The outcomes teams like yours see with Tars
Purpose-built AI agents for financial services and fintech
Customer Support
Answer every customer in seconds, and keep your team for the cases that need a person.
Resolve card and payment disputes the moment they're reported
The agent takes a disputed-charge report in the conversation: the transaction, the reason, whether the card is lost or stolen, and the documents the dispute needs. It runs the intake the same way every time, follows the rules that apply to you (Reg E for banks, your scheme rules for a PSP), and sets the right expectations on provisional-credit and chargeback timelines.
It works on web, WhatsApp, and SMS, writes the case to your dispute, card, and payment systems, and pulls in a fraud or operations specialist with the full thread when a claim needs a human eye.
Customers get a calm, immediate response on the channel they reported from, and your team picks up only the disputes that genuinely need them.
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Answer everyday money questions without the call queue
Balances, transaction history, routing and account numbers, statement and card questions, how to reset access, the agent handles the FAQ and support intent that fills your call center, answering only from your approved policies, not the internet's.
It reads your core banking, ledger, and knowledge sources to give the right answer, and stays inside the current question instead of jumping journeys when a customer asks something unrelated mid-conversation.
CLCU cut inbound calls 12% and saw a 20% drop in contact-form submissions with a Tars agent, and VM Group reduced support requests by 45%.
Confirm fraud and transaction alerts in two-way conversations
When a transaction looks risky, the agent reaches the customer on WhatsApp or SMS and asks the one question that matters: was this you? A reply confirms the charge or freezes the card, in the same thread, in seconds.
It writes the outcome back to your fraud and card systems and escalates a confirmed-fraud case to your team with the full exchange attached.
You catch fraud faster, cut the false declines that frustrate good customers, and take the back-and-forth off your fraud line.
Take payment reminders and collections off the phones
The agent runs early-stage reminders and collections conversations: upcoming and missed payments, a BNPL installment coming due, the amount owed, a payment link, and the option to set up an arrangement, all in a respectful two-way chat instead of a dialer.
It runs the payment step as a strict, deterministic flow so card and bank details are collected exactly the way compliance requires, and hands hardship and dispute cases to a human with the history intact.
More reminders land and get acted on, more payments clear without an agent on the phone, and your collections team focuses on the accounts that need a real conversation.
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Customer Acquisition
Turn every inquiry into a qualified application, before it ever reaches a person.
Pre-qualify borrowers before they reach a loan officer
The agent has the conversation a borrower actually starts with: "I'm looking for a loan of 15,000 to buy a car." From there it qualifies purpose, amount, employment status, and the documents that product and employment type require, the same questions your best loan officer or underwriting team would ask. It runs the same job for a digital lender's BNPL check or a wealth app's investor-suitability screen.
It works across web, WhatsApp, and SMS, recommends the right loan, savings, or investment product, and writes the qualified lead and its answers into your CRM or loan origination system so your team picks up a warm, ready file.
Tata Motors Finance generated 69,000+ leads and reached a 16.8% loan conversion rate running this kind of acquisition agent.
Open accounts and complete KYC in the conversation
The agent walks a new customer through opening an account, whether that's a checking and savings account at a bank or a neobank or wallet signup at a fintech: it collects the application details, runs identity and KYC steps, and tells the applicant exactly which documents to upload for their situation.
Identity verification and data collection run as deterministic steps so every applicant is taken through the same compliant sequence, with the agent passing the completed application into your onboarding stack.
More applications get finished instead of abandoned at a long form, and the ones that reach your team are clean and ready to approve.
Run cross-sell campaigns customers actually open
The agent runs outbound campaigns on the channels your customers read: a card upgrade, a better savings rate, a pre-approved loan offer, a top-up on a BNPL line, delivered on WhatsApp and SMS as a two-way conversation the customer can reply to.
When someone replies, the agent qualifies the interest and books the next step on the spot, and writes engaged contacts back to your CRM for the relationship team.
SBI and Union Bank saw 87% and 88% open rates on WhatsApp campaigns, and American Express reached 49.3% goal completion across tens of thousands of marketing conversations.
Route qualified leads to the right team
Not every inquiry should go to the same place. The agent reads what the customer wants, a mortgage, a business loan, wealth servicing, a payments-platform inquiry, and routes the qualified lead to the right relationship manager, branch, or sales pod, with the full conversation and the answers it collected.
Because it's one continuous thread, your team opens the lead already knowing the purpose, the amount, and the documents on file, instead of starting the discovery call from zero.
Fewer leads go cold in a shared inbox, and your relationship managers and sales teams spend their time on conversations that are ready to close.
How American Express turned automated conversations into completed actions
American Express needed its SMS marketing and website conversations to do more than start a dialogue, they needed to finish the action the customer came for. Tars AI agents ran those conversations end to end across SMS and web, guiding tens of thousands of customers from the first message to the goal, answering questions and keeping each conversation on track. The result: a 49.3% goal completion rate across tens of thousands of automated conversations.
One conversation per customer, across every channel and every team.
A customer starts a loan question on your website at lunch, replies on WhatsApp after work, and gets the confirmation by SMS. In Tars that is one conversation, not three disconnected tickets. The channel is just where each message arrived. There is no separate live-chat tool either. Your AI agent and your people work in the same thread. The agent resolves what it can, and when a dispute, a hardship case, or a high-value lead needs a person, it hands over with the whole story attached: what the customer asked, what was answered, and what's still open. Your banker, advisor, or specialist reads the full thread before replying. Your customer never repeats themselves. And every handoff stays inside your compliance boundary.
How Tars Agents Get Better
The Tars agent flywheel
Standing up an agent your customers trust isn't a click a button and you're done story. Tars closes the loop end to end: train, test, deploy, learn, improve. More conversations get resolved instantly, and fewer reach your team, with every interaction.
Train
Connect your knowledge base, past conversations, and the systems your team already uses. The agent learns your products, your policies, and your customers, configured to your own data and rules.
Test
Simulate the agent against real customer questions before launch. Failure modes become validated evaluators, so you see real accuracy before a single customer sees it.
Deploy
Go live on web, WhatsApp, SMS, and email when the numbers say it's ready, with code based and LLM as judge evaluators scoring every conversation.
Get Insights
See which questions the agent struggles with, why escalations happen, and where customers drop off, with resolution broken down by use case.
Improve continuously
Close the gaps, re test, and raise resolution month over month. Each loop resolves more and escalates less.
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