context", an 8. Reaching the right person fast gets a 7, because Fini's pages describe routing fraud reports to your risk team and nothing on after-hours handling or on a customer asking for a person. Setup is a 5, because you start with a demo and the page promises "Live in 14 days, autonomous in 30".
How it handles the 6 things a support team needs
Fini covers 3 of the 6 jobs fully, and its strongest part is the written-out fraud-report flow.
Job | Fini |
Spots the conversations that aren't normal tickets | ✅ fraud reporting and fraud claims named |
Gives only your approved safety steps | ⚠️ partial: reply rules, actions inside your policies |
Keeps a review confidential | ⚠️ partial: no-reply or internal-comment rules |
Answers verification-status questions | ✅ clears verification holds from live status |
Hands over with the details | ✅ escalates with the full context |
Reaches the right person fast, at any hour | ⚠️ partial: routes to your risk team |
Who's using Fini for fraud and account-review conversations?
Atlas is the clearest fintech story on Fini's site. Fini says Atlas reached 70% automation on its fintech support, including KYC (the identity checks a company runs on its customers) and account changes. Wefunder is another named Fini customer.
What does Fini cost at 1,000 conversations a month?
Fini's pricing page shows "$0.89 per resolved ticket" on its Growth plan, billed only on resolutions past a monthly allowance of at least 2,000,
Choose Fini for fraud and scam conversations if:
- You're a fintech team that wants a documented fraud-report flow that locks the account and routes to your risk team.
- You want questions about verification holds answered from live account data.
- You take fraud reports by phone as well as chat and email.
Don't choose Fini for fraud and scam conversations if:
- You need a published monthly total before you talk to sales.
- Your policy requires a documented route to a person that works at every step.
- You want to go live within a week.
For more on Fini, read our complete guide or browse the Fini alternatives roundup.
Can Intercom Fin handle fraud and scam conversations safely?
TL;DR: Intercom Fin splits when to escalate from where the conversation goes, so each type of escalation reaches the right team, and it covers 2 of the 6 jobs fully. The fraud team's questions get asked after the handover, and Fin costs $0.99 per outcome, from $495 a month here.
Fin is Intercom's AI agent. It runs inside Intercom, or on another helpdesk if you buy Fin on its own.
How does Intercom Fin handle a fraud report end to end?
Two controls decide when Fin steps back. Escalation Rules hand off when set data is detected, such as an attribute you use to mark an account under review, and Escalation Guidance lets you describe in plain words when to escalate, including an "Escalate immediately" option. Intercom's escalation article uses frustration, bugs and order totals as its examples, so the fraud topics are yours to write. I still give this job an 8 for those two controls.
When an Escalation Rule matches, Fin gives no answer at all and passes the conversation to your team. If you mark reviewed accounts with an attribute, that silence keeps the review private, so keeping reviews confidential scores 7. Guidance and Procedures steer replies on these topics, and the articles show no pinned word-for-word answer, so approved safety steps also score 7. Status questions land on 7, with Fin reading account data through data connectors (and an optional email code).
Routing is where I rate Fin highest. The article sets out the split: "Escalation Rules and Guidance decide when escalation happens. Workflows decide what happens next." A Workflow branch for each escalation type can send a fraud report to one team and a stuck verification to another, and that earns the 8 on reaching the right person fast.
Collecting details happens in the Workflow after the handover, and Procedures can't write a summary note on escalation, so handing over with the details scores 6. Setup is a 7 for me, because turning this on takes admin switches and plain-language rules, with nothing to build.
How it handles the 6 things a support team needs
Intercom Fin covers 2 of the 6 jobs fully, and its strength is sending each escalation type to a separate team.
Job | Intercom Fin |
Spots the conversations that aren't normal tickets | ✅ attribute rules and plain-language guidance |
Gives only your approved safety steps | ⚠️ partial: Guidance and Procedures steer replies |
Keeps a review confidential | ⚠️ partial: a matched rule means no answer |
Answers verification-status questions | ⚠️ partial: reads account data, optional code |
Hands over with the details | ⚠️ partial: details gathered after the handover |
Reaches the right person fast, at any hour | ✅ a Workflow branch per escalation type |
Who's using Intercom Fin for fraud and account-review conversations?
Intercom credits Fin with resolving 50% of Fundrise's support volume, and Rocket Money moved its support model onto Fin as its user base grew. Both are consumer finance companies, and both stories describe support as a whole.
What does Intercom Fin cost at 1,000 conversations a month?
Intercom's pricing page says "Fin is priced at $0.99 per outcome." If the AI closes 500 conversations, that's $495 a month in outcome charges. A handover that ends a Procedure also counts as an outcome under Intercom's outcome definitions, so the bill reaches $990 only if every one of the 500 handovers ends a Procedure. On an Intercom helpdesk plan each teammate also needs a seat, while Fin bought for another helpdesk has no seat costs. I mark cost down to 6 because the bill climbs with every conversation Fin closes.
Choose Intercom Fin for fraud and scam conversations if:
- You want each escalation type sent to a separate team from inside the AI setup.
- You mark accounts under review with an attribute and want Fin to stay silent on them.
- You want a published per-outcome rate.
Don't choose Intercom Fin for fraud and scam conversations if:
- Your team isn't on Intercom and doesn't want to buy Fin on its own.
- You need the fraud team's questions asked before the handover without building a Workflow.
- You want a bill that stays level as the AI closes more conversations.
For more on Intercom Fin, read our complete guide, browse the Intercom Fin alternatives roundup or see our My AskAI vs Intercom Fin comparison.
Can Zendesk AI agents handle fraud and scam conversations safely?
TL;DR: Zendesk AI agents lay out an after-hours switch step by step and cover 1 of the 6 jobs fully. The automatic email screen can't be adjusted, and 1,000 conversations cost about $950 a month pay-as-you-go ($712.50 committed) in resolutions, on top of Suite seats.
Zendesk AI agents run inside Zendesk on messaging and email. Zendesk's financial-services page says its AI agents route sensitive matters to the right support agent.
How do Zendesk AI agents handle a fraud report end to end?
Zendesk's escalation guide says a handover can happen when an inquiry is "complex, urgent, or sensitive", and you build the flows that do it. On email, requests on topics an AI agent isn't suited to answer are escalated before the AI engages. Zendesk's email article says that decision happens automatically, with no settings to change it. I hold this job at 7 because you can't tune that screen to your own fraud topics.
Answers come from template replies in escalation flows and generative procedures. An email screened out this way gets no AI reply at all (useful for reviews), but the articles name no control for review wording. The financial-services page lists payment status checks and routine verification requests, and signed-in customers can get restricted help-center answers. Approved steps, reviews and status questions each get a 6 from me.
Before escalating, the AI agent can gather details such as an order number, name or email, add tags and update fields, and the ticket keeps the conversation history. With no summary step in the articles, handing over is a 7. Each flow has an escalation team field, and an availability block escalates by email when nobody is online. Because Zendesk's article sets out that switch step by step and you can see where a 3am report goes, reaching the right person fast gets an 8.
I score setup 6, because you build the flows in a flow builder and the availability check needs a developer step.
How it handles the 6 things a support team needs
Zendesk AI agents cover 1 of the 6 jobs fully, and that one is the after-hours route.
Job | Zendesk AI agents |
Spots the conversations that aren't normal tickets | ⚠️ partial: automatic email screen, flows you build |
Gives only your approved safety steps | ⚠️ partial: template replies in flows |
Keeps a review confidential | ⚠️ partial: screened emails get no reply |
Answers verification-status questions | ⚠️ partial: payment status, signed-in answers |
Hands over with the details | ⚠️ partial: gathers details, no summary step |
Reaches the right person fast, at any hour | ✅ team field and after-hours email escalation |
Who's using Zendesk AI agents for fraud and account-review conversations?
InExchange, a business-document fintech, uses Zendesk's AI to send customer inquiries straight to the right department. Before that, every question landed in the same inbox and someone forwarded it by hand. The story credits Zendesk's AI as a whole and gives no fraud-specific detail. If someone on your team forwards fraud reports to the right people by hand today, that's the same problem the story describes.
What does Zendesk AI agents cost at 1,000 conversations a month?
Zendesk's pricing page lists automated resolutions at $2.00 pay-as-you-go or $1.50 committed. Suite Team includes 5 per agent each month, so the five agents I've assumed get 25, and the other 475 conversations the AI closes cost $950 a month pay-as-you-go ($712.50 committed). Assisted escalations don't count against the allowance. Cost is a 4, because the pay-as-you-go bill is about three times our $313.
Choose Zendesk AI agents for fraud and scam conversations if:
- You want after-hours escalation by email built into the AI's flow.
- You want an escalation team set on each flow.
- You want emails on topics the AI isn't suited to answer escalated without any setup.
Don't choose Zendesk AI agents for fraud and scam conversations if:
- You want to decide yourself which emails skip the AI.
- You want a lower bill at this volume, since resolutions come on top of seats.
- You want a summary written on every handover.
For more on Zendesk's AI, read our complete guide, browse the Zendesk AI alternatives roundup or see our My AskAI vs Zendesk AI agents comparison.
Can Decagon handle fraud and scam conversations safely?
TL;DR: Decagon names fraud alerts and dispute workflows among the account issues its agents handle and transfers calls to a person with a summary, covering 2 of the 6 jobs fully. Its homepage and product pages lead to a demo and show no price.
Decagon builds AI agents for large support teams across chat, email and voice, and it connects to a separate helpdesk for the human side.
How does Decagon handle a fraud report end to end?
Decagon's financial-services page lists password resets, balance inquiries, fraud alerts and dispute workflows among the secure account issues its agents handle around the clock. Its operating procedures set rules for escalations across chat, voice and email, and a detection system catches manipulation attempts and escalates them to a person. Naming fraud alerts, plus escalation rules you write, earns an 8 on spotting these conversations.
Watchtower reviews every conversation against criteria your team writes in plain language, and I read it as a quality check after the fact, useful for your QA lead.
Approved steps get a 7 from me, as Decagon's guardrails cover brand voice, escalations and made-up answers. No page names a control for what the AI says about an account under review, so review wording is a 6. Status questions are also a 7, with balance inquiries and secure account issues in scope and calls authenticated by voice.
Handover gets an 8, because calls go to a person with a concise summary and Decagon's agent assist tool promises full-context handoffs. The agents run 24/7, which I count in Decagon's favor for a 3am fraud report, but the pages show no team-level routing or priority rules, so reaching the right person fast is a 7. A demo-led enterprise implementation puts setup at 4.
How it handles the 6 things a support team needs
Decagon covers 2 of the 6 jobs fully, including a summary on every call it transfers.
Job | Decagon |
Spots the conversations that aren't normal tickets | ✅ fraud alerts named, escalation rules |
Gives only your approved safety steps | ⚠️ partial: guardrails on responses |
Keeps a review confidential | ⚠️ partial: no named control |
Answers verification-status questions | ⚠️ partial: balance and account issues |
Hands over with the details | ✅ transfer with a concise summary |
Reaches the right person fast, at any hour | ⚠️ partial: around the clock, routing unshown |
Who's using Decagon for fraud and account-review conversations?
Chime is Decagon's headline fintech customer, and Decagon puts Chime's resolution rate at 70% across chat and voice.
What does Decagon cost at 1,000 conversations a month?
Decagon's pricing article describes per-conversation and per-resolution pricing without a rate. I give cost a 2, because there's no figure you can put in a business case.
Choose Decagon for fraud and scam conversations if:
- You're an enterprise bank or fintech and many fraud reports come by phone.
- You want every conversation checked afterwards against criteria your team writes.
- You want the vendor's team to build the setup with you.
Don't choose Decagon for fraud and scam conversations if:
- You need a published price.
- You want to go live without a vendor-led implementation.
- You want the AI to work inside your current helpdesk.
For more on Decagon, read our complete guide, browse the Decagon alternatives roundup or see our My AskAI vs Decagon comparison.
Can Ada handle fraud and scam conversations safely?
TL;DR: Ada documents a sign-in step before sensitive answers and off-hours handoff paths, and it scores 6 or 7 on every job. Pricing comes from sales.
Ada is an enterprise AI agent for chat, email and voice, and it hands conversations over into a separate helpdesk such as Zendesk, Gorgias or Freshchat.
How does Ada handle a fraud report end to end?
Custom Instructions add rules for how the agent speaks, and they can apply to particular customers based on what Ada knows about them. Handoff management routes conversations on context. Ada's docs don't name fraud or scam topics, so I score spotting these conversations 7. Approved steps are a 7 too, because Custom Instructions guide answers within limits (with no pinned word-for-word reply), and with no named control for review wording, reviews score 6.
Ada's sign-in docs say sign-in "should happen before your AI Agent shares any sensitive data", and account lookups follow once the customer is signed in, a 7 on status questions. Handover is also a 7, since Ada can attach a summary to the handoff transcript on listed platforms and doesn't ask again for details it already has, which spares a scam victim from telling the story twice.
Ada's docs list off-hours handling as a use case and allow up to five active handoff routes, so I score reaching the right person fast 7. Setup scores 5 for an enterprise implementation run with Ada's team.
How it handles the 6 things a support team needs
Ada's docs cover each of the 6 jobs in part.
Job | Ada |
Spots the conversations that aren't normal tickets | ⚠️ partial: Custom Instructions, context routing |
Gives only your approved safety steps | ⚠️ partial: instructions within constraints |
Keeps a review confidential | ⚠️ partial: no named control |
Answers verification-status questions | ⚠️ partial: sign-in, then account lookups |
Hands over with the details | ⚠️ partial: summary on listed platforms |
Reaches the right person fast, at any hour | ⚠️ partial: off-hours paths, five handoffs |
Who's using Ada for fraud and account-review conversations?
Brigit, a fintech app, uses Ada for chat and later brought email into it. Ada's story says email stayed manual for a while "due to its sensitive nature and volume". For fraud reports I'd use the same order: let the AI prove itself on routine questions before it replies on anything sensitive.
What does Ada cost at 1,000 conversations a month?
Ada's pricing page leads to a demo booking. A buyer-data marketplace puts the median Ada contract at $72,000 a year, about $6,000 a month, and your price depends on volume and scope. With no published figure, cost is a 2, level with Decagon.
Choose Ada for fraud and scam conversations if:
- You're an enterprise team that wants customers signed in before any sensitive answer.
- You need documented off-hours paths for when no agent is available.
- You want one vendor across chat, email and voice.
Don't choose Ada for fraud and scam conversations if:
- You need a published price.
- You need more than five active handoff routes.
- You want your team to set it up in days.
For more on Ada, read our complete guide, browse the Ada alternatives roundup or see our My AskAI vs Ada comparison.
What does handling fraud and verification conversations with AI save you? (worked example)
TL;DR: At 1,000 fraud, scam and verification-status conversations a month, doing it all by hand costs about $2,400. My AskAI is the lowest published AI bill at about $313, and every AI row still leaves about $1,200 of team time on the conversations that must reach a person.
The basis for every row is 1,000 conversations a month in this category: fraud and scam reports, questions about what to do next, and questions about verification status. I've assumed 600 arrive by chat and 400 by email, with about two AI replies each. The AI closes about 500 of them, meaning status questions it can answer from the account and first-step questions where no money moved and no code was shared. The other 500 or so reach a person, including every fraud and scam report, every review or rejection, and any case where money moved or a code was shared.
For the no-AI row, I've assumed six minutes of team time per conversation for a team that already uses AI to help where a person does the work. That's priced at $0.40 a minute, which allows for overheads on top of the median US wage for customer service representatives of $21.53 an hour. The split and the timing are modeling assumptions I've made for this example.
Scenario | Plan modeled | Monthly cost | Effective $/conversation | Notes |
No AI | Your team handles every conversation | $2,400 | $2.40 | 1,000 conversations × 6 minutes × $0.40 |
My AskAI | Pro | $313 | $0.31 | 600 chat and 400 email conversations use 1,200 credits: $199 + 200 extra at $0.12, plus $40 of Task replies and $50 of AI Tagging; free trial |
Fini | Growth | Plan fee, not shown | - | 500 resolutions sit inside an allowance of at least 2,000, $0.89 each only past it; escalations free |
Intercom Fin | Per outcome | $495 to $990 | $0.50 to $0.99 | 500 outcomes at $0.99, up to 1,000 if every handover ends a Procedure; seats extra on Intercom helpdesk plans |
Zendesk AI agents | Suite Team | $712.50 to $950 | $0.71 to $0.95 | 475 resolutions at $1.50 committed or $2.00 pay-as-you-go after 25 included for five agents; the 500 that reach a person are assisted escalations, not counted; seats extra |
Decagon | Demo only | No price shown | - | Pricing article gives models, no rate |
Ada | Demo only | No price shown | - | Pricing page leads to a demo booking |
Every AI scenario also leaves roughly 500 conversations for a person, about $1,200 a month of team time at the same rate. That cost is the same whichever tool you pick. On those conversations, the AI saves your team the minutes spent asking which payment, when and whether a code was shared, because it collects the answers before the handover.
Per-resolution bills stay modest here because half of these conversations should reach a person anyway. We bill per ticket, in credits, whether the AI finishes it or hands it over, and add-ons such as Tasks and AI Tagging bill on top on every plan, which is why our row includes them. Our ROI calculator runs the same sums on your own volume.
So which fraud detection AI agent is best for customer support?
TL;DR: My AskAI is the pick for teams that want fraud topics, approved wording and detailed handovers set up inside their current helpdesk, Fini is the runner-up for a ready-made fraud-report flow, and Intercom Fin is third for sending each kind of escalation to a separate team.
We finish first on 66, nine points ahead of Fini, and six of those points come from setup effort and cost. Your approved safety wording goes out word for word, accounts under review get our say-nothing setting, and every handover carries a summary, with the fraud team's details collected first on live chat. All of it runs inside Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot, at the lowest published bill for this volume.
Fini, on 57, suits a fintech team that wants the vendor's own fraud-report flow and verification holds cleared from live data. Intercom Fin, on 56, fits a team that wants each escalation type routed to a different team through the AI setup. And if you run a financial-services business that already has experience building agents, building your own is a sensible option, given how bespoke bank setups and data silos tend to be.
Whichever tool you choose, this is the rollout order I recommend:
- List your fraud, scam and review topics and set the AI to draft internal notes only on them, while it answers routine payment questions.
- Add your approved safety wording as exact answers and let the AI give it.
- Let the AI answer verification-status questions from live account data.
- Let it collect the fraud team's details before each handover.
- Review a week of handovers with your fraud team before you widen anything.
The creator-monetization platform is widening its AI one category at a time, and the crypto-tax software company tuned its escalation behavior before it switched on direct replies. To set up your own fraud and scam topics, start with our Guidance page, then try My AskAI free for 30 days on your own conversations.
FAQs
How can AI help with KYC?
In support, AI helps most with the "why is my verification still pending?" question. When it can read the customer's real status, it tells them what's missing, such as a document, or that the wait is normal, and it hands reviews and rejections to a person with your approved wording. The document and selfie checks at signup belong to a compliance tool, and we treat proving who is asking in a conversation as a separate job.
Can an AI agent tell a fraud report or a scam from a normal "where is my payment?" question, and what does it do differently?
Yes, once you name the topics in plain language. A good setup takes "I didn't make this payment", "someone asked me for a code" and "my account is frozen" out of the routine path, gives your approved first steps and hands the conversation to the fraud team. In My AskAI we do that with Guidance rules and AI Tagging, Fini describes a ready-made fraud-report flow, and Intercom Fin and Decagon let you write escalation rules for it.
What should an AI agent never say to a customer whose account is under a fraud or compliance review?
It should never reveal that a review exists or why, guess at the outcome or a timeline, or ask for a PIN, password or one-time code. It gives the status line your compliance team approved and hands over. Banks also carry legal duties here, so have compliance sign off on the exact words before the AI uses them.
Can the AI answer "why is my verification still pending?" without a person, and when must it hand over?
Yes, when it can read the live status (we do it through User Data). A missing document or a normal wait is something the AI can answer and close on its own. A status under review, a rejection or a dispute goes to a person with the approved wording. I hold every tool to one rule here: a customer who asks for a person always gets one, whatever the status.
Does the fraud team get the conversation, the account details and what the AI already did, or do they start again?
That depends on the tool. The best setups ask the fraud team's questions once (which payment, when, how the customer was contacted, whether a code was shared), then hand over with a summary and a record of what the AI said. We write a summary before every escalation, Fini and Decagon hand over with full context or a summary, and Intercom Fin gathers the details in a Workflow after the handover.
Does a fraud report at 3am reach a person at 3am?
Only if the topic routes to an on-call person or team whatever the hour. Otherwise the AI should tell the customer clearly what happens next and when, and give them the steps to protect themselves meanwhile. Zendesk's AI agents show an after-hours email escalation step by step, and in My AskAI the fraud tag or handover sets off your helpdesk's own routing rules.
