MODA EN TRANSICIÓN /08/10

back office agent

Frontier AI models evaluated on real Servicing tasks in retail and business banking.

economic value

We are Rulebase: ML engineers and product people who have worked with the largest financial services companies in the world, on products that serve more than 30 million end users.

Bank Arena drops an agent into a working bank: five back-office applications, seven card charges, an approver who says no, and a 72-hour clock. It has to sort each charge, build the evidence, get approval, file with the card network and tell the customer the truth.

29 graded runs. 6 models. Nobody has finished the task.

Opus 5.5 scored 40 on all eight runs: each one told the customer a credit was final before the network settled. Uncapped, those runs score 87 to 91. GPT 6.1 Sol is one run, cut off at 72 virtual hours; Gemini 4 Argon is two. Not enough for a ranking.

┌────────────────────────────┐
│ ▒▒▒▒ •••• •••• •••• 4021 │
│ VOLTLINE*ONLINE 1,349.99│
└─────────────┬──────────────┘
│ disputed
▼
[HOLD] ──▶ [EVIDENCE] ──▶ [NETWORK]
│ │
customer ◀── credit ◀────────┘
"final"? × not settled yet

Disputes & fraud

3 tasks · 1 built and benchmarked

Card disputes, held funds and account takeover. The agent sorts each charge, builds the evidence, gets approval, files with the card network, and has to tell the customer the truth while late network events keep arriving.

 SENDER ────── 250.00 ──────▶ PAYEE
│ │
│ ┌──────────────┐ │
└──────▶│ CLEARING │◀────┘
└──────┬───────┘
│
┌──────────┼──────────┐
▼ ▼ ▼
REVERSAL LATE DEBIT RECALL

Payments

4 tasks

Instant transfers that reverse or arrive late, merchant settlements that collide with refunds and disputes, rejected deposits and voucher top-ups. The money moves first and the records have to catch up.

 ┌────────────┐
│ ┌────┐ │ [x] identity
│ │ () │ │ [x] address
│ │ /\ │ │ [ ] source of funds
│ └────┘ │ [!] sanctions hit
│ ID 0412 │
└────────────┘ STATUS REVIEW
▓▓▓▓▓▓░░░░░░ 2 / 4

Onboarding & compliance

3 tasks

KYC and KYB reviews with missing documents, re-KYC that stalls halfway, and account closures that have to wind down holds and residual funds before the account can close.

BANK LEDGER STATEMENT
─────────── ─────────
1,349.99 ══════ 1,349.99
865.40 ══════ 865.40
412.00 ──╳── 421.00
118.25 ══════ 118.25
─────────── ─────────
BREAK Δ -9.00 1 OF 4 OPEN

Finance

2 tasks

Reconciling payments against settlement files and recovering breaks upstream, and loan payoffs racing an overcollection.

 09:00 17:00
├────●──────●───●────────●──────▶
T1 T2 T3 T4
QUEUE ▓▓░ ▓▓▓▓░ ▓▓▓▓▓▓░ ▓▓▓▓▓▓▓
STATE ok ok !! ??
──────────────────────────────────
state changes under open tickets

Operations

1 task

A live incident shift: many tickets at once, state changing underneath them, and a queue that keeps growing.

results

Nobody completed the task. Scores are out of 100, averaged across each model's runs.

GPT 6.1 Sol has the highest mean, 88, from a single run cut off at 72 virtual hours. Gemini 4 Argon averages 64.5 over two runs; three more errored.

Claude Sonnet 5.5 is the best value: 53.0 over six runs at $4.00 a run. DeepSeek V4 Pro scores 47.6 for $1.90.

Opus 5.5 scored 40 on all eight runs. Each one told the customer a credit was final before the network settled; uncapped, those runs score 87 to 91.

Haiku 5.5 is the cheapest at $0.42 a run, and the lowest at 20.4.

COST

GPT-6.1 Sol costs $10 a run and passes 25% of the time, so each solved task costs about $40. A back-office analyst at $55 an hour needs around six hours: $330.

Four models beat the human on cost per solved task. Claude Fable 5.1 and Kimi K3.1 Pro fail so often that each success costs $1,393 and $7,100.

FIGURE 2. Each model's return per dollar against how often it passes. Human baseline assumes $55 an hour for six hours. Models that never passed (Grok 4.7, Muse Wonder, Qwen3.8 Max) have no return.

trajectories

Every run is a sequence of actions across five bank applications. This is how an Opus 5.5 run goes wrong: the work is right until the last message.

All eight Opus runs end the same way. They file with the card network, then tell the customer the credit is final before the network has settled. That one message caps the score at 40.

{
  "ticket": 48213,
  "comment": "cmt_48213_10",
  "body": "The card network accepted the fraud dispute in full, and the $1,349.99 credit on your account is now final."
}

{
  "comment": "cmt_48213_10",
  "posted": true,
  "ledger": {
    "txn_0002": {
      "NETWORK_SETTLEMENT": null
    }
  }
}

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FIGURE 3. One Opus 5.5 run, step by step. The five applications are the bank's back office: Trackboard, Casevault, Issuerline, Opsdesk and Caseboard. Synthetic data only. Round 3, tools lane.