The fraud detection and prevention market in BFSI is projected to grow from $7.78 billion in 2026 to $15.06 billion by 2031, at a CAGR of 14.1%, according to MarketsandMarkets. The growth is being driven by rising digital transactions, increasing fraud losses, and stronger regulatory pressure on financial institutions.
For banks, fraud detection is no longer just about spotting a suspicious transaction. Teams also need to catch account takeovers, payment fraud, unusual customer behavior, and identity risks in real time, while keeping false positives low and getting the right alerts to investigators quickly. As transaction volumes grow, doing all of that manually becomes difficult to scale. AI tools can automate much of the detection, risk scoring, alerting, and investigation workflow.
In this guide, we compare 8 AI tools to see which are best suited for fraud detection and alert automation in banking, based on their detection capabilities, real-time monitoring, integrations, compliance, scalability, and pricing.
TL;DR
Plivo: Best overall for banks that want fraud prevention and alert automation in the same communications stack. Its Fraud Shield monitors verification traffic in real time and blocks suspicious SMS pumping activity, while Verify supports customer authentication over SMS and voice.
Vapi: Best for developer-led banking teams that want to build highly customized fraud verification and alert workflows using their choice of LLM, voice, transcription, and telephony providers.
Retell AI: Best for teams that want to quickly automate fraud-alert callbacks, customer verification, and escalation to human agents. Retell specifically supports banking workflows such as fraud-alert callbacks.
Bland AI: Best for high-volume outbound fraud alerts and customer verification campaigns.
Synthflow AI: Best for operations teams that want to build fraud-alert and verification call flows without relying heavily on developers.
ElevenLabs: Best when natural-sounding and multilingual conversations are important for customer fraud alerts and verification calls.
Twilio: Best for banks already using Twilio infrastructure and looking to add AI-powered fraud alerts and verification workflows.
LiveKit: Best for engineering teams building highly customized real-time fraud verification or multimodal customer experiences.
If you're looking for one platform that can cover fraud prevention at the verification layer, customer authentication, and automated fraud communication, Plivo is the option we'd shortlist first. Its Fraud Shield is also included at no additional platform cost; customers pay the underlying communication-channel charges.
What Actually Matters When Choosing AI Tools for Fraud Detection & Alert Automation
Fraud tools can look similar on paper, but the real differences show up once you're dealing with suspicious transactions in real time, false positives, customer verification, and the need to get alerts to the right person quickly.
Here are the areas worth paying attention to.
1. Real-Time Fraud Detection
Speed matters. The platform should be able to identify suspicious patterns or anomalies quickly enough for the bank to act before a transaction or verification attempt is completed. Real-time monitoring and timely response are also part of the layered security controls highlighted in Federal Reserve guidance for electronic banking.
2. False Positive Management
A system that flags everything suspicious is not necessarily useful. Too many false positives create more work for fraud teams and can frustrate legitimate customers. Look at how the platform scores risk, applies rules, and helps teams separate genuine fraud from normal customer behavior.
3. Customer Verification
Once suspicious activity is flagged, the bank may need to confirm whether the transaction or login was legitimate. Voice calls, SMS, OTPs, and other verification methods can help automate that step instead of sending every case to a human agent.
4. Automated Fraud Alerts
The platform should make it easy to notify customers immediately when something looks wrong. That could include a suspicious transaction, unusual login, OTP attempt, or account activity that needs confirmation.
5. Workflow Integrations
Fraud alerts rarely work in isolation. Look for integrations with transaction monitoring systems, banking platforms, CRM, case-management tools, authentication systems, and internal APIs so alerts can automatically trigger the right next step.
6. Human Escalation
Some cases will still need an investigator or support agent. The platform should be able to escalate high-risk or unclear cases without losing the context collected during the automated interaction.
7. Compliance and Data Security
Banks are dealing with highly sensitive customer and transaction data, so security controls, certifications, data residency, access management, and auditability all matter when evaluating a platform.
8. Scalability and Pricing
Fraud volumes can spike suddenly, especially during coordinated attacks. Look at how well the platform handles higher traffic, concurrent interactions, and the total cost of running detection, verification, and alert workflows at scale.
AI Tools for Fraud Detection & Alert Automation in Banking Compared
Platform | Best For | Pricing | Fraud / Alert Automation Fit | Compliance |
Plivo | Banks that want fraud prevention, verification, and automated customer alerts in one communications stack | $0.04/min | Fraud Shield, OTP verification, voice/SMS alerts, suspicious-traffic monitoring | SOC 2, HIPAA, GDPR, PCI DSS |
Vapi | Developer-led banks building custom fraud verification and alert workflows | 0.13–$0.33/min | Custom alert calls, transaction verification, integrations with fraud systems | SOC 2 Type II, GDPR; HIPAA and PCI options |
Retell AI | Faster deployment of fraud-alert callbacks and customer verification workflows | $$0.31/min for AI Voice Agents | Fraud callbacks, verification calls, human escalation, post-call analysis | SOC 2 Type I & II, HIPAA, GDPR |
Bland AI | High-volume outbound fraud alerts and customer verification | $0.14/min | Large-scale alert campaigns, live transfers, voicemail handling | SOC 2 Type II, HIPAA, PCI DSS |
Synthflow AI | No-code fraud alert and verification workflows | Pay-as-you-go | Visual workflows, automated callbacks, routing, CRM/API integrations | SOC 2, HIPAA, GDPR |
ElevenLabs | Natural-sounding and multilingual fraud verification calls | $6/mo | AI voice alerts, customer verification, multilingual conversations | SOC 2 Type II, HIPAA, GDPR, PCI DSS |
Twilio | Banks already using Twilio for authentication and customer communications | Pay-as-you-go | Voice/SMS alerts, OTP verification, fraud-response workflows | SOC 2, HIPAA, GDPR, PCI DSS |
LiveKit | Engineering teams building highly customized real-time verification experiences | $50/mo | Custom voice, video, and multimodal fraud verification workflows | SOC 2 Type II, GDPR, HIPAA support |
The main difference here is that Plivo combines fraud prevention at the verification layer with the communication tools needed to act on those alerts, while most of the other platforms are stronger on the communication and workflow side rather than fraud detection itself.
1. Plivo
Plivo is one of the stronger options for banks that want to combine fraud prevention, customer verification, and automated fraud alerts in the same communications stack. Alongside AI voice agents, SMS, and voice verification, Plivo includes Fraud Shield, which monitors verification traffic in real time and blocks suspicious activity such as SMS pumping.
That makes it useful at two points in a fraud workflow: helping prevent abuse at the verification layer, and automating what happens after a bank's fraud system flags suspicious activity, such as calling or messaging a customer to confirm a transaction.
Key strengths
Built-in fraud protection: Fraud Shield analyzes verification traffic in real time and can automatically block activity identified as potential SMS pumping.
Suspicious traffic monitoring: Plivo can flag patterns such as sudden traffic spikes, unusual destinations, and potential account takeover activity.
Customer verification: Banks can use Plivo Verify for OTP-based authentication over SMS and voice, which is useful for login, transaction, and account verification workflows.
Automated alerts: Voice and SMS can be used to immediately reach customers when suspicious account activity needs confirmation.
Fraud controls: Geo Permissions and traffic thresholds let teams restrict destinations, set sending limits, and trigger alerts or blocks when unusual traffic patterns appear.
Integrated communications stack: Banks can combine verification, fraud controls, voice calls, and messaging instead of managing a separate provider for every part of the customer-response workflow.
Limitations
Plivo's native fraud detection is strongest at the communications and verification layer. It is not a replacement for a bank's transaction-monitoring or core fraud-risk engine that analyzes card purchases, transfers, or broader behavioral patterns.
For those use cases, Plivo works better as part of the fraud stack: the bank's risk system identifies suspicious financial activity, while Plivo handles verification, customer outreach, alerts, and escalation.
Pricing
Plivo AI Voice Agents cost $0.04 per minute. For verification, Fraud Shield and OTP verification carry no separate platform fee, so businesses pay only for the SMS, voice, or WhatsApp channel used.
2. Vapi
Vapi is a good fit for banks that want to build their own fraud-alert and customer-verification workflows rather than use a tightly bundled platform. It gives developers control over the voice model, LLM, transcription provider, and telephony setup, which makes it easier to connect AI calling with an existing fraud or risk engine.
That flexibility can be useful when a bank already has fraud detection in place and mainly wants to customize what happens next, such as calling a customer to confirm a transaction, collecting a response, or escalating the case.
Key strengths
Highly customizable: Teams can choose different LLM, speech-to-text, and text-to-speech providers depending on the workflow.
Good for developer-led banks: Vapi is API-first, so engineering teams can build custom verification logic and connect calls with existing fraud systems.
Flexible telephony: Vapi supports its own US numbers and integrations with providers such as Twilio, Telnyx, and Plivo for broader telephony setups.
Useful for fraud-response workflows: Banks can use it to automate suspicious-transaction callbacks, customer verification, and escalation after a fraud system triggers an alert.
Enterprise security options: Vapi's Scale plan includes SOC 2, PCI, SSO, RBAC, and data-residency options, with HIPAA available as an add-on.
Limitations
Vapi does not provide native banking fraud detection. It works better as the voice and workflow layer connected to an existing fraud engine.
There are also more moving parts to manage. Telephony, LLMs, transcription, and voice providers can all be separate, which gives you flexibility but also makes the setup and final cost more complicated.
Pricing
Vapi charges $0.05 per minute for the platform layer, with model and provider costs charged separately. For this comparison, a realistic all-in cost is roughly $0.13 to $0.33 per minute, depending on the stack you choose.
3. Retell AI
Retell AI is a good fit for banks that want to get fraud-alert and customer-verification workflows live quickly without building the entire voice stack themselves. It combines agent building, calling, monitoring, transfers, and post-call analysis in one platform.
For fraud workflows, it can sit on top of an existing risk or transaction-monitoring system and automate what happens after suspicious activity is flagged, such as calling the customer, confirming whether a transaction was legitimate, and escalating uncertain cases to a human agent.
Key strengths
Faster deployment: Retell brings agent building, testing, deployment, monitoring, and post-call analysis into one platform.
Useful for fraud callbacks: Banks can use AI agents to call customers after suspicious activity is detected and collect a confirmation or denial.
Human escalation: Calls can be transferred to a fraud or support agent when the situation needs manual review.
Post-call automation: Retell can generate summaries, call outcomes, sentiment data, and custom extracted fields that can be pushed back into downstream workflows.
Flexible telephony: Teams can use Retell's telephony layer or connect existing infrastructure through SIP and third-party providers.
Compliance coverage: Retell supports SOC 2 Type I and II, HIPAA, and GDPR requirements.
Limitations
Retell is not a native banking fraud-detection engine. It is better suited to the alert, verification, and response layer after another system has identified suspicious activity.
Pricing can also vary depending on the voice, model, telephony setup, and other components you use, so the lowest advertised rate may not reflect the final cost at scale.
Pricing
Retell AI costs $0.07 to $0.31 per minute for AI Voice Agents, depending on the voice, model, telephony setup, and other components selected.
4. Bland AI
Bland AI is a good fit for banks that need to automate high-volume fraud alerts and customer verification calls. It is built for large-scale inbound and outbound calling, which can be useful when suspicious activity triggers a lot of customer callbacks or transaction-confirmation requests.
For fraud workflows, Bland is strongest on the response side. It can call customers, follow a structured verification flow, collect a response, and hand higher-risk or unclear cases over to a human fraud team.
Key strengths
Built for high call volumes: Bland is designed for large outbound campaigns, which makes it useful when banks need to contact a large number of customers quickly.
Structured verification flows: Teams can build branching conversations for things like transaction confirmation, account verification, or follow-up questions.
Human handoffs: If a customer disputes a transaction or the situation needs manual review, the call can be transferred to a human agent with the conversation context.
Strong compliance coverage: Bland supports SOC 2, HIPAA, GDPR, and PCI DSS requirements.
Flexible setup: Banks can connect their existing telephony or SIP infrastructure instead of replacing everything.
Limitations
Bland is not a dedicated banking fraud-detection engine. It is better suited to automating alerts, verification calls, and customer response workflows after suspicious activity has already been identified.
It is also more API and enterprise-focused than some no-code platforms, so teams without much engineering support may find it a little heavier to set up and manage.
Pricing
Bland AI costs $0.14 per minute, with final costs depending on the plan, telephony setup, transfers, and enterprise requirements.
5. Synthflow AI
Synthflow AI is a good fit for banking teams that want to build fraud alert and customer verification workflows without relying too heavily on developers. Its no-code builder makes it easier to create structured call flows for suspicious transaction alerts, account verification, and follow-up conversations.
For fraud response, it works best as the communication layer after suspicious activity has already been flagged by another system.
Key strengths
No-code workflow builder: Operations teams can create fraud alert and verification flows without writing much code.
Useful for structured verification: Teams can build step-by-step conversations for confirming transactions, account activity, or customer identity.
Human handoffs: More complex or higher-risk cases can be routed to a human agent when needed.
Broad integrations: Synthflow can connect with CRMs, databases, ticketing tools, and external APIs, which makes it easier to plug into existing fraud workflows.
Compliance coverage: Synthflow supports SOC 2, HIPAA, and GDPR requirements.
Limitations
Synthflow does not provide native banking fraud detection. It is better suited to automating customer alerts, verification calls, and follow-up workflows after a fraud system has already identified suspicious activity.
It also gives technical teams less control than more developer-focused platforms like Vapi or LiveKit, which may matter if you are building very customized fraud-response logic.
Pricing
Synthflow uses a pay-as-you-go pricing model, with total costs depending on call volume, telephony, AI models, and the features used.
6. ElevenLabs
ElevenLabs is a strong option for banks that care about how fraud alert and verification calls actually sound. Its biggest advantage is natural-sounding voice quality, which can make suspicious-activity calls feel less robotic and easier for customers to engage with.
It is especially useful for banks serving customers across multiple regions, where multilingual fraud alerts and verification calls may be part of the workflow.
Key strengths
Natural-sounding voices: ElevenLabs is one of the stronger options for making automated fraud alerts and verification calls feel more human.
Multilingual support: Useful for banks that need to reach customers in different languages.
Structured verification calls: Teams can use AI agents to confirm suspicious transactions, account activity, or other flagged events.
Flexible telephony setup: ElevenLabs can connect with existing telephony providers and SIP-based infrastructure.
Strong compliance coverage: ElevenLabs supports SOC 2 Type II, HIPAA, GDPR, PCI DSS, and several ISO certifications.
Built-in agent tools: Teams can use workflow builders, knowledge bases, and configurable agents to manage different fraud-response scenarios.
Limitations
ElevenLabs is not a native banking fraud-detection platform. It works better on the customer communication and verification side, after suspicious activity has already been flagged by another system.
It is also more voice-focused than end-to-end fraud workflow-focused, so banks may still need other systems for detection, case management, or deeper risk analysis.
Pricing
ElevenLabs starts at $6 per month.
7. Twilio
Twilio is a good fit for banks that already use its communications infrastructure and want to add automated fraud alerts and verification workflows on top. It gives teams the telephony, messaging, and orchestration layer while still letting them connect their own fraud systems, LLMs, and business logic.
For banks with an existing Twilio setup, this can make it easier to trigger customer calls or messages when suspicious activity is detected without bringing in a completely separate communications stack.
Key strengths
Owned telephony infrastructure: Twilio operates its own voice network, routing, phone numbers, and SIP infrastructure.
Voice + messaging: Banks can combine voice calls, SMS, and other channels for fraud alerts and customer verification.
Bring your own LLM: Teams can connect the AI model they prefer instead of being locked into one provider.
Good for custom fraud workflows: Twilio can connect with existing transaction-monitoring or fraud systems and trigger customer outreach when an alert is raised.
Strong compliance coverage: Twilio supports SOC 2, HIPAA, GDPR, PCI DSS, and multiple ISO certifications.
Works well for existing Twilio users: If your banking communication stack already runs on Twilio, adding fraud-response automation is a more natural extension.
Limitations
Twilio is not a dedicated banking fraud-detection platform. It is stronger on the alerting, verification, and communications side after suspicious activity has already been detected.
It also takes more technical setup than some newer AI calling platforms. Teams still need to connect the fraud logic, AI model, and backend workflows themselves.
Pricing
Twilio uses a pay-as-you-go pricing model, with final costs depending on voice, messaging, AI, phone numbers, and other services used.
8. LiveKit
LiveKit is a developer-first platform for banks that want to build highly customized real-time fraud verification experiences. It gives engineering teams more control over the voice, video, AI models, telephony, and application logic behind each interaction.
For fraud workflows, it is most useful when a bank wants to build its own response layer around an existing fraud engine, such as transaction verification calls, step-up authentication, or more complex customer confirmation flows.
Key strengths
Built for real-time AI: LiveKit is designed for low-latency voice and video interactions, which helps fraud verification conversations feel more responsive.
Flexible AI stack: Developers can choose their preferred speech-to-text, LLM, and text-to-speech providers.
Native telephony support: LiveKit supports inbound and outbound calling through SIP and can also provide phone numbers.
Good for custom verification workflows: Engineering teams can build their own fraud alerts, customer confirmation flows, escalation logic, and backend integrations.
Multimodal support: LiveKit can go beyond voice into video and other real-time experiences, which may be useful for more advanced verification workflows.
Compliance support: LiveKit supports SOC 2 Type II, GDPR, CCPA, and HIPAA requirements.
Limitations
LiveKit is not a native banking fraud-detection engine. It is better suited to the verification and response layer once suspicious activity has already been identified.
It also requires more engineering effort than most platforms on this list, so it may not be the best fit for banking operations teams that want something they can configure and launch with minimal development work.
Pricing
LiveKit starts at $50 per month, with additional usage costs depending on agent sessions, telephony, and the AI services used.
Choosing the Right AI Tool for Your Fraud Automation Use Case
The right platform depends on where the gap is in your fraud workflow. Some banks need stronger verification and alerting, while others care more about high-volume outreach, custom integrations, or keeping everything inside one communications stack.
If fraud prevention and verification are the priority: Plivo is the strongest fit if you want fraud protection at the verification layer alongside OTPs, voice, SMS, and automated customer alerts. Its Fraud Shield adds an extra layer of protection against suspicious verification traffic, while the same stack can be used to reach customers when something needs confirmation.
If high-volume fraud alerts are the priority: Bland AI is worth considering when you need to run a large number of outbound verification or fraud-alert calls. Plivo also works well here if you want those alerts tied more closely to your verification and communications infrastructure.
If you want to launch quickly: Retell AI is a good option for teams that want to get fraud callbacks, customer verification, and escalation workflows live without building the entire voice stack from scratch.
If you want a no-code setup: Synthflow AI makes sense for operations teams that want to build and adjust fraud-alert workflows without depending too heavily on developers.
If your engineering team wants more control: Vapi gives developers more freedom to choose their own LLM, voice, transcription, and telephony providers. LiveKit is a better fit if you are building something highly customized or extending verification beyond voice into real-time multimodal experiences.
If you want that flexibility without managing as many separate providers, Plivo sits in a useful middle ground between a modular stack and a more integrated platform.
If you already use Twilio: Twilio is the natural option if your bank already runs authentication and customer communications on its infrastructure. If you are starting fresh, though, it is worth comparing that setup against Plivo, especially if you want fraud protection, verification, and customer communication handled more tightly together.
The main thing is not to look at fraud detection and customer alerts as two completely separate workflows. The faster you can move from spotting suspicious activity to verifying the customer and taking the next action, the better. For banks looking for that balance in one communications stack, Plivo is the platform we would shortlist first.
Looking for a More Integrated Fraud Alert & Verification Stack?
If you want to avoid managing separate tools for verification, fraud controls, voice, SMS, and customer alerts, Plivo is one of the stronger options to look at.
It combines fraud protection at the verification layer with OTP authentication, AI voice agents, SMS, and automated customer communication. That makes it useful for banks that want to move quickly from detecting suspicious activity to verifying the customer and triggering the right next step.
Plivo also gives teams one communications stack for fraud alerts, transaction confirmation, account verification, and escalation, instead of stitching together multiple providers.
With Fraud Shield built into its verification layer and AI Voice Agents priced at $0.04 per minute, Plivo is a practical option for banks looking to keep fraud-response workflows simpler and easier to scale.
Explore Plivo for fraud alert and verification automation
Frequently Asked Questions
What are AI tools used for in banking fraud detection?
AI tools can help banks monitor suspicious activity, score risk, automate customer verification, trigger fraud alerts, and route higher-risk cases to human teams. Depending on the platform, they can also support OTP verification, voice callbacks, SMS alerts, and post-alert workflows.
How can AI automate fraud alerts in banking?
Once suspicious activity is flagged, AI can automatically contact the customer, confirm whether a transaction or login was legitimate, collect their response, and escalate the case if needed. This helps banks move faster without relying on manual calls for every alert.
Which AI tool is best for fraud alert automation in banking?
There is no single best option for every bank. Plivo is a strong all-round choice if you want fraud protection at the verification layer, OTP authentication, voice and SMS alerts, and customer communication in one stack. Retell AI is useful for faster deployment, while Vapi and LiveKit are better suited to developer-led teams that want more control.
What should banks look for in an AI fraud automation platform?
Focus on real-time detection capabilities, customer verification, alert automation, integrations, human escalation, compliance, data security, scalability, and the total cost of running the workflow at scale.
Can AI completely replace human fraud teams?
Not really. AI is useful for spotting suspicious patterns, automating verification, and handling repetitive alert workflows, but complex or high-risk cases still need human judgment. The strongest setup is usually one where AI handles the first layer and sends the right cases to investigators when needed.
